From 7063eab123c47e57d28065bc88a71993b2ccf323 Mon Sep 17 00:00:00 2001 From: huzunjie Date: Tue, 13 Oct 2026 09:50:58 +0800 Subject: [PATCH] feat(postgresql): support custom metadata schema via dinky.metadata.schema Allow Dinky metadata tables to be created in a custom PostgreSQL schema (e.g. 'dinky' instead of the default 'public'). A single configuration entry controls JDBC URL, Flyway migrations, and MyBatis-Plus table name resolution. Configuration: dinky.metadata.schema: dinky (default: public) or environment variable DINKY_METADATA_SCHEMA Changes: New files: - DinkyMetadataProperties.java: schema config properties class - DinkySchemaInnerInterceptor.java: MyBatis-Plus DynamicTableNameInnerInterceptor that dynamically prepends schema prefix to all dinky_* table names (uses official setTableNameHandler(TableNameHandler) API with prefix-based matching, so any future dinky_* tables are automatically covered) Modified files: - application-postgresql.yml: added dinky.metadata.schema config, JDBC URL currentSchema parameter, Flyway default-schema/placeholders - MybatisPlusConfig.java: register schema interceptor under postgresql profile (between TenantLine and Pagination interceptors, using ObjectProvider so non-postgresql profiles are unaffected) - 10 Flyway migration scripts: replaced hardcoded 'public.' with Flyway placeholder '\.' and string literals 'public' with '\' - V20241205 migration script: 'enabled = 0' -> 'enabled::int = 0' for PostgreSQL boolean column compatibility during historical SMALLINT to BOOLEAN data migration - script/sql/dinky-pg.sql: removed all 'public.' prefixes so the manual initialization script works with any search_path Design notes: - Default schema is 'public', fully backward compatible - MyBatis-Plus schema interceptor is Profile-gated to postgresql only - Interceptor order: TenantLine -> DinkySchema -> Pagination, ensuring tenant ignoreTable matches original table names - Flyway validate-on-migrate remains false, so checksum changes for already-executed scripts do not break existing deployments - All other database profiles (MySQL, etc.) are unaffected --- .../configure/DinkyMetadataProperties.java | 40 + .../dinky/configure/MybatisPlusConfig.java | 24 +- .../DinkySchemaInnerInterceptor.java | 60 + .../main/resources/application-postgresql.yml | 15 +- .../postgresql/R20240708.1.1.0__release.sql | 20 +- .../postgresql/R20240729.1.1.0__release.sql | 18 +- .../postgresql/V20240506.1.0.2__baseline.sql | 1856 ++++++++--------- .../postgresql/V20240708.1.1.0__release.sql | 22 +- .../postgresql/V20240729.1.1.0__release.sql | 18 +- .../postgresql/V20240827.1.2.0__release.sql | 24 +- .../postgresql/V20241203.1.2.0__release.sql | 32 +- .../postgresql/V20241205.1.2.0__release.sql | 206 +- .../postgresql/V20241217.1.2.0__release.sql | 26 +- .../postgresql/V20250301.1.3.0__release.sql | 44 +- script/sql/dinky-pg.sql | 518 ++--- 15 files changed, 1528 insertions(+), 1395 deletions(-) create mode 100644 dinky-admin/src/main/java/org/dinky/configure/DinkyMetadataProperties.java create mode 100644 dinky-admin/src/main/java/org/dinky/interceptor/DinkySchemaInnerInterceptor.java diff --git a/dinky-admin/src/main/java/org/dinky/configure/DinkyMetadataProperties.java b/dinky-admin/src/main/java/org/dinky/configure/DinkyMetadataProperties.java new file mode 100644 index 0000000000..6ed65ab548 --- /dev/null +++ b/dinky-admin/src/main/java/org/dinky/configure/DinkyMetadataProperties.java @@ -0,0 +1,40 @@ +/* + * + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * + */ + +package org.dinky.configure; + +import org.springframework.boot.context.properties.ConfigurationProperties; + +import lombok.Data; + +/** + * Metadata properties for Dinky, used to configure metadata database connection behaviors + * such as custom PostgreSQL schema support. + */ +@Data +@ConfigurationProperties(prefix = "dinky.metadata") +public class DinkyMetadataProperties { + + /** + * The schema name for PostgreSQL metadata database. + * Defaults to {@code public} to maintain backward compatibility. + * Override with {@code dinky.metadata.schema} or environment variable {@code DINKY_METADATA_SCHEMA}. + */ + private String schema = "public"; +} diff --git a/dinky-admin/src/main/java/org/dinky/configure/MybatisPlusConfig.java b/dinky-admin/src/main/java/org/dinky/configure/MybatisPlusConfig.java index e349706822..bf78e4597d 100644 --- a/dinky-admin/src/main/java/org/dinky/configure/MybatisPlusConfig.java +++ b/dinky-admin/src/main/java/org/dinky/configure/MybatisPlusConfig.java @@ -20,6 +20,7 @@ package org.dinky.configure; import org.dinky.context.TenantContextHolder; +import org.dinky.interceptor.DinkySchemaInnerInterceptor; import org.dinky.interceptor.PostgreSQLPrepareInterceptor; import org.dinky.interceptor.PostgreSQLQueryInterceptor; import org.dinky.mybatis.handler.DateMetaObjectHandler; @@ -28,6 +29,7 @@ import java.util.Set; import org.mybatis.spring.annotation.MapperScan; +import org.springframework.beans.factory.ObjectProvider; import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean; import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty; import org.springframework.boot.context.properties.EnableConfigurationProperties; @@ -51,12 +53,13 @@ /** mybatisPlus config class */ @Configuration @MapperScan("org.dinky.mapper") -@EnableConfigurationProperties(MybatisPlusFillProperties.class) +@EnableConfigurationProperties({MybatisPlusFillProperties.class, DinkyMetadataProperties.class}) @Slf4j @RequiredArgsConstructor public class MybatisPlusConfig { private final MybatisPlusFillProperties autoFillProperties; + private final DinkyMetadataProperties metadataProperties; private static final Set IGNORE_TABLE_NAMES = ImmutableSet.of( "dinky_namespace", @@ -97,8 +100,22 @@ public PostgreSQLPrepareInterceptor postgreSQLPrepareInterceptor() { return new PostgreSQLPrepareInterceptor(); } + /** + * MyBatis-Plus interceptor that dynamically prepends a custom PostgreSQL schema + * prefix to all Dinky business table names. Only active when the + * {@code postgresql} profile is enabled and a non-{@code public} schema is configured. + * + * @return the schema interceptor instance (can be a no-op handler map) + */ + @Bean + @Profile("postgresql") + public DinkySchemaInnerInterceptor dinkySchemaInnerInterceptor() { + return new DinkySchemaInnerInterceptor(metadataProperties.getSchema()); + } + @Bean - public MybatisPlusInterceptor mybatisPlusInterceptor() { + public MybatisPlusInterceptor mybatisPlusInterceptor( + ObjectProvider schemaInterceptorProvider) { log.info("mybatis plus interceptor execute"); MybatisPlusInterceptor interceptor = new MybatisPlusInterceptor(); interceptor.addInnerInterceptor(new TenantLineInnerInterceptor(new TenantLineHandler() { @@ -120,6 +137,9 @@ public boolean ignoreTable(String tableName) { return !IGNORE_TABLE_NAMES.contains(tableName); } })); + // Add schema prefix interceptor after tenant interceptor so that ignoreTable + // still matches the original (un-prefixed) table names + schemaInterceptorProvider.ifAvailable(interceptor::addInnerInterceptor); interceptor.addInnerInterceptor(new PaginationInnerInterceptor()); return interceptor; } diff --git a/dinky-admin/src/main/java/org/dinky/interceptor/DinkySchemaInnerInterceptor.java b/dinky-admin/src/main/java/org/dinky/interceptor/DinkySchemaInnerInterceptor.java new file mode 100644 index 0000000000..f872219944 --- /dev/null +++ b/dinky-admin/src/main/java/org/dinky/interceptor/DinkySchemaInnerInterceptor.java @@ -0,0 +1,60 @@ +/* + * + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + * + */ + +package org.dinky.interceptor; + +import com.baomidou.mybatisplus.extension.plugins.handler.TableNameHandler; +import com.baomidou.mybatisplus.extension.plugins.inner.DynamicTableNameInnerInterceptor; + +/** + * MyBatis-Plus interceptor that dynamically prepends a custom PostgreSQL schema prefix to + * all Dinky business table names (those with the {@code dinky_} prefix). + * + *

When the configured schema is {@code public} or empty, this interceptor is a no-op, + * preserving the original behavior of querying tables in the default schema.

+ * + *

Using a prefix-based match (dinky_*) instead of an explicit table-name set means + * any future Dinky table will automatically receive the schema prefix without code changes.

+ * + *

Interceptor ordering note: Must be registered after + * {@link com.baomidou.mybatisplus.extension.plugins.inner.TenantLineInnerInterceptor} + * and before {@link com.baomidou.mybatisplus.extension.plugins.inner.PaginationInnerInterceptor} + * so that tenant's {@code ignoreTable} still matches the original (un-prefixed) table names.

+ */ +public class DinkySchemaInnerInterceptor extends DynamicTableNameInnerInterceptor { + + /** Only table names starting with this prefix receive the schema prefix. */ + private static final String DINKY_TABLE_PREFIX = "dinky_"; + + public DinkySchemaInnerInterceptor(String schema) { + // schema is empty, null, or "public" → no-op, keep original table names + if (schema == null || schema.isEmpty() || "public".equalsIgnoreCase(schema)) { + return; + } + + final String prefix = schema + "."; + TableNameHandler handler = (sql, tableName) -> { + if (tableName != null && tableName.startsWith(DINKY_TABLE_PREFIX)) { + return prefix + tableName; + } + return tableName; + }; + setTableNameHandler(handler); + } +} diff --git a/dinky-admin/src/main/resources/application-postgresql.yml b/dinky-admin/src/main/resources/application-postgresql.yml index eff2bdf64a..a0b74385e9 100644 --- a/dinky-admin/src/main/resources/application-postgresql.yml +++ b/dinky-admin/src/main/resources/application-postgresql.yml @@ -21,4 +21,17 @@ spring: password: ${POSTGRES_PASSWORD:dinky} driver-class-name: org.postgresql.Driver # The POSTGRES_ADDR variable is not officially provided. If you use docker, please manually add an env to support it. - url: jdbc:postgresql://${POSTGRES_ADDR:localhost:5432}/${POSTGRES_DB:dinky}?stringtype=unspecified \ No newline at end of file + url: jdbc:postgresql://${POSTGRES_ADDR:localhost:5432}/${POSTGRES_DB:dinky}?stringtype=unspecified¤tSchema=${dinky.metadata.schema:public} + flyway: + default-schema: ${dinky.metadata.schema:public} + schemas: ${dinky.metadata.schema:public} + create-schemas: true + placeholder-replacement: true + placeholder-prefix: '${' + placeholder-suffix: '}' + placeholders: + dinky_schema: ${dinky.metadata.schema:public} + +dinky: + metadata: + schema: ${DINKY_METADATA_SCHEMA:public} diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/R20240708.1.1.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/R20240708.1.1.0__release.sql index 0da1a45b36..606bceab9e 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/R20240708.1.1.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/R20240708.1.1.0__release.sql @@ -1,30 +1,30 @@ -- note: Rolling back SQL statements is only necessary to perform a rollback operation in the event of an automatic upgrade failure. The following SQL statements need to be manually executed -update public.dinky_sys_menu set "path"='/settings/alertrule', +update ${dinky_schema}.dinky_sys_menu set "path"='/settings/alertrule', "component"='./SettingCenter/AlertRule', "perms"='settings:alertrule', "parent_id"=6 where "id" = 116; -update public.dinky_sys_menu set "path"='/settings/alertrule/add', +update ${dinky_schema}.dinky_sys_menu set "path"='/settings/alertrule/add', "perms"='settings:alertrule:add' where "id" = 117; -update public.dinky_sys_menu set "path"='/settings/alertrule/delete', +update ${dinky_schema}.dinky_sys_menu set "path"='/settings/alertrule/delete', "perms"='settings:alertrule:delete' where "id" = 118; -update public.dinky_sys_menu set "path"='/settings/alertrule/edit', +update ${dinky_schema}.dinky_sys_menu set "path"='/settings/alertrule/edit', "perms"='settings:alertrule:edit' where "id" = 119; -ALTER TABLE public.dinky_task DROP COLUMN "first_level_owner"; -ALTER TABLE public.dinky_task DROP COLUMN "second_level_owners"; +ALTER TABLE ${dinky_schema}.dinky_task DROP COLUMN "first_level_owner"; +ALTER TABLE ${dinky_schema}.dinky_task DROP COLUMN "second_level_owners"; -- Delete the 1.1.0 record in the _dinky_flyway_schema_history table -DELETE FROM public."_dinky_flyway_schema_history" WHERE version = '1.1.0'; +DELETE FROM ${dinky_schema}."_dinky_flyway_schema_history" WHERE version = '1.1.0'; -UPDATE public.dinky_user SET "password" = '21232f297a57a5a743894a0e4a801fc3' WHERE "id" =1 and "password"= 'f4b3a484ee745b98d64cd69c429b2aa2'; +UPDATE ${dinky_schema}.dinky_user SET "password" = '21232f297a57a5a743894a0e4a801fc3' WHERE "id" =1 and "password"= 'f4b3a484ee745b98d64cd69c429b2aa2'; -ALTER TABLE public.dinky_resources ALTER COLUMN file_name TYPE varchar(64); +ALTER TABLE ${dinky_schema}.dinky_resources ALTER COLUMN file_name TYPE varchar(64); -alter table public.dinky_udf_manage drop column "language"; +alter table ${dinky_schema}.dinky_udf_manage drop column "language"; diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/R20240729.1.1.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/R20240729.1.1.0__release.sql index 23907a64b8..6b2a1cb975 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/R20240729.1.1.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/R20240729.1.1.0__release.sql @@ -1,16 +1,16 @@ # note: Rolling back SQL statements is only necessary to perform a rollback operation in the event of an automatic upgrade failure. The following SQL statements need to be manually executed -delete from public.dinky_sys_menu where parent_id = -1 and path = '/home'; +delete from ${dinky_schema}.dinky_sys_menu where parent_id = -1 and path = '/home'; -delete from public.dinky_sys_menu where parent_id = 164 and path = '/dashboard/list'; +delete from ${dinky_schema}.dinky_sys_menu where parent_id = 164 and path = '/dashboard/list'; -update public.dinky_sys_menu set path = '/dashboard/add', perms='dashboard:add' where path = '/dashboard/list/add'; -update public.dinky_sys_menu set path = '/dashboard/edit', perms='dashboard:edit' where path = '/dashboard/list/edit'; -update public.dinky_sys_menu set path = '/dashboard/delete', perms='dashboard:delete' where path = '/dashboard/list/delete'; -update public.dinky_sys_menu set path = '/dashboard/view', perms='dashboard:view' where path = '/dashboard/list/view'; +update ${dinky_schema}.dinky_sys_menu set path = '/dashboard/add', perms='dashboard:add' where path = '/dashboard/list/add'; +update ${dinky_schema}.dinky_sys_menu set path = '/dashboard/edit', perms='dashboard:edit' where path = '/dashboard/list/edit'; +update ${dinky_schema}.dinky_sys_menu set path = '/dashboard/delete', perms='dashboard:delete' where path = '/dashboard/list/delete'; +update ${dinky_schema}.dinky_sys_menu set path = '/dashboard/view', perms='dashboard:view' where path = '/dashboard/list/view'; -delete from public.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/dashboard-layout'; -delete from public.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/chart/add'; -delete from public.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/chart/edit'; +delete from ${dinky_schema}.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/dashboard-layout'; +delete from ${dinky_schema}.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/chart/add'; +delete from ${dinky_schema}.dinky_sys_menu where `parent_id` = 164 and path = '/dashboard/chart/edit'; diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20240506.1.0.2__baseline.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20240506.1.0.2__baseline.sql index 8cfd7b2dee..b483ed3084 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20240506.1.0.2__baseline.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20240506.1.0.2__baseline.sql @@ -33,10 +33,10 @@ $$ -- ---------------------------- --- Table structure for public.dinky_alert_group +-- Table structure for ${dinky_schema}.dinky_alert_group -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_group +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_group ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(50) NOT NULL, @@ -52,41 +52,41 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_group ); COMMENT - ON COLUMN public.dinky_alert_group.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_alert_group.id IS 'id'; COMMENT - ON COLUMN public.dinky_alert_group.name IS 'alert group name'; + ON COLUMN ${dinky_schema}.dinky_alert_group.name IS 'alert group name'; COMMENT - ON COLUMN public.dinky_alert_group.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_alert_group.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_alert_group.alert_instance_ids IS 'Alert instance IDS'; + ON COLUMN ${dinky_schema}.dinky_alert_group.alert_instance_ids IS 'Alert instance IDS'; COMMENT - ON COLUMN public.dinky_alert_group.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_alert_group.note IS 'note'; COMMENT - ON COLUMN public.dinky_alert_group.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_alert_group.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_alert_group.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_alert_group.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_alert_group.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_alert_group.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_alert_group.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_alert_group.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_alert_group.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_alert_group.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_alert_group IS 'Alert group'; + ON TABLE ${dinky_schema}.dinky_alert_group IS 'Alert group'; CREATE OR REPLACE TRIGGER set_update_time_dinky_alert_group BEFORE UPDATE - ON public.dinky_alert_group + ON ${dinky_schema}.dinky_alert_group FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_alert_history +-- Table structure for ${dinky_schema}.dinky_alert_history -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_history +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_history ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -101,40 +101,40 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_history ); COMMENT - ON COLUMN public.dinky_alert_history.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_alert_history.id IS 'id'; COMMENT - ON COLUMN public.dinky_alert_history.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_alert_history.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_alert_history.alert_group_id IS 'Alert group ID'; + ON COLUMN ${dinky_schema}.dinky_alert_history.alert_group_id IS 'Alert group ID'; COMMENT - ON COLUMN public.dinky_alert_history.job_instance_id IS 'job instance ID'; + ON COLUMN ${dinky_schema}.dinky_alert_history.job_instance_id IS 'job instance ID'; COMMENT - ON COLUMN public.dinky_alert_history.title IS 'alert title'; + ON COLUMN ${dinky_schema}.dinky_alert_history.title IS 'alert title'; COMMENT - ON COLUMN public.dinky_alert_history.content IS 'content description'; + ON COLUMN ${dinky_schema}.dinky_alert_history.content IS 'content description'; COMMENT - ON COLUMN public.dinky_alert_history.status IS 'alert status'; + ON COLUMN ${dinky_schema}.dinky_alert_history.status IS 'alert status'; COMMENT - ON COLUMN public.dinky_alert_history.log IS 'log'; + ON COLUMN ${dinky_schema}.dinky_alert_history.log IS 'log'; COMMENT - ON COLUMN public.dinky_alert_history.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_alert_history.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_alert_history.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_alert_history.update_time IS 'update time'; COMMENT - ON TABLE public.dinky_alert_history IS 'Alert history'; + ON TABLE ${dinky_schema}.dinky_alert_history IS 'Alert history'; CREATE OR REPLACE TRIGGER set_update_time_dinky_alert_history BEFORE UPDATE - ON public.dinky_alert_history + ON ${dinky_schema}.dinky_alert_history FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_alert_instance +-- Table structure for ${dinky_schema}.dinky_alert_instance -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_instance +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_instance ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(50) NOT NULL, @@ -150,42 +150,42 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_instance ); COMMENT - ON COLUMN public.dinky_alert_instance.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.id IS 'id'; COMMENT - ON COLUMN public.dinky_alert_instance.name IS 'alert instance name'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.name IS 'alert instance name'; COMMENT - ON COLUMN public.dinky_alert_instance.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_alert_instance.type IS 'alert instance type such as: DingTalk,Wechat(Webhook,app) Feishu ,email'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.type IS 'alert instance type such as: DingTalk,Wechat(Webhook,app) Feishu ,email'; COMMENT - ON COLUMN public.dinky_alert_instance.params IS 'configuration'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.params IS 'configuration'; COMMENT - ON COLUMN public.dinky_alert_instance.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_alert_instance.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_alert_instance.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_alert_instance.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_alert_instance.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_alert_instance IS 'Alert instance'; + ON TABLE ${dinky_schema}.dinky_alert_instance IS 'Alert instance'; CREATE OR REPLACE TRIGGER set_update_time_dinky_alert_instance BEFORE UPDATE - ON public.dinky_alert_instance + ON ${dinky_schema}.dinky_alert_instance FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_catalogue +-- Table structure for ${dinky_schema}.dinky_catalogue -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_catalogue +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_catalogue ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -203,45 +203,45 @@ CREATE TABLE IF NOT EXISTS public.dinky_catalogue ); COMMENT - ON COLUMN public.dinky_catalogue.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_catalogue.id IS 'ID'; COMMENT - ON COLUMN public.dinky_catalogue.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_catalogue.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_catalogue.task_id IS 'Job ID'; + ON COLUMN ${dinky_schema}.dinky_catalogue.task_id IS 'Job ID'; COMMENT - ON COLUMN public.dinky_catalogue.name IS 'Job Name'; + ON COLUMN ${dinky_schema}.dinky_catalogue.name IS 'Job Name'; COMMENT - ON COLUMN public.dinky_catalogue.type IS 'Job Type'; + ON COLUMN ${dinky_schema}.dinky_catalogue.type IS 'Job Type'; COMMENT - ON COLUMN public.dinky_catalogue.parent_id IS 'parent ID'; + ON COLUMN ${dinky_schema}.dinky_catalogue.parent_id IS 'parent ID'; COMMENT - ON COLUMN public.dinky_catalogue.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_catalogue.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_catalogue.is_leaf IS 'is leaf node'; + ON COLUMN ${dinky_schema}.dinky_catalogue.is_leaf IS 'is leaf node'; COMMENT - ON COLUMN public.dinky_catalogue.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_catalogue.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_catalogue.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_catalogue.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_catalogue.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_catalogue.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_catalogue.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_catalogue.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_catalogue IS 'catalogue'; + ON TABLE ${dinky_schema}.dinky_catalogue IS 'catalogue'; CREATE OR REPLACE TRIGGER set_update_time_dinky_catalogue BEFORE UPDATE - ON public.dinky_catalogue + ON ${dinky_schema}.dinky_catalogue FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_cluster +-- Table structure for ${dinky_schema}.dinky_cluster -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_cluster +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_cluster ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -263,59 +263,59 @@ CREATE TABLE IF NOT EXISTS public.dinky_cluster updater INT DEFAULT NULL ); -CREATE UNIQUE INDEX IF NOT EXISTS cluster_un_idx1 ON public.dinky_cluster (name, tenant_id); +CREATE UNIQUE INDEX IF NOT EXISTS cluster_un_idx1 ON ${dinky_schema}.dinky_cluster (name, tenant_id); COMMENT - ON COLUMN public.dinky_cluster.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_cluster.id IS 'ID'; COMMENT - ON COLUMN public.dinky_cluster.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_cluster.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_cluster.name IS 'cluster instance name'; + ON COLUMN ${dinky_schema}.dinky_cluster.name IS 'cluster instance name'; COMMENT - ON COLUMN public.dinky_cluster.alias IS 'cluster instance alias'; + ON COLUMN ${dinky_schema}.dinky_cluster.alias IS 'cluster instance alias'; COMMENT - ON COLUMN public.dinky_cluster.type IS 'cluster types'; + ON COLUMN ${dinky_schema}.dinky_cluster.type IS 'cluster types'; COMMENT - ON COLUMN public.dinky_cluster.hosts IS 'cluster hosts'; + ON COLUMN ${dinky_schema}.dinky_cluster.hosts IS 'cluster hosts'; COMMENT - ON COLUMN public.dinky_cluster.job_manager_host IS 'Job Manager Host'; + ON COLUMN ${dinky_schema}.dinky_cluster.job_manager_host IS 'Job Manager Host'; COMMENT - ON COLUMN public.dinky_cluster.version IS 'version'; + ON COLUMN ${dinky_schema}.dinky_cluster.version IS 'version'; COMMENT - ON COLUMN public.dinky_cluster.status IS 'cluster status'; + ON COLUMN ${dinky_schema}.dinky_cluster.status IS 'cluster status'; COMMENT - ON COLUMN public.dinky_cluster.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_cluster.note IS 'note'; COMMENT - ON COLUMN public.dinky_cluster.auto_registers IS 'is auto registration'; + ON COLUMN ${dinky_schema}.dinky_cluster.auto_registers IS 'is auto registration'; COMMENT - ON COLUMN public.dinky_cluster.cluster_configuration_id IS 'cluster configuration id'; + ON COLUMN ${dinky_schema}.dinky_cluster.cluster_configuration_id IS 'cluster configuration id'; COMMENT - ON COLUMN public.dinky_cluster.task_id IS 'task ID'; + ON COLUMN ${dinky_schema}.dinky_cluster.task_id IS 'task ID'; COMMENT - ON COLUMN public.dinky_cluster.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_cluster.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_cluster.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_cluster.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_cluster.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_cluster.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_cluster.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_cluster.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_cluster.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_cluster.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_cluster IS 'cluster instance management'; + ON TABLE ${dinky_schema}.dinky_cluster IS 'cluster instance management'; CREATE OR REPLACE TRIGGER set_update_time_dinky_cluster BEFORE UPDATE - ON public.dinky_cluster + ON ${dinky_schema}.dinky_cluster FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_cluster_configuration +-- Table structure for ${dinky_schema}.dinky_cluster_configuration -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_cluster_configuration +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_cluster_configuration ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -331,49 +331,49 @@ CREATE TABLE IF NOT EXISTS public.dinky_cluster_configuration updater INT DEFAULT NULL ); -CREATE UNIQUE INDEX IF NOT EXISTS cluster_configuration_un_idx1 ON public.dinky_cluster_configuration (name, tenant_id); +CREATE UNIQUE INDEX IF NOT EXISTS cluster_configuration_un_idx1 ON ${dinky_schema}.dinky_cluster_configuration (name, tenant_id); COMMENT - ON TABLE public.dinky_cluster_configuration IS 'cluster configuration management'; + ON TABLE ${dinky_schema}.dinky_cluster_configuration IS 'cluster configuration management'; COMMENT - ON COLUMN public.dinky_cluster_configuration.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.id IS 'ID'; COMMENT - ON COLUMN public.dinky_cluster_configuration.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_cluster_configuration.name IS 'cluster configuration name'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.name IS 'cluster configuration name'; COMMENT - ON COLUMN public.dinky_cluster_configuration.type IS 'cluster type'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.type IS 'cluster type'; COMMENT - ON COLUMN public.dinky_cluster_configuration.config_json IS 'json of configuration'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.config_json IS 'json of configuration'; COMMENT - ON COLUMN public.dinky_cluster_configuration.is_available IS 'is available'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.is_available IS 'is available'; COMMENT - ON COLUMN public.dinky_cluster_configuration.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.note IS 'note'; COMMENT - ON COLUMN public.dinky_cluster_configuration.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_cluster_configuration.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_cluster_configuration.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_cluster_configuration.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_cluster_configuration.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_cluster_configuration.updater IS 'updater user id'; CREATE OR REPLACE TRIGGER set_update_time_dinky_cluster_configuration BEFORE UPDATE - ON public.dinky_cluster_configuration + ON ${dinky_schema}.dinky_cluster_configuration FOR EACH ROW EXECUTE PROCEDURE trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_database +-- Table structure for ${dinky_schema}.dinky_database -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_database +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_database ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -395,62 +395,62 @@ CREATE TABLE IF NOT EXISTS public.dinky_database updater INT DEFAULT NULL ); -CREATE UNIQUE INDEX IF NOT EXISTS database_un_idx1 ON public.dinky_database (name, tenant_id); +CREATE UNIQUE INDEX IF NOT EXISTS database_un_idx1 ON ${dinky_schema}.dinky_database (name, tenant_id); COMMENT - ON TABLE public.dinky_database IS 'database management'; + ON TABLE ${dinky_schema}.dinky_database IS 'database management'; COMMENT - ON COLUMN public.dinky_database.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_database.id IS 'ID'; COMMENT - ON COLUMN public.dinky_database.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_database.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_database.name IS 'database name'; + ON COLUMN ${dinky_schema}.dinky_database.name IS 'database name'; COMMENT - ON COLUMN public.dinky_database.group_name IS 'database belong group name'; + ON COLUMN ${dinky_schema}.dinky_database.group_name IS 'database belong group name'; COMMENT - ON COLUMN public.dinky_database.type IS 'database type'; + ON COLUMN ${dinky_schema}.dinky_database.type IS 'database type'; COMMENT - ON COLUMN public.dinky_database.connect_config IS 'connect config'; + ON COLUMN ${dinky_schema}.dinky_database.connect_config IS 'connect config'; COMMENT - ON COLUMN public.dinky_database.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_database.note IS 'note'; COMMENT - ON COLUMN public.dinky_database.flink_config IS 'Flink configuration'; + ON COLUMN ${dinky_schema}.dinky_database.flink_config IS 'Flink configuration'; COMMENT - ON COLUMN public.dinky_database.flink_template IS 'Flink template'; + ON COLUMN ${dinky_schema}.dinky_database.flink_template IS 'Flink template'; COMMENT - ON COLUMN public.dinky_database.db_version IS 'version，such as: 11g of oracle ，2.2.3 of hbase'; + ON COLUMN ${dinky_schema}.dinky_database.db_version IS 'version，such as: 11g of oracle ，2.2.3 of hbase'; COMMENT - ON COLUMN public.dinky_database.status IS 'heartbeat status'; + ON COLUMN ${dinky_schema}.dinky_database.status IS 'heartbeat status'; COMMENT - ON COLUMN public.dinky_database.health_time IS 'last heartbeat time of trigger'; + ON COLUMN ${dinky_schema}.dinky_database.health_time IS 'last heartbeat time of trigger'; COMMENT - ON COLUMN public.dinky_database.heartbeat_time IS 'last heartbeat time'; + ON COLUMN ${dinky_schema}.dinky_database.heartbeat_time IS 'last heartbeat time'; COMMENT - ON COLUMN public.dinky_database.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_database.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_database.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_database.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_database.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_database.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_database.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_database.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_database.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_database.updater IS 'updater user id'; CREATE OR REPLACE TRIGGER set_update_time_dinky_database BEFORE UPDATE - ON public.dinky_database + ON ${dinky_schema}.dinky_database FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_flink_document +-- Table structure for ${dinky_schema}.dinky_flink_document -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_flink_document +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_flink_document ( id SERIAL PRIMARY KEY NOT NULL, category VARCHAR(255) DEFAULT NULL, @@ -469,90 +469,90 @@ CREATE TABLE IF NOT EXISTS public.dinky_flink_document ); COMMENT - ON TABLE public.dinky_flink_document IS 'flink document management'; + ON TABLE ${dinky_schema}.dinky_flink_document IS 'flink document management'; COMMENT - ON COLUMN public.dinky_flink_document.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_flink_document.id IS 'id'; COMMENT - ON COLUMN public.dinky_flink_document.category IS 'document category'; + ON COLUMN ${dinky_schema}.dinky_flink_document.category IS 'document category'; COMMENT - ON COLUMN public.dinky_flink_document.type IS 'document type'; + ON COLUMN ${dinky_schema}.dinky_flink_document.type IS 'document type'; COMMENT - ON COLUMN public.dinky_flink_document.subtype IS 'document subtype'; + ON COLUMN ${dinky_schema}.dinky_flink_document.subtype IS 'document subtype'; COMMENT - ON COLUMN public.dinky_flink_document.name IS 'document name'; + ON COLUMN ${dinky_schema}.dinky_flink_document.name IS 'document name'; COMMENT - ON COLUMN public.dinky_flink_document.description IS 'document description'; + ON COLUMN ${dinky_schema}.dinky_flink_document.description IS 'document description'; COMMENT - ON COLUMN public.dinky_flink_document.fill_value IS 'fill value'; + ON COLUMN ${dinky_schema}.dinky_flink_document.fill_value IS 'fill value'; COMMENT - ON COLUMN public.dinky_flink_document.version IS 'document version such as:(flink1.12, flink1.13, flink1.14, flink1.15, flink1.16, flink1.17, flink1.18)'; + ON COLUMN ${dinky_schema}.dinky_flink_document.version IS 'document version such as:(flink1.12, flink1.13, flink1.14, flink1.15, flink1.16, flink1.17, flink1.18)'; COMMENT - ON COLUMN public.dinky_flink_document.like_num IS 'like number'; + ON COLUMN ${dinky_schema}.dinky_flink_document.like_num IS 'like number'; COMMENT - ON COLUMN public.dinky_flink_document.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_flink_document.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_flink_document.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_flink_document.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_flink_document.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_flink_document.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_flink_document.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_flink_document.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_flink_document.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_flink_document.updater IS 'updater user id'; CREATE OR REPLACE TRIGGER set_update_time_dinky_flink_document BEFORE UPDATE - ON public.dinky_flink_document + ON ${dinky_schema}.dinky_flink_document FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- --- Data for Name: public.dinky_flink_document; Type: TABLE DATA; Schema: public; Owner: postgres +-- Data for Name: ${dinky_schema}.dinky_flink_document; Type: TABLE DATA; Schema: public; Owner: postgres -- -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (1, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.async-lookup.buffer-capacity', '异步查找连接可以触发的最大异步操作的操作数。 The max number of async i/o operation that the async lookup join can trigger.', 'Set ''table.exec.async-lookup.buffer-capacity''=''100'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (2, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.async-lookup.timeout', '异步操作完成的超时时间。 The async timeout for the asynchronous operation to complete.', 'Set ''table.exec.async-lookup.timeout''=''3 min'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (3, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.disabled-operators', '禁用指定operators，用逗号分隔 Mainly for testing. A comma-separated list of operator names, each name represents a kind of disabled operator. Operators that can be disabled include "NestedLoopJoin", "ShuffleHashJoin", "BroadcastHashJoin", "SortMergeJoin", "HashAgg", "SortAgg". By default no operator is disabled.', 'Set ''table.exec.disabled-operators''=''SortMergeJoin'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (4, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.allow-latency', '最大等待时间可用于MiniBatch缓冲输入记录。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。MiniBatch以允许的等待时间间隔以及达到最大缓冲记录数触发。注意：如果将table.exec.mini-batch.enabled设置为true，则其值必须大于零.', 'Set ''table.exec.mini-batch.allow-latency''=''-1 ms'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (5, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.enabled', '指定是否启用MiniBatch优化。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。默认情况下禁用此功能。 要启用此功能，用户应将此配置设置为true。注意：如果启用了mini batch 处理，则必须设置“ table.exec.mini-batch.allow-latency”和“ table.exec.mini-batch.size”.', 'Set ''table.exec.mini-batch.enabled''=''false'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (6, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.size', '可以为MiniBatch缓冲最大输入记录数。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。MiniBatch以允许的等待时间间隔以及达到最大缓冲记录数触发。 注意：MiniBatch当前仅适用于非窗口聚合。如果将table.exec.mini-batch.enabled设置为true，则其值必须为正.', 'Set ''table.exec.mini-batch.size''=''-1'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (7, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.resource.default-parallelism', '设置所有Operator的默认并行度。 Sets default parallelism for all operators (such as aggregate, join, filter) to run with parallel instances. This config has a higher priority than parallelism of StreamExecutionEnvironment (actually, this config overrides the parallelism of StreamExecutionEnvironment). A value of -1 indicates that no default parallelism is set, then it will fallback to use the parallelism of StreamExecutionEnvironment.', 'Set ''table.exec.resource.default-parallelism''=''1'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (8, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.sink.not-null-enforcer', '对表的NOT NULL列约束强制执行不能将空值插入到表中。Flink支持“error”（默认）和“drop”强制行为 The NOT NULL column constraint on a table enforces that null values can''t be inserted into the table. Flink supports ''error'' (default) and ''drop'' enforcement behavior. By default, Flink will check values and throw runtime exception when null values writing into NOT NULL columns. Users can change the behavior to ''drop'' to silently drop such records without throwing exception. @@ -560,7 +560,7 @@ Possible values: "ERROR" "DROP"', 'Set ''table.exec.sink.not-null-enforcer''=''ERROR'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (9, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.sink.upsert-materialize', '由于分布式系统中 Shuffle 导致 ChangeLog 数据混乱，Sink 接收到的数据可能不是全局 upsert 的顺序。因此，在 upsert sink 之前添加 upsert materialize 运算符。它接收上游的变更日志记录并为下游生成一个 upsert 视图。默认情况下，当唯一键出现分布式无序时，会添加具体化操作符。您也可以选择不实现（NONE）或强制实现（FORCE）。 Possible values: @@ -568,7 +568,7 @@ Possible values: "FORCE" "AUTO"', 'Set ''table.exec.sink.upsert-materialize''=''AUTO'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (10, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.kafka', 'kafka快速建表格式', 'CREATE TABLE Kafka_Table ( `event_time` TIMESTAMP(3) METADATA FROM ''timestamp'', @@ -588,7 +588,7 @@ VALUES (10, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.kafka', 'kafka --可选: ''value.fields-include'' = ''ALL'', --可选: ''json.ignore-parse-errors'' = ''true'', --可选: ''key.fields-prefix'' = ''k_'',', '1.14', 0, true, '2022-01-20 16:59:18', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (11, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.doris', 'Doris快速建表', 'CREATE TABLE doris_table ( cid INT, @@ -604,7 +604,7 @@ VALUES (11, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.doris', 'Doris ''username'' = ''root'', ''password''='''' );', '1.14', 0, true, '2022-01-20 17:08:00', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (12, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.jdbc', 'JDBC建表语句', 'CREATE TABLE JDBC_table ( id BIGINT, @@ -621,7 +621,7 @@ VALUES (12, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.jdbc', 'JDBC建 ); --可选: ''sink.parallelism''=''1'', --可选: ''lookup.cache.ttl''=''1000s'',', '1.14', 0, true, '2022-01-20 17:15:26', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (13, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.catalog.hive', '创建HIVE的catalog', 'CREATE CATALOG hive WITH ( ''type'' = ''hive'', @@ -629,34 +629,34 @@ VALUES (13, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.catalog.hive', '创建 ''hive-conf-dir'' = ''/app/wwwroot/MBDC/hive/conf/'', --hive配置文件 ''hadoop-conf-dir''=''/app/wwwroot/MBDC/hadoop/etc/hadoop/'' --hadoop配置文件，配了环境变量则不需要。 );', '1.14', 0, true, '2022-01-20 17:18:54', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (14, 'Operator', 'SQL_TEMPLATE', 'FlinkSql', 'use.catalog.hive', '使用hive的catalog', 'USE CATALOG hive;', '1.14', 0, true, '2022-01-20 17:22:53', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (15, 'Operator', 'SQL_TEMPLATE', 'FlinkSql', 'use.catalog.default', '使用default的catalog', 'USE CATALOG default_catalog;', '1.14', 0, true, '2022-01-20 17:23:48', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (16, 'Variable', 'FLINK_OPTIONS', '', 'set dialect.hive', '使用hive方言', 'Set table.sql-dialect=hive;', '1.14', 0, true, '2022-01-20 17:25:37', '2023-12-28 00:04:44', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (17, 'Variable', 'FLINK_OPTIONS', '', 'set dialect.default', '使用default方言', 'Set table.sql-dialect=default;', '1.14', 0, true, '2022-01-20 17:26:19', '2023-12-28 00:04:44', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (40, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value NOT IN (sub-query)', '如果value不存在于子查询中，则返回TRUE。', '${1:} NOT IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (41, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean1 OR boolean2', '如果BOOLEAN1为TRUE或BOOLEAN2为TRUE，则返回TRUE。支持三值逻辑。 例如，true || Null(Types.BOOLEAN)返回TRUE。', '${1:} OR ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (18, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.stream.table.hive', '创建流式HIVE表', 'CREATE CATALOG hive WITH ( --创建hive的catalog ''type'' = ''hive'', @@ -680,7 +680,7 @@ CREATE TABLE hive_stream_table ( ''sink.rolling-policy.check-interval''=''1min'', ''sink.partition-commit.policy.kind''=''metastore,success-file'' );', '1.14', 0, true, '2022-01-20 17:34:06', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (19, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.mysql_cdc', '创建Mysql_CDC表', 'CREATE TABLE mysql_cdc_table( cid INT, @@ -704,7 +704,7 @@ VALUES (19, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.mysql_cdc', '创 ''debezium.datetime.format.timestamp''=''yyyy-MM-dd HH-mm-ss'', ''debezium.datetime.format.timestamp.zone''=''UTC+8'', ''table-name'' = ''mysql_cdc_table'');', '1.14', 0, true, '2022-01-20 17:49:14', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (20, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.hudi', '创建hudi表', 'CREATE TABLE hudi_table ( @@ -744,80 +744,80 @@ WITH ( ''hive_sync.password'' = ''123456'', -- required, HMS 密码 ''hive_sync.skip_ro_suffix'' = ''true'' -- 去除ro后缀 );', '1.14', 0, true, '2022-01-20 17:56:50', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (21, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 <> value2', '如果value1不等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} <> ${2:}', '1.12', 4, true, '2021-02-22 10:05:38', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (22, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 > value2', '如果value1大于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} > ${2:}', '1.12', 2, true, '2021-02-22 14:37:58', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (23, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 >= value2', '如果value1大于或等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} >= ${2:}', '1.12', 2, true, '2021-02-22 14:38:52', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (24, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 < value2', '如果value1小于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} < ${2:}', '1.12', 0, true, '2021-02-22 14:39:15', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (25, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 <= value2', '如果value1小于或等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} <= ${2:}', '1.12', 0, true, '2021-02-22 14:39:40', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (26, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IS NULL', '如果value为NULL，则返回TRUE 。', '${1:} IS NULL', '1.12', 2, true, '2021-02-22 14:40:39', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (27, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IS NOT NULL', '如果value不为NULL，则返回TRUE 。', '${1:} IS NOT NULL', '1.12', 0, true, '2021-02-22 14:41:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (28, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IS DISTINCT FROM value2', '如果两个值不相等则返回TRUE。NULL值在这里被视为相同的值。', '${1:} IS DISTINCT FROM ${2:}', '1.12', 0, true, '2021-02-22 14:42:39', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (29, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IS NOT DISTINCT FROM value2', '如果两个值相等则返回TRUE。NULL值在这里被视为相同的值。', '${1:} IS NOT DISTINCT FROM ${2:}', '1.12', 0, true, '2021-02-22 14:43:23', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (30, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3', '如果value1大于或等于value2和小于或等于value3 返回true', '${1:} BETWEEN ${2:} AND ${3:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (31, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3', '如果value1小于value2或大于value3 返回true', '${1:} NOT BETWEEN ${2:} AND ${3:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (32, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 LIKE string2 [ ESCAPE char ]', '如果STRING1匹配模式STRING2，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} LIKE ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (33, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 NOT LIKE string2 [ ESCAPE char ]', '如果STRING1不匹配模式STRING2，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} NOT LIKE ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (34, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 SIMILAR TO string2 [ ESCAPE char ]', '如果STRING1与SQL正则表达式STRING2匹配，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} SIMILAR TO ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (35, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 NOT SIMILAR TO string2 [ ESCAPE char ]', '如果STRING1与SQL正则表达式STRING2不匹配，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} NOT SIMILAR TO ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (36, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IN (value2 [, value3]* )', '如果value1存在于给定列表（value2，value3，...）中，则返回TRUE 。 @@ -825,7 +825,7 @@ VALUES (36, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IN (value2 [, val 如果value1为NULL，则始终返回UNKNOWN 。', '${1:} IN (${2:} )', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (37, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT IN (value2 [, value3]* )', '如果value1不存在于给定列表（value2，value3，...）中，则返回TRUE 。 @@ -833,611 +833,611 @@ VALUES (37, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT IN (value2 [, 如果value1为NULL，则始终返回UNKNOWN 。', '${1:} NOT IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (38, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'EXISTS (sub-query)', '如果value存在于子查询中，则返回TRUE。', 'EXISTS (${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (42, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean1 AND boolean2', '如果BOOLEAN1和BOOLEAN2均为TRUE，则返回TRUE。支持三值逻辑。 例如，true && Null(Types.BOOLEAN)返回未知。', '${1:} AND ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (43, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'NOT boolean', '如果BOOLEAN为FALSE，则返回TRUE ；如果BOOLEAN为TRUE，则返回FALSE 。 如果BOOLEAN为UNKNOWN，则返回UNKNOWN。', 'NOT ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (44, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS FALSE', '如果BOOLEAN为FALSE，则返回TRUE ；如果BOOLEAN为TRUE或UNKNOWN，则返回FALSE 。', '${1:} IS FALSE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (45, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT FALSE', '如果BOOLEAN为TRUE或UNKNOWN，则返回TRUE ；如果BOOLEAN为FALSE，则返回FALSE。', '${1:} IS NOT FALSE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (46, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS TRUE', '如果BOOLEAN为TRUE，则返回TRUE；如果BOOLEAN为FALSE或UNKNOWN，则返回FALSE 。', '${1:} IS TRUE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (47, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT TRUE', '如果BOOLEAN为FALSE或UNKNOWN，则返回TRUE ；如果BOOLEAN为TRUE，则返回FALSE 。', '${1:} IS NOT TRUE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (48, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS UNKNOWN', '如果BOOLEAN为UNKNOWN，则返回TRUE ；如果BOOLEAN为TRUE或FALSE，则返回FALSE 。', '${1:} IS UNKNOWN', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (49, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT UNKNOWN', '如果BOOLEAN为TRUE或FALSE，则返回TRUE ；如果BOOLEAN为UNKNOWN，则返回FALSE 。', '${1:} IS NOT UNKNOWN', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (50, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', '+ numeric', '返回NUMERIC。', '+ ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (51, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', '- numeric', '返回负数NUMERIC。', '- ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (52, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 + numeric2', '返回NUMERIC1加NUMERIC2。', '${1:} + ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (53, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 - numeric2', '返回NUMERIC1减去NUMERIC2。', '${1:} - ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (54, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 * numeric2', '返回NUMERIC1乘以NUMERIC2。', '${1:} * ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (55, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 / numeric2', '返回NUMERIC1除以NUMERIC2。', '${1:} / ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (56, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 % numeric2', '返回NUMERIC1除以NUMERIC2的余数（模）。仅当numeric1为负数时，结果为负数。', '${1:} % ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (57, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'POWER(numeric1, numeric2)', '返回NUMERIC1的NUMERIC2 次幂。', 'POWER(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (58, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ABS(numeric)', '返回NUMERIC的绝对值。', 'ABS(${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (59, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'MOD(numeric1, numeric2)', '返回numeric1除以numeric2的余数(模)。只有当numeric1为负数时，结果才为负数', 'MOD(${1:} , ${2:} )', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (60, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SQRT(numeric)', '返回NUMERIC的平方根。', 'SQRT(${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (61, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LN(numeric)', '返回NUMERIC的自然对数（以e为底）。', 'LN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (62, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG10(numeric)', '返回NUMERIC的以10为底的对数。', 'LOG10(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (63, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG2(numeric)', '返回NUMERIC的以2为底的对数。', 'LOG2(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (64, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'EXP(numeric)', '返回e 的 NUMERIC 次幂。', 'EXP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (65, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'FLOOR(numeric)', '向下舍入NUMERIC，并返回小于或等于NUMERIC的最大整数。', 'FLOOR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (66, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SIN(numeric)', '返回NUMERIC的正弦值。', 'SIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (67, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SINH(numeric)', '返回NUMERIC的双曲正弦值。 返回类型为DOUBLE。', 'SINH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (68, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COS(numeric)', '返回NUMERIC的余弦值。', 'COS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (69, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TAN(numeric)', '返回NUMERIC的正切。', 'TAN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (70, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TANH(numeric)', '返回NUMERIC的双曲正切值。 返回类型为DOUBLE。', 'TANH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (71, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COT(numeric)', '返回NUMERIC的余切。', 'COT(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (72, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ASIN(numeric)', '返回NUMERIC的反正弦值。', 'ASIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (73, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ACOS(numeric)', '返回NUMERIC的反余弦值。', 'ACOS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (74, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ATAN(numeric)', '返回NUMERIC的反正切。', 'ATAN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (75, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ATAN2(numeric1, numeric2)', '返回坐标的反正切（NUMERIC1，NUMERIC2）。', 'ATAN2(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (76, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COSH(numeric)', '返回NUMERIC的双曲余弦值。 返回值类型为DOUBLE。', 'COSH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (77, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'DEGREES(numeric)', '返回弧度NUMERIC的度数表示形式', 'DEGREES(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (78, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RADIANS(numeric)', '返回度数NUMERIC的弧度表示。', 'RADIANS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (79, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SIGN(numeric)', '返回NUMERIC的符号。', 'SIGN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (80, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ROUND(numeric, integer)', '返回一个数字，四舍五入为NUMERIC的INT小数位。', 'ROUND(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (81, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'PI', '返回一个比任何其他值都更接近圆周率的值。', 'PI', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (82, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'E()', '返回一个比任何其他值都更接近e的值。', 'E()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (83, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND()', '返回介于0.0（含）和1.0（不含）之间的伪随机双精度值。', 'RAND()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (84, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND(integer)', '返回带有初始种子INTEGER的介于0.0（含）和1.0（不含）之间的伪随机双精度值。 如果两个RAND函数具有相同的初始种子，它们将返回相同的数字序列。', 'RAND(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (85, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND_INTEGER(integer)', '返回介于0（含）和INTEGER（不含）之间的伪随机整数值。', 'RAND_INTEGER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (86, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND_INTEGER(integer1, integer2)', '返回介于0（含）和INTEGER2（不含）之间的伪随机整数值，其初始种子为INTEGER1。 如果两个randInteger函数具有相同的初始种子和边界，它们将返回相同的数字序列。', 'RAND_INTEGER(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (87, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'UUID()', '根据RFC 4122 type 4（伪随机生成）UUID返回UUID（通用唯一标识符）字符串 （例如，“ 3d3c68f7-f608-473f-b60c-b0c44ad4cc4e”）。使用加密强度高的伪随机数生成器生成UUID。', 'UUID()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (88, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'BIN(integer)', '以二进制格式返回INTEGER的字符串表示形式。如果INTEGER为NULL，则返回NULL。 例如，4.bin()返回“ 100”并12.bin()返回“ 1100”。', 'BIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (89, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'HEX(numeric) HEX(string)', '以十六进制格式返回整数NUMERIC值或STRING的字符串表示形式。如果参数为NULL，则返回NULL。 例如，数字20导致“ 14”，数字100导致“ 64”，字符串“ hello，world”导致“ 68656C6C6F2C776F726C64”。', 'HEX(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (90, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TRUNCATE(numeric1, integer2)', '返回一个小数点后被截断为integer2位的数字。', 'TRUNCATE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (91, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'PI()', '返回π (pi)的值。仅在blink planner中支持。', 'PI()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (92, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG(numeric1)', '如果不带参数调用，则返回NUMERIC1的自然对数。当使用参数调用时，将NUMERIC1的对数返回到基数NUMERIC2。 注意：当前，NUMERIC1必须大于0，而NUMERIC2必须大于1。', 'LOG(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (93, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG(numeric1, numeric2)', '如果不带参数调用，则返回NUMERIC1的自然对数。当使用参数调用时，将NUMERIC1的对数返回到基数NUMERIC2。 注意：当前，NUMERIC1必须大于0，而NUMERIC2必须大于1。', 'LOG(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (94, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'CEIL(numeric)', '将NUMERIC向上舍入，并返回大于或等于NUMERIC的最小整数。', 'CEIL(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (95, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'CEILING(numeric)', '将NUMERIC向上舍入，并返回大于或等于NUMERIC的最小整数。', 'CEILING(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (96, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'string1 || string2', '返回string1和string2的连接。', '${1:} || ${2:}', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (97, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'UPPER(string)', '以大写形式返回STRING。', 'UPPER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (98, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LOWER(string)', '以小写形式返回STRING。', 'LOWER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (99, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'POSITION(string1 IN string2)', '返回STRING1在STRING2中第一次出现的位置（从1开始）； 如果在STRING2中找不到STRING1，则返回0 。', 'POSITION(${1:} IN ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (100, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'TRIM([ BOTH | LEADING | TRAILING ] string1 FROM string2)', '返回一个字符串，该字符串从STRING中删除前导和/或结尾字符。', 'TRIM(${1:} FROM ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (101, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LTRIM(string)', '返回一个字符串，该字符串从STRING除去左空格。 例如，" This is a test String.".ltrim()返回“This is a test String.”。', 'LTRIM(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (102, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RTRIM(string)', '返回一个字符串，该字符串从STRING中删除正确的空格。 例如，"This is a test String. ".rtrim()返回“This is a test String.”。', 'RTRIM(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (103, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REPEAT(string, integer)', '返回一个字符串，该字符串重复基本STRING INT次。 例如，"This is a test String.".repeat(2)返回“This is a test String.This is a test String.”。', 'REPEAT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (104, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP_REPLACE(string1, string2, string3)', '返回字符串STRING1所有匹配正则表达式的子串STRING2连续被替换STRING3。 例如，"foobar".regexpReplace("oo|ar", "")返回“ fb”。', 'REGEXP_REPLACE(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (105, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'OVERLAY(string1 PLACING string2 FROM integer1 [ FOR integer2 ])', '从位置INT1返回一个字符串，该字符串将STRING1的INT2（默认为STRING2的长度）字符替换为STRING2', 'OVERLAY(${1:} PLACING ${2:} FROM ${3:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (106, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SUBSTRING(string FROM integer1 [ FOR integer2 ])', '返回字符串STRING的子字符串，从位置INT1开始，长度为INT2（默认为结尾）。', 'SUBSTRING${1:} FROM ${2:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (107, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REPLACE(string1, string2, string3)', '返回一个新字符串替换其中出现的所有STRING2与STRING3（非重叠）从STRING1。', 'REPLACE(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (108, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP_EXTRACT(string1, string2[, integer])', '从STRING1返回一个字符串，该字符串使用指定的正则表达式STRING2和正则表达式匹配组索引INTEGER1提取。', 'REGEXP_EXTRACT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (109, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'INITCAP(string)', '返回一种新形式的STRING，其中每个单词的第一个字符转换为大写，其余字符转换为小写。', 'INITCAP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (110, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CONCAT(string1, string2,...)', '返回连接STRING1，STRING2，...的字符串。如果任何参数为NULL，则返回NULL。', 'CONCAT(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (111, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CONCAT_WS(string1, string2, string3,...)', '返回一个字符串，会连接STRING2，STRING3，......与分离STRING1。', 'CONCAT_WS(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (112, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LPAD(string1, integer, string2)', '返回一个新字符串，该字符串从STRING1的左侧填充STRING2，长度为INT个字符。', 'LPAD(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (113, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RPAD(string1, integer, string2)', '返回一个新字符串，该字符串从STRING1右侧填充STRING2，长度为INT个字符。', 'RPAD(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (114, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'FROM_BASE64(string)', '返回来自STRING的base64解码结果；如果STRING为NULL，则返回null 。', 'FROM_BASE64(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (115, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'TO_BASE64(string)', '从STRING返回base64编码的结果；如果STRING为NULL，则返回NULL。', 'TO_BASE64(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (116, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'ASCII(string)', '返回字符串的第一个字符的数值。如果字符串为NULL，则返回NULL。仅在blink planner中支持。', 'ASCII(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (117, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHR(integer)', '返回与integer在二进制上等价的ASCII字符。如果integer大于255，我们将首先得到integer的模数除以255，并返回模数的CHR。如果integer为NULL，则返回NULL。仅在blink planner中支持。', 'CHR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (118, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'DECODE(binary, string)', '使用提供的字符集(''US-ASCII''， ''ISO-8859-1''， ''UTF-8''， ''UTF-16BE''， ''UTF-16LE''， ''UTF-16''之一)将第一个参数解码为字符串。如果任意一个参数为空，结果也将为空。仅在blink planner中支持。', 'DECODE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (119, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'ENCODE(string1, string2)', '使用提供的string2字符集(''US-ASCII''， ''ISO-8859-1''， ''UTF-8''， ''UTF-16BE''， ''UTF-16LE''， ''UTF-16''之一)将string1编码为二进制。如果任意一个参数为空，结果也将为空。仅在blink planner中支持。', 'ENCODE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (120, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'INSTR(string1, string2)', '返回string2在string1中第一次出现的位置。如果任何参数为空，则返回NULL。仅在blink planner中支持。', 'INSTR(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (121, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LEFT(string, integer)', '返回字符串中最左边的整数字符。如果整数为负，则返回空字符串。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'LEFT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (122, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RIGHT(string, integer)', '返回字符串中最右边的整数字符。如果整数为负，则返回空字符串。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'RIGHT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (123, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LOCATE(string1, string2[, integer])', '返回string1在string2中的位置整数之后第一次出现的位置。如果没有找到，返回0。如果任何参数为NULL，则返回NULL仅在blink planner中支持。', 'LOCATE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (124, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'PARSE_URL(string1, string2[, string3])', '从URL返回指定的部分。string2的有效值包括''HOST''， ''PATH''， ''QUERY''， ''REF''， ''PROTOCOL''， ''AUTHORITY''， ''FILE''和''USERINFO''。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'PARSE_URL(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (125, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP(string1, string2)', '如果string1的任何子字符串(可能为空)与Java正则表达式string2匹配，则返回TRUE，否则返回FALSE。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'REGEXP(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (126, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REVERSE(string)', '返回反向字符串。如果字符串为NULL，则返回NULL仅在blink planner中支持。', 'REVERSE(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (127, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SPLIT_INDEX(string1, string2, integer1)', '通过分隔符string2拆分string1，返回拆分字符串的整数(从零开始)字符串。如果整数为负，返回NULL。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'SPLIT_INDEX(${1:}, ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (128, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'STR_TO_MAP(string1[, string2, string3]])', '使用分隔符将string1分割成键/值对后返回一个映射。string2是pair分隔符，默认为''，''。string3是键值分隔符，默认为''=''。仅在blink planner中支持。', 'STR_TO_MAP(${1:})', '1.12', 4, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (129, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SUBSTR(string[, integer1[, integer2]])', '返回一个字符串的子字符串，从位置integer1开始，长度为integer2(默认到末尾)。仅在blink planner中支持。', 'SUBSTR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (130, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHAR_LENGTH(string)', '返回STRING中的字符数。', 'CHAR_LENGTH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (131, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHARACTER_LENGTH(string)', '返回STRING中的字符数。', 'CHARACTER_LENGTH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (132, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DATE string', '返回以“ yyyy-MM-dd”形式从STRING解析的SQL日期。', 'DATE(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (133, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIME string', '返回以“ HH：mm：ss”的形式从STRING解析的SQL时间。', 'TIME(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (134, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMP string', '返回从STRING解析的SQL时间戳，格式为“ yyyy-MM-dd HH：mm：ss [.SSS]”', 'TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (135, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'INTERVAL string range', '解析“dd hh:mm:ss”形式的区间字符串。fff表示毫秒间隔，yyyy-mm表示月间隔。间隔范围可以是天、分钟、天到小时或天到秒，以毫秒为间隔;年或年到月的间隔。', 'INTERVAL ${1:} range', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (136, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_DATE', '返回UTC时区中的当前SQL日期。', 'CURRENT_DATE', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (137, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_TIME', '返回UTC时区的当前SQL时间。', 'CURRENT_TIME', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (138, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_TIMESTAMP', '返回UTC时区内的当前SQL时间戳。', 'CURRENT_TIMESTAMP', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (139, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'LOCALTIME', '返回本地时区的当前SQL时间。', 'LOCALTIME', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (140, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'LOCALTIMESTAMP', '返回本地时区的当前SQL时间戳。', 'LOCALTIMESTAMP', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (141, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'EXTRACT(timeintervalunit FROM temporal)', '返回从时域的timeintervalunit部分提取的长值。', 'EXTRACT(${1:} FROM ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (142, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'YEAR(date)', '返回SQL date日期的年份。等价于EXTRACT(YEAR FROM date)。', 'YEAR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (143, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'QUARTER(date)', '从SQL date date返回一年中的季度(1到4之间的整数)。相当于EXTRACT(从日期起四分之一)。', 'QUARTER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (144, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'MONTH(date)', '返回SQL date date中的某月(1到12之间的整数)。等价于EXTRACT(MONTH FROM date)。', 'MONTH(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (145, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'WEEK(date)', '从SQL date date返回一年中的某个星期(1到53之间的整数)。相当于EXTRACT(从日期开始的星期)。', 'WEEK(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (146, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFYEAR(date)', '返回SQL date date中的某一天(1到366之间的整数)。相当于EXTRACT(DOY FROM date)。', 'DAYOFYEAR(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (147, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFMONTH(date)', '从SQL date date返回一个月的哪一天(1到31之间的整数)。相当于EXTRACT(DAY FROM date)。', 'DAYOFMONTH(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (148, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFWEEK(date)', '返回星期几(1到7之间的整数;星期日= 1)从SQL日期日期。相当于提取(道指从日期)。', 'DAYOFWEEK(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (149, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'HOUR(timestamp)', '从SQL timestamp timestamp返回一天中的小时(0到23之间的整数)。相当于EXTRACT(HOUR FROM timestamp)。', 'HOUR(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (150, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'MINUTE(timestamp)', '从SQL timestamp timestamp返回一小时的分钟(0到59之间的整数)。相当于EXTRACT(分钟从时间戳)。', 'MINUTE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (151, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'SECOND(timestamp)', '从SQL时间戳返回一分钟中的秒(0到59之间的整数)。等价于EXTRACT(从时间戳开始倒数第二)。', 'SECOND(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (152, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'FLOOR(timepoint TO timeintervalunit)', '返回一个将timepoint舍入到时间单位timeintervalunit的值。', 'FLOOR(${1:} TO ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (153, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CEIL(timepoint TO timeintervalunit)', '返回一个将timepoint舍入到时间单位timeintervalunit的值。', 'CEIL(${1:} TO ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (154, 'Function', 'FUN_UDF', 'TIME_FUNCTION', '(timepoint1, temporal1) OVERLAPS (timepoint2, temporal2)', '如果(timepoint1, temporal1)和(timepoint2, temporal2)定义的两个时间间隔重叠，则返回TRUE。时间值可以是时间点或时间间隔。', '(${1:} , ${1:}) OVERLAPS (${2:} , ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (155, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DATE_FORMAT(timestamp, string)', '注意这个功能有严重的错误，现在不应该使用。请实现一个自定义的UDF，或者使用EXTRACT作为解决方案。', 'DATE_FORMAT(${1:}, ''yyyy-MM-dd'')', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (156, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMPADD(timeintervalunit, interval, timepoint)', '返回一个新的时间值，该值将一个(带符号的)整数间隔添加到时间点。间隔的单位由unit参数给出，它应该是以下值之一:秒、分、小时、日、周、月、季度或年。', 'TIMESTAMPADD(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (39, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IN (sub-query)', '如果value存在于子查询中，则返回TRUE。', '${1:} IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (157, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMPDIFF(timepointunit, timepoint1, timepoint2)', '返回timepointunit在timepoint1和timepoint2之间的(带符号)数。间隔的单位由第一个参数给出，它应该是以下值之一:秒、分、小时、日、月或年。', 'TIMESTAMPDIFF(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (158, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CONVERT_TZ(string1, string2, string3)', '将时区string2中的datetime string1(默认ISO时间戳格式''yyyy-MM-dd HH:mm:ss'')转换为时区string3。时区的格式可以是缩写，如“PST”;可以是全名，如“America/Los_Angeles”;或者是自定义ID，如“GMT-8:00”。仅在blink planner中支持。', 'CONVERT_TZ(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (159, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'FROM_UNIXTIME(numeric[, string])', '以字符串格式返回数值参数的表示形式(默认为''yyyy-MM-dd HH:mm:ss'')。numeric是一个内部时间戳值，表示从UTC ''1970-01-01 00:00:00''开始的秒数，例如UNIX_TIMESTAMP()函数生成的时间戳。返回值用会话时区表示(在TableConfig中指定)。仅在blink planner中支持。', 'FROM_UNIXTIME(${1:} )', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (160, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'UNIX_TIMESTAMP()', '获取当前Unix时间戳(以秒为单位)。仅在blink planner中支持。', 'UNIX_TIMESTAMP()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (161, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'UNIX_TIMESTAMP(string1[, string2])', '转换日期时间字符串string1，格式为string2(缺省为yyyy-MM-dd HH:mm:ss，如果没有指定)为Unix时间戳(以秒为单位)，使用表配置中指定的时区。仅在blink planner中支持。', 'UNIX_TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (162, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TO_DATE(string1[, string2])', '将格式为string2的日期字符串string1(默认为''yyyy-MM-dd'')转换为日期。仅在blink planner中支持。', 'TO_DATE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (163, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TO_TIMESTAMP(string1[, string2])', '将会话时区(由TableConfig指定)下的日期时间字符串string1转换为时间戳，格式为string2(默认为''yyyy-MM-dd HH:mm:ss'')。仅在blink planner中支持。', 'TO_TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (164, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'NOW()', '返回UTC时区内的当前SQL时间戳。仅在blink planner中支持。', 'NOW()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (165, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'CASE value WHEN value1_1 [, value1_2 ]* THEN result1 @@ -1447,7 +1447,7 @@ END', '当第一个时间值包含在(valueX_1, valueX_2，…)中时，返回re WHEN ${2:} THEN ${3:} ELSE ${4:} END AS ${5:}', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (166, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'CASE WHEN condition1 THEN result1 @@ -1456,255 +1456,255 @@ WHEN condition1 THEN result1 END', '当第一个条件满足时返回resultX。当不满足任何条件时，如果提供了resultZ则返回resultZ，否则返回NULL。', 'CASE WHEN ${1:} THEN ${2:} ELSE ${3:} END AS ${4:}', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (167, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'NULLIF(value1, value2)', '如果value1等于value2，则返回NULL;否则返回value1。', 'NULLIF(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (168, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'COALESCE(value1, value2 [, value3 ]* )', '返回value1, value2， ....中的第一个非空值', 'COALESCE(${1:} )', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (169, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IF(condition, true_value, false_value)', '如果条件满足则返回true值，否则返回false值。仅在blink planner中支持。', 'IF((${1:}, ${2:}, ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (170, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_ALPHA(string)', '如果字符串中所有字符都是字母则返回true，否则返回false。仅在blink planner中支持。', 'IS_ALPHA(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (171, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_DECIMAL(string)', '如果字符串可以被解析为有效的数字则返回true，否则返回false。仅在blink planner中支持。', 'IS_DECIMAL(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (172, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_DIGIT(string)', '如果字符串中所有字符都是数字则返回true，否则返回false。仅在blink planner中支持。', 'IS_DIGIT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (173, 'Function', 'FUN_UDF', 'TYPE_CONVER_FUNCTION', 'CAST(value AS type)', '返回一个要转换为type类型的新值。', 'CAST(${1:} AS ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (174, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'CARDINALITY(array)', '返回数组中元素的数量。', 'CARDINALITY(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (175, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'array ‘[’ integer ‘]’', '返回数组中位于整数位置的元素。索引从1开始。', 'array[${1:}]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (176, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'ELEMENT(array)', '返回数组的唯一元素(其基数应为1);如果数组为空，则返回NULL。如果数组有多个元素，则抛出异常。', 'ELEMENT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (177, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'CARDINALITY(map)', '返回map中的条目数。', 'CARDINALITY(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (178, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'map ‘[’ value ‘]’', '返回map中key value指定的值。', 'map[${1:}]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (179, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'ARRAY ‘[’ value1 [, value2 ]* ‘]’', '返回一个由一系列值(value1, value2，…)创建的数组。', 'ARRAY[ ${1:} ]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (180, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'MAP ‘[’ value1, value2 [, value3, value4 ]* ‘]’', '返回一个从键值对列表((value1, value2)， (value3, value4)，…)创建的映射。', 'MAP[ ${1:} ]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (181, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'implicit constructor with parenthesis (value1 [, value2]*)', '返回从值列表(value1, value2，…)创建的行。', '(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (182, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'explicit ROW constructor ROW(value1 [, value2]*)', '返回从值列表(value1, value2，…)创建的行。', 'ROW(${1:}) ', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (183, 'Function', 'FUN_UDF', 'VALUE_ACCESS_FUNCTION', 'tableName.compositeType.field', '按名称从Flink复合类型(例如，Tuple, POJO)中返回一个字段的值。', 'tableName.compositeType.field', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (184, 'Function', 'FUN_UDF', 'VALUE_ACCESS_FUNCTION', 'tableName.compositeType.*', '返回Flink复合类型(例如，Tuple, POJO)的平面表示，它将每个直接子类型转换为一个单独的字段。在大多数情况下，平面表示的字段的名称与原始字段类似，但使用了$分隔符(例如，mypojo$mytuple$f0)。', 'tableName.compositeType.*', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (185, 'Function', 'FUN_UDF', 'GROUP_FUNCTION', 'GROUP_ID()', '返回唯一标识分组键组合的整数', 'GROUP_ID()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (186, 'Function', 'FUN_UDF', 'GROUP_FUNCTION', 'GROUPING(expression1 [, expression2]* ) GROUPING_ID(expression1 [, expression2]* )', '返回给定分组表达式的位向量。', 'GROUPING(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (187, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'MD5(string)', '以32位十六进制数字的字符串形式返回string的MD5哈希值;如果字符串为NULL，则返回NULL。', 'MD5(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (188, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA1(string)', '返回字符串的SHA-1散列，作为一个由40个十六进制数字组成的字符串;如果字符串为NULL，则返回NULL', 'SHA1(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (189, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA224(string)', '以56位十六进制数字的字符串形式返回字符串的SHA-224散列;如果字符串为NULL，则返回NULL。', 'SHA224(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (190, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA256(string)', '以64位十六进制数字的字符串形式返回字符串的SHA-256散列;如果字符串为NULL，则返回NULL。', 'SHA256(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (191, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA384(string)', '以96个十六进制数字的字符串形式返回string的SHA-384散列;如果字符串为NULL，则返回NULL。', 'SHA384(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (192, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA512(string)', '以128位十六进制数字的字符串形式返回字符串的SHA-512散列;如果字符串为NULL，则返回NULL。', 'SHA512(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (193, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA2(string, hashLength)', '使用SHA-2哈希函数族(SHA-224、SHA-256、SHA-384或SHA-512)返回哈希值。第一个参数string是要散列的字符串，第二个参数hashLength是结果的位长度(224、256、384或512)。如果string或hashLength为NULL，则返回NULL。', 'SHA2(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (194, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COUNT([ ALL ] expression | DISTINCT expression1 [, expression2]*)', '默认情况下或使用ALL时，返回表达式不为空的输入行数。对每个值的唯一实例使用DISTINCT。', 'COUNT( DISTINCT ${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (195, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COUNT(*) COUNT(1)', '返回输入行数。', 'COUNT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (196, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'AVG([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的平均值(算术平均值)。对每个值的唯一实例使用DISTINCT。', 'AVG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (197, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'SUM([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回所有输入行表达式的和。对每个值的唯一实例使用DISTINCT。', 'SUM(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (198, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'MAX([ ALL | DISTINCT ] expression)', '默认情况下或使用关键字ALL，返回表达式在所有输入行中的最大值。对每个值的唯一实例使用DISTINCT。', 'MAX(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (199, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'MIN([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的最小值。对每个值的唯一实例使用DISTINCT。', 'MIN(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (200, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'STDDEV_POP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的总体标准差。对每个值的唯一实例使用DISTINCT。', 'STDDEV_POP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (201, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'STDDEV_SAMP([ ALL | DISTINCT ] expression)', '默认情况下或使用关键字ALL时，返回表达式在所有输入行中的样本标准差。对每个值的唯一实例使用DISTINCT。', 'STDDEV_SAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (202, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VAR_POP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的总体方差(总体标准差的平方)。对每个值的唯一实例使用DISTINCT。', 'VAR_POP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (203, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VAR_SAMP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的样本方差(样本标准差的平方)。对每个值的唯一实例使用DISTINCT。', 'VAR_SAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (204, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COLLECT([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，跨所有输入行返回表达式的多集。空值将被忽略。对每个值的唯一实例使用DISTINCT。', 'COLLECT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (205, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VARIANCE([ ALL | DISTINCT ] expression)', 'VAR_SAMP的同义词。仅在blink planner中支持。', 'VARIANCE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (206, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'RANK()', '返回值在一组值中的秩。结果是1加上分区顺序中位于当前行之前或等于当前行的行数。这些值将在序列中产生空白。仅在blink planner中支持。', 'RANK()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (207, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'DENSE_RANK()', '返回值在一组值中的秩。结果是1加上前面分配的秩值。与函数rank不同，dense_rank不会在排序序列中产生空隙。仅在blink planner中支持。', 'DENSE_RANK()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (208, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'ROW_NUMBER()', '根据窗口分区中的行顺序，为每一行分配一个惟一的连续数字，从1开始。仅在blink planner中支持。', 'ROW_NUMBER()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (209, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LEAD(expression [, offset] [, default] )', '返回表达式在窗口中当前行之前的偏移行上的值。offset的默认值是1,default的默认值是NULL。仅在blink planner中支持。', 'LEAD(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (210, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LAG(expression [, offset] [, default])', '返回表达式的值，该值位于窗口中当前行之后的偏移行。offset的默认值是1,default的默认值是NULL。仅在blink planner中支持。', 'LAG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (211, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'FIRST_VALUE(expression)', '返回一组有序值中的第一个值。仅在blink planner中支持。', 'FIRST_VALUE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (212, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LAST_VALUE(expression)', '返回一组有序值中的最后一个值。仅在blink planner中支持。', 'LAST_VALUE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (213, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LISTAGG(expression [, separator])', '连接字符串表达式的值，并在它们之间放置分隔符值。分隔符没有添加在字符串的末尾。分隔符的默认值是''，''。仅在blink planner中支持。', 'LISTAGG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (214, 'Function', 'FUN_UDF', 'COLUMN_FUNCTION', 'withColumns(…)', '选择的列', 'withColumns(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (215, 'Function', 'FUN_UDF', 'COLUMN_FUNCTION', 'withoutColumns(…)', '不选择的列', 'withoutColumns(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (216, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 = value2', '如果value1等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} =${2:}', '1.12', 9, true, '2021-02-22 10:06:49', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (217, 'Function', 'FUN_UDF', 'TABLE_AGGREGATE_FUNCTION', 'TO_MAP(string1,object2[, string3])', '将非规则一维表转化为规则二维表，string1是key。string2是value。string3为非必填项，表示key的值域（维度），用英文逗号分割。', 'TO_MAP(${1:})', '1.12', 8, true, '2021-05-20 19:59:22', '2023-12-28 00:10:10', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (218, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE print', 'Whole library synchronization print', 'EXECUTE CDCSOURCE demo_print WITH ( ''connector'' = ''mysql-cdc'', @@ -1718,7 +1718,7 @@ VALUES (218, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE print', ''table-name'' = ''test\.student,test\.score'', ''sink.connector'' = ''print'' );', 'All Versions', 0, true, '2023-10-31 16:01:45', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (219, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE doris', 'Whole library synchronization doris', 'EXECUTE CDCSOURCE demo_print WITH ( ''connector'' = ''mysql-cdc'', @@ -1732,7 +1732,7 @@ VALUES (219, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE doris', ''table-name'' = ''test\.student,test\.score'', ''sink.connector'' = ''print'' );', 'All Versions', 0, true, '2023-10-31 16:02:21', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (220, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_doris_schema_evolution', 'The entire library is synchronized to doris tape mode evolution', 'EXECUTE CDCSOURCE demo_doris_schema_evolution WITH ( @@ -1755,7 +1755,7 @@ VALUES (220, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_do ''sink.sink.db'' = ''test'', ''sink.table.identifier'' = ''${schemaName}.${tableName}'' );', 'All Versions', 0, true, '2023-10-31 16:04:53', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (230, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2hive', 'The entire library is synchronized to the sql-catalog of hive', 'EXECUTE CDCSOURCE mysql2hive WITH ( @@ -1774,7 +1774,7 @@ VALUES (230, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2h ''sink.default-database'' = ''hdb'', ''sink.hive-conf-dir'' = ''/usr/local/dlink/hive-conf'' );', 'All Versions', 0, true, '2023-10-31 16:14:31', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (231, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2paimon', 'The entire library is synchronized to paimon', 'EXECUTE CDCSOURCE mysql2paimon WITH ( @@ -1792,7 +1792,7 @@ VALUES (231, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2 ''sink.catalog.type'' = ''table-store'', ''sink.catalog.warehouse''=''file:/tmp/table_store'' );', 'All Versions', 0, true, '2023-10-31 16:15:22', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (221, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE StarRocks ', 'The entire library is synchronized to StarRocks ', 'EXECUTE CDCSOURCE demo_hudi WITH ( @@ -1836,7 +1836,7 @@ VALUES (221, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE StarRoc ''sink.hive_sync.table''=''${tableName}'', ''sink.table.prefix.schema''=''true'' );', 'All Versions', 0, true, '2023-10-31 16:05:50', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (222, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_mysql', 'The entire library is synchronized to mysql', 'EXECUTE CDCSOURCE demo_startrocks WITH ( @@ -1865,7 +1865,7 @@ VALUES (222, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_mys ''sink.sink.buffer-flush.interval-ms'' = ''15000'', ''sink.sink.parallelism'' = ''1'' );', 'All Versions', 0, true, '2023-10-31 16:07:08', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (223, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_doris', 'The entire library is synchronized to mysql', 'EXECUTE CDCSOURCE cdc_mysql WITH ( @@ -1892,7 +1892,7 @@ VALUES (223, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_do ''sink.sink.max-retries'' = ''5'', ''sink.auto.create'' = ''true'' );', 'All Versions', 0, true, '2023-10-31 16:07:47', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (224, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_oracle', 'The entire library is synchronized to cdc_oracle', 'EXECUTE CDCSOURCE cdc_oracle WITH ( @@ -1912,7 +1912,7 @@ VALUES (224, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_ora ''password'' = ''123456'', ''table-name'' = ''TEST2.${tableName}'' );', 'All Versions', 0, true, '2023-10-31 16:08:30', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (225, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kafka_one', 'The entire library is synchronized to a topic in kafka', 'EXECUTE CDCSOURCE cdc_kafka_one WITH ( @@ -1929,7 +1929,7 @@ VALUES (225, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kaf ''sink.topic''=''cdctest'', ''sink.brokers''=''bigdata2:9092,bigdata3:9092,bigdata4:9092'' );', 'All Versions', 0, true, '2023-10-31 16:10:13', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (226, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kafka_mul', 'The entire library is synchronized to a single topic in kafka', 'EXECUTE CDCSOURCE cdc_kafka_mul WITH ( @@ -1945,7 +1945,7 @@ VALUES (226, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kaf ''sink.connector''=''datastream-kafka'', ''sink.brokers''=''bigdata2:9092,bigdata3:9092,bigdata4:9092'' )', 'All Versions', 0, true, '2023-10-31 16:10:59', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (227, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_upsert_kafka', 'The entire library is synchronized to kafka primary key mode', 'EXECUTE CDCSOURCE cdc_upsert_kafka WITH ( @@ -1964,7 +1964,7 @@ VALUES (227, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_ups ''sink.key.format'' = ''json'', ''sink.value.format'' = ''json'' );', 'All Versions', 0, true, '2023-10-31 16:12:14', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (228, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_postgresql ', 'The entire library is synchronized to postgresql', 'EXECUTE CDCSOURCE cdc_postgresql WITH ( @@ -1990,7 +1990,7 @@ VALUES (228, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_pos ''sink.sink.buffer-flush.max-rows'' = ''100'', ''sink.sink.max-retries'' = ''5'' )', 'All Versions', 0, true, '2023-10-31 16:12:54', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (229, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_clickhouse', 'Sync the entire library to clickhouse', 'EXECUTE CDCSOURCE cdc_clickhouse WITH ( @@ -2016,10 +2016,10 @@ VALUES (229, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_cli ''sink.sink.flush-interval'' = ''1000'', ''sink.sink.max-retries'' = ''3'' );', 'All Versions', 0, true, '2023-10-31 16:13:33', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) -VALUES (232, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2public.dinky_catalog', - 'The entire library is synchronized to dinky''s built-in catalog', 'EXECUTE CDCSOURCE mysql2public.dinky_catalog WITH ( +VALUES (232, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2${dinky_schema}.dinky_catalog', + 'The entire library is synchronized to dinky''s built-in catalog', 'EXECUTE CDCSOURCE mysql2${dinky_schema}.dinky_catalog WITH ( ''connector'' = ''mysql-cdc'', ''hostname'' = ''127.0.0.1'', ''port'' = ''3306'', @@ -2037,7 +2037,7 @@ VALUES (232, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2p ''sink.catalog.url'' = ''jdbc:mysql://127.0.0.1:3306/dlink?useUnicode=true&characterEncoding=utf8&serverTimezone=UTC'', ''sink.sink.db'' = ''default_database'' );', 'All Versions', 0, true, '2023-10-31 16:16:22', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (233, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2multiple_sink', 'Synchronization of the entire library to multiple data sources (sink)', 'EXECUTE CDCSOURCE mysql2multiple_sink WITH ( @@ -2067,19 +2067,19 @@ VALUES (233, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2m ''sink[1].topic''=''cdc'', ''sink[1].brokers''=''127.0.0.1:9092'' )', 'All Versions', 0, true, '2023-10-31 16:17:27', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (234, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'ADD JAR', 'ADD JAR', 'ADD JAR ${1:}; -- str path ', 'All Versions', 0, true, '2023-10-31 16:19:52', '2023-12-28 00:02:02', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (235, 'Function', 'Other', 'Other', 'SHOW FRAGMENTS', 'SHOW FRAGMENTS', 'SHOW FRAGMENTS;', 'All Versions', 0, true, '2023-10-31 16:20:30', '2023-12-28 09:57:55', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (236, 'Function', 'Other', 'Other', 'SHOW FRAGMENT var1', 'SHOW FRAGMENT var1', 'SHOW FRAGMENT ${1:};', 'All Versions', 0, true, '2023-10-31 16:21:23', '2023-12-28 09:57:54', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (237, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_hudi', 'The entire library is synchronized to hudi', 'EXECUTE CDCSOURCE demo_hudi WITH ( @@ -2123,7 +2123,7 @@ VALUES (237, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_hu ''sink.hive_sync.table''=''${tableName}'', ''sink.table.prefix.schema''=''true'' );', 'All Versions', 0, true, '2023-10-31 16:24:47', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (238, 'Reference', 'SQL_TEMPLATE', 'FlinkJar', 'EXECUTE JAR ', 'EXECUTE JAR use sql', 'EXECUTE JAR WITH ( ''uri''=''rs:///jar/flink/demo/SocketWindowWordCount.jar'', @@ -2132,11 +2132,11 @@ VALUES (238, 'Reference', 'SQL_TEMPLATE', 'FlinkJar', 'EXECUTE JAR ', 'EXECUTE J ''parallelism''='''', ''savepoint-path''='''' );', 'All Versions', 0, true, '2023-10-31 16:27:53', '2023-12-28 09:57:54', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (239, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'PRINT tablename', 'PRINT table data', 'PRINT ${1:}', 'All Versions', 0, true, '2023-10-31 16:30:22', '2023-12-28 00:09:39', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (240, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE Like', 'CREATE TABLE Like source table', 'DROP TABLE IF EXISTS sink_table; CREATE TABLE IF not EXISTS sink_table @@ -2144,7 +2144,7 @@ WITH ( ''topic'' = ''motor_vehicle_error'' ) LIKE source_table;', 'All Versions', 0, true, '2023-10-31 16:33:38', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (241, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE like source_table EXCLUDING', 'CREATE TABLE like source_table EXCLUDING', 'DROP TABLE IF EXISTS sink_table; @@ -2161,7 +2161,7 @@ LIKE source_table ( EXCLUDING ALL INCLUDING GENERATED );', 'All Versions', 0, true, '2023-10-31 16:36:13', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (242, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE ctas_kafka', 'CREATE TABLE ctas_kafka', 'CREATE TABLE my_ctas_table WITH ( @@ -2169,7 +2169,7 @@ WITH ( ) AS SELECT id, name, age FROM source_table WHERE mod(id, 10) = 0;', 'All Versions', 0, true, '2023-10-31 16:37:33', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (243, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE rtas_kafka', 'CREATE TABLE rtas_kafka', 'CREATE OR REPLACE TABLE my_ctas_table WITH ( @@ -2177,7 +2177,7 @@ WITH ( ) AS SELECT id, name, age FROM source_table WHERE mod(id, 10) = 0;', 'All Versions', 0, true, '2023-10-31 16:41:46', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (244, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'datagen job demo', 'datagen job demo', 'DROP TABLE IF EXISTS source_table3; CREATE TABLE IF NOT EXISTS source_table3( @@ -2232,7 +2232,7 @@ ORDER BY order_time RANGE BETWEEN INTERVAL ''1'' MINUTE PRECEDING AND CURRENT ROW ) as one_minute_sum FROM source_table3;', 'All Versions', 0, true, '2023-11-15 15:42:16', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (245, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'checkpoint config', 'checkpoint config', '-- 声明一些调优参数 (checkpoint 等相关配置) set ''execution.checkpointing.checkpoints-after-tasks-finish.enabled'' =''true''; @@ -2246,7 +2246,7 @@ set ''state.checkpoints.num-retained''=''100''; -- 使 solt 均匀分布在 各个 TM 上 set ''cluster.evenly-spread-out-slots''=''true'';', 'All Versions', 0, true, '2023-11-15 15:57:42', '2023-12-28 15:49:20', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (246, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'note template', 'note template', '-- ----------------------------------------------------------------- -- @Description(作业描述): ${1:} @@ -2255,7 +2255,7 @@ VALUES (246, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'note template', 'note tem -- ----------------------------------------------------------------- ${4:}', 'All Versions', 0, true, '2023-11-17 17:03:24', '2023-12-28 12:05:20', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (247, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'dinky_paimon_auto_create_table', 'dinky paimon auto create table', '-- ----------------------------------------------------------------- @@ -2263,7 +2263,7 @@ VALUES (247, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'dinky_paimon_auto_create_ -- ----------------------------------------------------------------- -EXECUTE CDCSOURCE public.dinky_paimon_auto_create_table +EXECUTE CDCSOURCE ${dinky_schema}.dinky_paimon_auto_create_table WITH ( ''connector'' = ''mysql-cdc'', @@ -2279,12 +2279,12 @@ WITH ''sink.path'' = ''hdfs:/tmp/paimon/#{schemaName}.db/#{tableName}'', ''sink.auto-create'' = ''true'', );', 'All Versions', 0, true, '2023-12-27 16:53:37', '2023-12-28 12:05:20', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (248, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'add-customjar', 'add CUSTOMJAR 为 Dinky 扩展语法 功能实现和 add jar 类似 , 推荐使用此方式', '-- add CUSTOMJAR 为 Dinky 扩展语法 功能实现和 add jar 类似 , 推荐使用此方式 add CUSTOMJAR ''${1:}'';', 'All Versions', 0, true, '2023-12-28 10:50:17', '2023-12-28 15:49:40', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO ${dinky_schema}.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (249, 'Property', 'FLINK_OPTIONS', 'FlinkSql', 'restart-strategy', '重启策略', 'fixed-delay', '1.15', 0, true, '2024-03-01 15:10:31', '2024-03-01 15:10:31', 1, 1); @@ -2292,10 +2292,10 @@ VALUES (249, 'Property', 'FLINK_OPTIONS', 'FlinkSql', 'restart-strategy', '重 -- ---------------------------- --- Table structure for public.dinky_fragment +-- Table structure for ${dinky_schema}.dinky_fragment -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_fragment +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_fragment ( id serial PRIMARY KEY NOT NULL, name varchar(50) NOT NULL, @@ -2310,30 +2310,30 @@ CREATE TABLE IF NOT EXISTS public.dinky_fragment UNIQUE (name, tenant_id) ); -COMMENT ON TABLE public.dinky_fragment is 'fragment management'; -COMMENT ON COLUMN public.dinky_fragment.id is 'id'; -COMMENT ON COLUMN public.dinky_fragment.name is 'fragment name'; -COMMENT ON COLUMN public.dinky_fragment.tenant_id is 'tenant id'; -COMMENT ON COLUMN public.dinky_fragment.fragment_value is 'fragment value'; -COMMENT ON COLUMN public.dinky_fragment.note is 'note'; -COMMENT ON COLUMN public.dinky_fragment.enabled is 'enabled'; -COMMENT ON COLUMN public.dinky_fragment.create_time is 'create time'; -COMMENT ON COLUMN public.dinky_fragment.update_time is 'update time'; -COMMENT ON COLUMN public.dinky_fragment.creator is 'creator'; -COMMENT ON COLUMN public.dinky_fragment.updater is 'updater'; +COMMENT ON TABLE ${dinky_schema}.dinky_fragment is 'fragment management'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.id is 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.name is 'fragment name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.tenant_id is 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.fragment_value is 'fragment value'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.note is 'note'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.enabled is 'enabled'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.create_time is 'create time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.update_time is 'update time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.creator is 'creator'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment.updater is 'updater'; CREATE OR REPLACE TRIGGER update_dinky_fragment_modtime BEFORE UPDATE - ON public.dinky_fragment + ON ${dinky_schema}.dinky_fragment FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_history +-- Table structure for ${dinky_schema}.dinky_history -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_history +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_history ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -2355,57 +2355,57 @@ CREATE TABLE IF NOT EXISTS public.dinky_history task_id INT NULL ); -- Add indexes -CREATE INDEX IF NOT EXISTS task_index ON public.dinky_history (task_id); -CREATE INDEX IF NOT EXISTS cluster_index ON public.dinky_history (cluster_id); +CREATE INDEX IF NOT EXISTS task_index ON ${dinky_schema}.dinky_history (task_id); +CREATE INDEX IF NOT EXISTS cluster_index ON ${dinky_schema}.dinky_history (cluster_id); -- Add comments to columns COMMENT - ON COLUMN public.dinky_history.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_history.id IS 'ID'; COMMENT - ON COLUMN public.dinky_history.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_history.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_history.cluster_id IS 'cluster ID'; + ON COLUMN ${dinky_schema}.dinky_history.cluster_id IS 'cluster ID'; COMMENT - ON COLUMN public.dinky_history.cluster_configuration_id IS 'cluster configuration id'; + ON COLUMN ${dinky_schema}.dinky_history.cluster_configuration_id IS 'cluster configuration id'; COMMENT - ON COLUMN public.dinky_history.session IS 'session'; + ON COLUMN ${dinky_schema}.dinky_history.session IS 'session'; COMMENT - ON COLUMN public.dinky_history.job_id IS 'Job ID'; + ON COLUMN ${dinky_schema}.dinky_history.job_id IS 'Job ID'; COMMENT - ON COLUMN public.dinky_history.job_name IS 'Job Name'; + ON COLUMN ${dinky_schema}.dinky_history.job_name IS 'Job Name'; COMMENT - ON COLUMN public.dinky_history.job_manager_address IS 'Job Manager Address'; + ON COLUMN ${dinky_schema}.dinky_history.job_manager_address IS 'Job Manager Address'; COMMENT - ON COLUMN public.dinky_history.status IS 'status'; + ON COLUMN ${dinky_schema}.dinky_history.status IS 'status'; COMMENT - ON COLUMN public.dinky_history.batch_model IS 'is batch model'; + ON COLUMN ${dinky_schema}.dinky_history.batch_model IS 'is batch model'; COMMENT - ON COLUMN public.dinky_history.type IS 'job type'; + ON COLUMN ${dinky_schema}.dinky_history.type IS 'job type'; COMMENT - ON COLUMN public.dinky_history.statement IS 'statement set'; + ON COLUMN ${dinky_schema}.dinky_history.statement IS 'statement set'; COMMENT - ON COLUMN public.dinky_history.error IS 'error message'; + ON COLUMN ${dinky_schema}.dinky_history.error IS 'error message'; COMMENT - ON COLUMN public.dinky_history.result IS 'result set'; + ON COLUMN ${dinky_schema}.dinky_history.result IS 'result set'; COMMENT - ON COLUMN public.dinky_history.config_json IS 'config json'; + ON COLUMN ${dinky_schema}.dinky_history.config_json IS 'config json'; COMMENT - ON COLUMN public.dinky_history.start_time IS 'job start time'; + ON COLUMN ${dinky_schema}.dinky_history.start_time IS 'job start time'; COMMENT - ON COLUMN public.dinky_history.end_time IS 'job end time'; + ON COLUMN ${dinky_schema}.dinky_history.end_time IS 'job end time'; COMMENT - ON COLUMN public.dinky_history.task_id IS 'task ID'; + ON COLUMN ${dinky_schema}.dinky_history.task_id IS 'task ID'; -- Add comment to the table COMMENT - ON TABLE public.dinky_history IS 'execution history'; + ON TABLE ${dinky_schema}.dinky_history IS 'execution history'; -- ---------------------------- --- Table structure for public.dinky_job_history +-- Table structure for ${dinky_schema}.dinky_job_history -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_job_history +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_job_history ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL DEFAULT 1, @@ -2421,41 +2421,41 @@ CREATE TABLE IF NOT EXISTS public.dinky_job_history -- 为列添加注释 COMMENT - ON COLUMN public.dinky_job_history.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_job_history.id IS 'id'; COMMENT - ON COLUMN public.dinky_job_history.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_job_history.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_job_history.job_json IS 'dinky job json'; + ON COLUMN ${dinky_schema}.dinky_job_history.job_json IS 'dinky job json'; COMMENT - ON COLUMN public.dinky_job_history.exceptions_json IS 'exception json '; + ON COLUMN ${dinky_schema}.dinky_job_history.exceptions_json IS 'exception json '; COMMENT - ON COLUMN public.dinky_job_history.checkpoints_json IS 'checkpoint json'; + ON COLUMN ${dinky_schema}.dinky_job_history.checkpoints_json IS 'checkpoint json'; COMMENT - ON COLUMN public.dinky_job_history.checkpoints_config_json IS 'checkpoints config json '; + ON COLUMN ${dinky_schema}.dinky_job_history.checkpoints_config_json IS 'checkpoints config json '; COMMENT - ON COLUMN public.dinky_job_history.config_json IS 'config json'; + ON COLUMN ${dinky_schema}.dinky_job_history.config_json IS 'config json'; COMMENT - ON COLUMN public.dinky_job_history.cluster_json IS 'cluster json'; + ON COLUMN ${dinky_schema}.dinky_job_history.cluster_json IS 'cluster json'; COMMENT - ON COLUMN public.dinky_job_history.cluster_configuration_json IS 'cluster configuration json'; + ON COLUMN ${dinky_schema}.dinky_job_history.cluster_configuration_json IS 'cluster configuration json'; COMMENT - ON COLUMN public.dinky_job_history.update_time IS 'update_time'; + ON COLUMN ${dinky_schema}.dinky_job_history.update_time IS 'update_time'; -- 为表添加注释 COMMENT - ON TABLE public.dinky_job_history IS 'dinky_job_history'; + ON TABLE ${dinky_schema}.dinky_job_history IS 'dinky_job_history'; CREATE OR REPLACE TRIGGER updatetime_dinky_job_history BEFORE UPDATE - ON public.dinky_job_history + ON ${dinky_schema}.dinky_job_history FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_job_instance +-- Table structure for ${dinky_schema}.dinky_job_instance -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_job_instance +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_job_instance ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(255) NULL, @@ -2478,64 +2478,64 @@ CREATE TABLE IF NOT EXISTS public.dinky_job_instance ); -- 添加唯一索引（name、tenant_id、task_id、history_id的组合必须是唯一的） -CREATE UNIQUE INDEX IF NOT EXISTS job_instance_un_idx1 ON public.dinky_job_instance (tenant_id, name, task_id, history_id); +CREATE UNIQUE INDEX IF NOT EXISTS job_instance_un_idx1 ON ${dinky_schema}.dinky_job_instance (tenant_id, name, task_id, history_id); -- 添加普通索引 -CREATE INDEX IF NOT EXISTS job_instance_task_id_idx1 ON public.dinky_job_instance (task_id); +CREATE INDEX IF NOT EXISTS job_instance_task_id_idx1 ON ${dinky_schema}.dinky_job_instance (task_id); -- 为列添加注释 COMMENT - ON COLUMN public.dinky_job_instance.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_job_instance.id IS 'id'; COMMENT - ON COLUMN public.dinky_job_instance.name IS 'job instance name'; + ON COLUMN ${dinky_schema}.dinky_job_instance.name IS 'job instance name'; COMMENT - ON COLUMN public.dinky_job_instance.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_job_instance.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_job_instance.task_id IS 'task id '; + ON COLUMN ${dinky_schema}.dinky_job_instance.task_id IS 'task id '; COMMENT - ON COLUMN public.dinky_job_instance.step IS 'job history step'; + ON COLUMN ${dinky_schema}.dinky_job_instance.step IS 'job history step'; COMMENT - ON COLUMN public.dinky_job_instance.cluster_id IS 'cluster id'; + ON COLUMN ${dinky_schema}.dinky_job_instance.cluster_id IS 'cluster id'; COMMENT - ON COLUMN public.dinky_job_instance.jid IS 'Flink JobId'; + ON COLUMN ${dinky_schema}.dinky_job_instance.jid IS 'Flink JobId'; COMMENT - ON COLUMN public.dinky_job_instance.status IS 'job instance status'; + ON COLUMN ${dinky_schema}.dinky_job_instance.status IS 'job instance status'; COMMENT - ON COLUMN public.dinky_job_instance.history_id IS 'history id'; + ON COLUMN ${dinky_schema}.dinky_job_instance.history_id IS 'history id'; COMMENT - ON COLUMN public.dinky_job_instance.create_time IS 'create_time'; + ON COLUMN ${dinky_schema}.dinky_job_instance.create_time IS 'create_time'; COMMENT - ON COLUMN public.dinky_job_instance.create_time IS 'create_time'; + ON COLUMN ${dinky_schema}.dinky_job_instance.create_time IS 'create_time'; COMMENT - ON COLUMN public.dinky_job_instance.finish_time IS 'finish_time'; + ON COLUMN ${dinky_schema}.dinky_job_instance.finish_time IS 'finish_time'; COMMENT - ON COLUMN public.dinky_job_instance.duration IS 'job duration'; + ON COLUMN ${dinky_schema}.dinky_job_instance.duration IS 'job duration'; COMMENT - ON COLUMN public.dinky_job_instance.error IS 'error log'; + ON COLUMN ${dinky_schema}.dinky_job_instance.error IS 'error log'; COMMENT - ON COLUMN public.dinky_job_instance.failed_restart_count IS 'failed restart count'; + ON COLUMN ${dinky_schema}.dinky_job_instance.failed_restart_count IS 'failed restart count'; COMMENT - ON COLUMN public.dinky_job_instance.creator IS 'creator'; + ON COLUMN ${dinky_schema}.dinky_job_instance.creator IS 'creator'; COMMENT - ON COLUMN public.dinky_job_instance.updater IS 'updater'; + ON COLUMN ${dinky_schema}.dinky_job_instance.updater IS 'updater'; COMMENT - ON COLUMN public.dinky_job_instance.operator IS 'operator uid'; + ON COLUMN ${dinky_schema}.dinky_job_instance.operator IS 'operator uid'; -- 为表添加注释 COMMENT - ON TABLE public.dinky_job_instance IS '工作实例'; + ON TABLE ${dinky_schema}.dinky_job_instance IS '工作实例'; CREATE OR REPLACE TRIGGER updatetime_dinky_job_instance BEFORE UPDATE - ON public.dinky_job_instance + ON ${dinky_schema}.dinky_job_instance FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_role +-- Table structure for ${dinky_schema}.dinky_role -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_role +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_role ( id SERIAL PRIMARY KEY NOT NULL, tenant_id INT NOT NULL, @@ -2548,49 +2548,49 @@ CREATE TABLE IF NOT EXISTS public.dinky_role ); -- 添加唯一索引 -CREATE UNIQUE INDEX IF NOT EXISTS role_un_idx1 ON public.dinky_role (role_code); +CREATE UNIQUE INDEX IF NOT EXISTS role_un_idx1 ON ${dinky_schema}.dinky_role (role_code); -- 为列添加注释 COMMENT - ON COLUMN public.dinky_role.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_role.id IS 'ID'; COMMENT - ON COLUMN public.dinky_role.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_role.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_role.role_code IS 'role code'; + ON COLUMN ${dinky_schema}.dinky_role.role_code IS 'role code'; COMMENT - ON COLUMN public.dinky_role.role_name IS 'role name'; + ON COLUMN ${dinky_schema}.dinky_role.role_name IS 'role name'; COMMENT - ON COLUMN public.dinky_role.is_delete IS 'is delete'; + ON COLUMN ${dinky_schema}.dinky_role.is_delete IS 'is delete'; COMMENT - ON COLUMN public.dinky_role.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_role.note IS 'note'; COMMENT - ON COLUMN public.dinky_role.create_time IS 'create_time'; + ON COLUMN ${dinky_schema}.dinky_role.create_time IS 'create_time'; COMMENT - ON COLUMN public.dinky_role.update_time IS 'update_time'; + ON COLUMN ${dinky_schema}.dinky_role.update_time IS 'update_time'; -- 为表添加注释 COMMENT - ON TABLE public.dinky_role IS 'dinky_role'; + ON TABLE ${dinky_schema}.dinky_role IS 'dinky_role'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_role BEFORE UPDATE - ON public.dinky_role + ON ${dinky_schema}.dinky_role FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Records of public.dinky_role +-- Records of ${dinky_schema}.dinky_role -- ---------------------------- -INSERT INTO public.dinky_role +INSERT INTO ${dinky_schema}.dinky_role VALUES (1, 1, 'SuperAdmin', 'SuperAdmin', false, 'SuperAdmin of Role', '2022-12-13 05:27:19', '2022-12-13 05:27:19'); -- ---------------------------- --- Table structure for public.dinky_savepoints +-- Table structure for ${dinky_schema}.dinky_savepoints -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_savepoints +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_savepoints ( id SERIAL PRIMARY KEY NOT NULL, task_id INT NOT NULL, @@ -2604,28 +2604,28 @@ CREATE TABLE IF NOT EXISTS public.dinky_savepoints -- 为列添加注释 COMMENT - ON COLUMN public.dinky_savepoints.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_savepoints.id IS 'ID'; COMMENT - ON COLUMN public.dinky_savepoints.task_id IS 'task id'; + ON COLUMN ${dinky_schema}.dinky_savepoints.task_id IS 'task id'; COMMENT - ON COLUMN public.dinky_savepoints.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_savepoints.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_savepoints.name IS 'task name'; + ON COLUMN ${dinky_schema}.dinky_savepoints.name IS 'task name'; COMMENT - ON COLUMN public.dinky_savepoints.type IS 'savepoint type'; + ON COLUMN ${dinky_schema}.dinky_savepoints.type IS 'savepoint type'; COMMENT - ON COLUMN public.dinky_savepoints.path IS 'savepoint path'; + ON COLUMN ${dinky_schema}.dinky_savepoints.path IS 'savepoint path'; COMMENT - ON COLUMN public.dinky_savepoints.create_time IS 'create_time'; + ON COLUMN ${dinky_schema}.dinky_savepoints.create_time IS 'create_time'; COMMENT - ON COLUMN public.dinky_savepoints.creator IS 'creator'; + ON COLUMN ${dinky_schema}.dinky_savepoints.creator IS 'creator'; -- 为表添加注释 COMMENT - ON TABLE public.dinky_savepoints IS 'dinky_savepoints'; + ON TABLE ${dinky_schema}.dinky_savepoints IS 'dinky_savepoints'; --- Table structure for public.dinky_sys_config -CREATE TABLE IF NOT EXISTS public.dinky_sys_config +-- Table structure for ${dinky_schema}.dinky_sys_config +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_config ( id serial PRIMARY KEY NOT NULL, name varchar(255) NOT NULL, @@ -2634,29 +2634,29 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_config update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); COMMENT - ON COLUMN public.dinky_sys_config.id IS 'ID'; + ON COLUMN ${dinky_schema}.dinky_sys_config.id IS 'ID'; COMMENT - ON COLUMN public.dinky_sys_config.name IS 'configuration name'; + ON COLUMN ${dinky_schema}.dinky_sys_config.name IS 'configuration name'; COMMENT - ON COLUMN public.dinky_sys_config.value IS 'configuration value'; + ON COLUMN ${dinky_schema}.dinky_sys_config.value IS 'configuration value'; COMMENT - ON COLUMN public.dinky_sys_config.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_sys_config.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_sys_config.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_sys_config.update_time IS 'update time'; COMMENT - ON TABLE public.dinky_sys_config IS 'system configuration'; + ON TABLE ${dinky_schema}.dinky_sys_config IS 'system configuration'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_sys_config BEFORE UPDATE - ON public.dinky_sys_config + ON ${dinky_schema}.dinky_sys_config FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_task -CREATE TABLE IF NOT EXISTS public.dinky_task +-- Table structure for ${dinky_schema}.dinky_task +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_task ( id serial PRIMARY KEY not null, name varchar(255) NOT NULL, @@ -2689,48 +2689,48 @@ CREATE TABLE IF NOT EXISTS public.dinky_task operator int ); -CREATE UNIQUE INDEX IF NOT EXISTS task_un_idx1 ON public.dinky_task (name, tenant_id); -COMMENT ON TABLE public.dinky_task IS 'Task'; -COMMENT ON COLUMN public.dinky_task.id IS 'ID'; -COMMENT ON COLUMN public.dinky_task.name IS 'Job name'; -COMMENT ON COLUMN public.dinky_task.tenant_id IS 'tenant id'; -COMMENT ON COLUMN public.dinky_task.dialect IS 'dialect'; -COMMENT ON COLUMN public.dinky_task.type IS 'Job type'; -COMMENT ON COLUMN public.dinky_task.check_point IS 'CheckPoint trigger seconds'; -COMMENT ON COLUMN public.dinky_task.save_point_strategy IS 'SavePoint strategy'; -COMMENT ON COLUMN public.dinky_task.save_point_path IS 'SavePointPath'; -COMMENT ON COLUMN public.dinky_task.parallelism IS 'parallelism'; -COMMENT ON COLUMN public.dinky_task.fragment IS 'fragment'; -COMMENT ON COLUMN public.dinky_task.statement_set IS 'enable statement set'; -COMMENT ON COLUMN public.dinky_task.batch_model IS 'use batch model'; -COMMENT ON COLUMN public.dinky_task.cluster_id IS 'Flink cluster ID'; -COMMENT ON COLUMN public.dinky_task.cluster_configuration_id IS 'cluster configuration ID'; -COMMENT ON COLUMN public.dinky_task.database_id IS 'database ID'; -COMMENT ON COLUMN public.dinky_task.env_id IS 'env id'; -COMMENT ON COLUMN public.dinky_task.alert_group_id IS 'alert group id'; -COMMENT ON COLUMN public.dinky_task.config_json IS 'configuration json'; -COMMENT ON COLUMN public.dinky_task.note IS 'Job Note'; -COMMENT ON COLUMN public.dinky_task.step IS 'Job lifecycle'; -COMMENT ON COLUMN public.dinky_task.job_instance_id IS 'job instance id'; -COMMENT ON COLUMN public.dinky_task.enabled IS 'is enable'; -COMMENT ON COLUMN public.dinky_task.create_time IS 'create_time'; -COMMENT ON COLUMN public.dinky_task.update_time IS 'update_time'; -COMMENT ON COLUMN public.dinky_task.version_id IS 'version id'; -COMMENT ON COLUMN public.dinky_task.statement IS 'sql statement'; -COMMENT ON COLUMN public.dinky_task.creator IS 'creator'; -COMMENT ON COLUMN public.dinky_task.updater IS 'updater'; -COMMENT ON COLUMN public.dinky_task.operator IS 'operator user id'; +CREATE UNIQUE INDEX IF NOT EXISTS task_un_idx1 ON ${dinky_schema}.dinky_task (name, tenant_id); +COMMENT ON TABLE ${dinky_schema}.dinky_task IS 'Task'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.name IS 'Job name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.tenant_id IS 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.dialect IS 'dialect'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.type IS 'Job type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.check_point IS 'CheckPoint trigger seconds'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.save_point_strategy IS 'SavePoint strategy'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.save_point_path IS 'SavePointPath'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.parallelism IS 'parallelism'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.fragment IS 'fragment'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.statement_set IS 'enable statement set'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.batch_model IS 'use batch model'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.cluster_id IS 'Flink cluster ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.cluster_configuration_id IS 'cluster configuration ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.database_id IS 'database ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.env_id IS 'env id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.alert_group_id IS 'alert group id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.config_json IS 'configuration json'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.note IS 'Job Note'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.step IS 'Job lifecycle'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.job_instance_id IS 'job instance id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.enabled IS 'is enable'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.create_time IS 'create_time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.update_time IS 'update_time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.version_id IS 'version id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.statement IS 'sql statement'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.creator IS 'creator'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.updater IS 'updater'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.operator IS 'operator user id'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_task BEFORE UPDATE - ON public.dinky_task + ON ${dinky_schema}.dinky_task FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_task_version -CREATE TABLE IF NOT EXISTS public.dinky_task_version +-- Table structure for ${dinky_schema}.dinky_task_version +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_task_version ( id serial PRIMARY KEY NOT NULL, task_id int NOT NULL, @@ -2744,20 +2744,20 @@ CREATE TABLE IF NOT EXISTS public.dinky_task_version create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, creator int ); -CREATE UNIQUE INDEX IF NOT EXISTS task_version_un_idx1 ON public.dinky_task_version (task_id, tenant_id, version_id); -COMMENT ON TABLE public.dinky_task_version IS 'job history version'; -COMMENT ON COLUMN public.dinky_task_version.id IS 'ID'; -COMMENT ON COLUMN public.dinky_task_version.task_id IS 'task ID '; -COMMENT ON COLUMN public.dinky_task_version.tenant_id IS 'tenant id'; -COMMENT ON COLUMN public.dinky_task_version.version_id IS 'version ID '; -COMMENT ON COLUMN public.dinky_task_version.statement IS 'flink sql statement'; -COMMENT ON COLUMN public.dinky_task_version.name IS 'version name'; -COMMENT ON COLUMN public.dinky_task_version.type IS 'type'; -COMMENT ON COLUMN public.dinky_task_version.task_configure IS 'task configuration'; - - --- Table structure for public.dinky_tenant -CREATE TABLE IF NOT EXISTS public.dinky_tenant +CREATE UNIQUE INDEX IF NOT EXISTS task_version_un_idx1 ON ${dinky_schema}.dinky_task_version (task_id, tenant_id, version_id); +COMMENT ON TABLE ${dinky_schema}.dinky_task_version IS 'job history version'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.task_id IS 'task ID '; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.tenant_id IS 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.version_id IS 'version ID '; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.statement IS 'flink sql statement'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.name IS 'version name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.type IS 'type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_task_version.task_configure IS 'task configuration'; + + +-- Table structure for ${dinky_schema}.dinky_tenant +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_tenant ( id serial PRIMARY KEY NOT NULL, tenant_code varchar(64) NOT NULL, @@ -2766,26 +2766,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_tenant create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON TABLE public.dinky_tenant IS 'tenant'; -COMMENT ON COLUMN public.dinky_tenant.id IS 'ID'; -COMMENT ON COLUMN public.dinky_tenant.tenant_code IS 'tenant code'; -COMMENT ON COLUMN public.dinky_tenant.is_delete IS 'is delete'; -COMMENT ON COLUMN public.dinky_tenant.note IS 'note'; +COMMENT ON TABLE ${dinky_schema}.dinky_tenant IS 'tenant'; +COMMENT ON COLUMN ${dinky_schema}.dinky_tenant.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_tenant.tenant_code IS 'tenant code'; +COMMENT ON COLUMN ${dinky_schema}.dinky_tenant.is_delete IS 'is delete'; +COMMENT ON COLUMN ${dinky_schema}.dinky_tenant.note IS 'note'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_tenant BEFORE UPDATE - ON public.dinky_tenant + ON ${dinky_schema}.dinky_tenant FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Insert default record into public.dinky_tenant -INSERT INTO public.dinky_tenant (id, tenant_code, is_delete, note, create_time, update_time) +-- Insert default record into ${dinky_schema}.dinky_tenant +INSERT INTO ${dinky_schema}.dinky_tenant (id, tenant_code, is_delete, note, create_time, update_time) VALUES (1, 'DefaultTenant', FALSE, 'DefaultTenant', '2022-12-13 05:27:19', '2022-12-13 05:27:19'); --- Table structure for public.dinky_udf_template -CREATE TABLE IF NOT EXISTS public.dinky_udf_template +-- Table structure for ${dinky_schema}.dinky_udf_template +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_udf_template ( id serial PRIMARY KEY NOT NULL, name varchar(100), @@ -2798,24 +2798,24 @@ CREATE TABLE IF NOT EXISTS public.dinky_udf_template creator int, updater int ); -COMMENT ON TABLE public.dinky_udf_template IS 'udf template'; -COMMENT ON COLUMN public.dinky_udf_template.id IS 'ID'; -COMMENT ON COLUMN public.dinky_udf_template.name IS 'template name'; -COMMENT ON COLUMN public.dinky_udf_template.code_type IS 'code type'; -COMMENT ON COLUMN public.dinky_udf_template.function_type IS 'function type'; -COMMENT ON COLUMN public.dinky_udf_template.template_code IS 'code'; -COMMENT ON COLUMN public.dinky_udf_template.enabled IS 'enabled'; +COMMENT ON TABLE ${dinky_schema}.dinky_udf_template IS 'udf template'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.name IS 'template name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.code_type IS 'code type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.function_type IS 'function type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.template_code IS 'code'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_template.enabled IS 'enabled'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_udf_template BEFORE UPDATE - ON public.dinky_udf_template + ON ${dinky_schema}.dinky_udf_template FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_udf_template -INSERT INTO public.dinky_udf_template (id, name, code_type, function_type, template_code, enabled, create_time, update_time, +-- Records of ${dinky_schema}.dinky_udf_template +INSERT INTO ${dinky_schema}.dinky_udf_template (id, name, code_type, function_type, template_code, enabled, create_time, update_time, creator, updater) VALUES (1, 'java_udf', 'Java', 'UDF', $$${(package=='''')?string('''',''package ''+package+'';'')} @@ -2908,8 +2908,8 @@ $$, null); --- Table structure for public.dinky_user -CREATE TABLE IF NOT EXISTS public.dinky_user +-- Table structure for ${dinky_schema}.dinky_user +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_user ( id serial PRIMARY KEY NOT NULL, username varchar(50) NOT NULL, @@ -2925,33 +2925,33 @@ CREATE TABLE IF NOT EXISTS public.dinky_user create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON TABLE public.dinky_user IS 'user'; -COMMENT ON COLUMN public.dinky_user.id IS 'id'; -COMMENT ON COLUMN public.dinky_user.username IS 'username'; -COMMENT ON COLUMN public.dinky_user.password IS 'password'; -COMMENT ON COLUMN public.dinky_user.nickname IS 'nickname'; -COMMENT ON COLUMN public.dinky_user.worknum IS 'worknum'; -COMMENT ON COLUMN public.dinky_user.avatar IS 'avatar'; -COMMENT ON COLUMN public.dinky_user.mobile IS 'mobile phone'; -COMMENT ON COLUMN public.dinky_user.enabled IS 'enabled'; -COMMENT ON COLUMN public.dinky_user.super_admin_flag IS 'is super admin(0:false,1true)'; +COMMENT ON TABLE ${dinky_schema}.dinky_user IS 'user'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.username IS 'username'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.password IS 'password'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.nickname IS 'nickname'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.worknum IS 'worknum'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.avatar IS 'avatar'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.mobile IS 'mobile phone'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.enabled IS 'enabled'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user.super_admin_flag IS 'is super admin(0:false,1true)'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_user BEFORE UPDATE - ON public.dinky_user + ON ${dinky_schema}.dinky_user FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_user -INSERT INTO public.dinky_user (id, username, user_type, password, nickname, worknum, avatar, mobile, enabled, super_admin_flag, +-- Records of ${dinky_schema}.dinky_user +INSERT INTO ${dinky_schema}.dinky_user (id, username, user_type, password, nickname, worknum, avatar, mobile, enabled, super_admin_flag, is_delete, create_time, update_time) VALUES (1, 'admin', 0, '21232f297a57a5a743894a0e4a801fc3', 'Admin', 'Dinky-001', null, '17777777777', true, 1, false, '2022-12-13 05:27:19', '2023-07-28 23:22:52'); --- Table structure for public.dinky_user_role -CREATE TABLE IF NOT EXISTS public.dinky_user_role +-- Table structure for ${dinky_schema}.dinky_user_role +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_user_role ( id serial PRIMARY KEY NOT NULL, user_id int NOT NULL, @@ -2960,26 +2960,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_user_role update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -CREATE UNIQUE INDEX IF NOT EXISTS user_role_un_idx1 ON public.dinky_user_role (user_id, role_id); +CREATE UNIQUE INDEX IF NOT EXISTS user_role_un_idx1 ON ${dinky_schema}.dinky_user_role (user_id, role_id); -COMMENT ON TABLE public.dinky_user_role IS 'Relationship between users and roles'; -COMMENT ON COLUMN public.dinky_user_role.id IS 'id'; -COMMENT ON COLUMN public.dinky_user_role.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_user_role.role_id IS 'role_id'; +COMMENT ON TABLE ${dinky_schema}.dinky_user_role IS 'Relationship between users and roles'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_role.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_role.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_role.role_id IS 'role_id'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_user_role BEFORE UPDATE - ON public.dinky_user_role + ON ${dinky_schema}.dinky_user_role FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_user_role -INSERT INTO public.dinky_user_role (id, user_id, role_id, create_time, update_time) +-- Records of ${dinky_schema}.dinky_user_role +INSERT INTO ${dinky_schema}.dinky_user_role (id, user_id, role_id, create_time, update_time) VALUES (1, 1, 1, '2022-12-13 05:27:19', '2022-12-13 05:27:19'); --- Table structure for public.dinky_user_tenant -CREATE TABLE IF NOT EXISTS public.dinky_user_tenant +-- Table structure for ${dinky_schema}.dinky_user_tenant +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_user_tenant ( id serial PRIMARY KEY, user_id int NOT NULL, @@ -2989,24 +2989,24 @@ CREATE TABLE IF NOT EXISTS public.dinky_user_tenant update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -CREATE UNIQUE INDEX IF NOT EXISTS user_tenant_un_idx1 ON public.dinky_user_tenant (user_id, tenant_id); +CREATE UNIQUE INDEX IF NOT EXISTS user_tenant_un_idx1 ON ${dinky_schema}.dinky_user_tenant (user_id, tenant_id); -COMMENT ON TABLE public.dinky_user_tenant IS 'Relationship between users and tenants'; -COMMENT ON COLUMN public.dinky_user_tenant.id IS 'id'; -COMMENT ON COLUMN public.dinky_user_tenant.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_user_tenant.tenant_id IS 'tenant id'; -COMMENT ON COLUMN public.dinky_user_tenant.tenant_admin_flag IS 'tenant admin flag(0:false,1:true)'; +COMMENT ON TABLE ${dinky_schema}.dinky_user_tenant IS 'Relationship between users and tenants'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant.tenant_id IS 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant.tenant_admin_flag IS 'tenant admin flag(0:false,1:true)'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_user_tenant BEFORE UPDATE - ON public.dinky_user_tenant + ON ${dinky_schema}.dinky_user_tenant FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_user_tenant -INSERT INTO public.dinky_user_tenant (id, user_id, tenant_id, tenant_admin_flag, create_time, update_time) +-- Records of ${dinky_schema}.dinky_user_tenant +INSERT INTO ${dinky_schema}.dinky_user_tenant (id, user_id, tenant_id, tenant_admin_flag, create_time, update_time) VALUES (1, 1, 1, 1, CURRENT_TIMESTAMP, CURRENT_TIMESTAMP); @@ -3163,8 +3163,8 @@ CREATE OR REPLACE TRIGGER set_update_time_metadata_table_property FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_row_permissions -CREATE TABLE IF NOT EXISTS public.dinky_row_permissions +-- Table structure for ${dinky_schema}.dinky_row_permissions +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_row_permissions ( id serial PRIMARY KEY NOT NULL, role_id int NOT NULL, @@ -3175,22 +3175,22 @@ CREATE TABLE IF NOT EXISTS public.dinky_row_permissions creator int, updater int ); -COMMENT ON TABLE public.dinky_row_permissions IS 'row permissions of select'; +COMMENT ON TABLE ${dinky_schema}.dinky_row_permissions IS 'row permissions of select'; -COMMENT ON COLUMN public.dinky_row_permissions.id IS 'id'; -COMMENT ON COLUMN public.dinky_row_permissions.role_id IS 'role id'; -COMMENT ON COLUMN public.dinky_row_permissions.table_name IS 'table name'; -COMMENT ON COLUMN public.dinky_row_permissions.expression IS 'expression'; +COMMENT ON COLUMN ${dinky_schema}.dinky_row_permissions.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_row_permissions.role_id IS 'role id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_row_permissions.table_name IS 'table name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_row_permissions.expression IS 'expression'; -- 创建触发器以在每次更新记录时设置update_time CREATE OR REPLACE TRIGGER set_update_time_dinky_row_permissions BEFORE UPDATE - ON public.dinky_row_permissions + ON ${dinky_schema}.dinky_row_permissions FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_git_project -CREATE TABLE IF NOT EXISTS public.dinky_git_project +-- Table structure for ${dinky_schema}.dinky_git_project +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_git_project ( id SERIAL PRIMARY KEY NOT NULL, tenant_id bigint NOT NULL, @@ -3217,30 +3217,30 @@ CREATE TABLE IF NOT EXISTS public.dinky_git_project updater int, operator int ); -CREATE INDEX IF NOT EXISTS tenant_id_idx ON public.dinky_git_project (tenant_id); - -COMMENT ON TABLE public.dinky_git_project IS 'Git project configurations'; - -COMMENT ON COLUMN public.dinky_git_project.id IS 'id'; -COMMENT ON COLUMN public.dinky_git_project.private_key IS 'keypath'; -COMMENT ON COLUMN public.dinky_git_project.code_type IS 'code type(1-java,2-python)'; -COMMENT ON COLUMN public.dinky_git_project.type IS '1-http ,2-ssh'; -COMMENT ON COLUMN public.dinky_git_project.id IS 'id'; -COMMENT ON COLUMN public.dinky_git_project.build_state IS '0-notStart 1-process 2-failed 3-success'; -COMMENT ON COLUMN public.dinky_git_project.build_step IS 'different from java and python, when build java project, the step value is as follows: 0: environment check 1: clone project 2: compile and build 3: get artifact 4: analyze UDF 5: finish; when build python project, the step value is as follows: 0: environment check 1: clone project 2: get artifact 3: analyze UDF 4: finish'; -COMMENT ON COLUMN public.dinky_git_project.enabled IS '0-disable 1-enable'; -COMMENT ON COLUMN public.dinky_git_project.udf_class_map_list IS 'scan udf class'; -COMMENT ON COLUMN public.dinky_git_project.order_line IS 'order'; --- public.dinky_git_project +CREATE INDEX IF NOT EXISTS tenant_id_idx ON ${dinky_schema}.dinky_git_project (tenant_id); + +COMMENT ON TABLE ${dinky_schema}.dinky_git_project IS 'Git project configurations'; + +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.private_key IS 'keypath'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.code_type IS 'code type(1-java,2-python)'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.type IS '1-http ,2-ssh'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.build_state IS '0-notStart 1-process 2-failed 3-success'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.build_step IS 'different from java and python, when build java project, the step value is as follows: 0: environment check 1: clone project 2: compile and build 3: get artifact 4: analyze UDF 5: finish; when build python project, the step value is as follows: 0: environment check 1: clone project 2: get artifact 3: analyze UDF 4: finish'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.enabled IS '0-disable 1-enable'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.udf_class_map_list IS 'scan udf class'; +COMMENT ON COLUMN ${dinky_schema}.dinky_git_project.order_line IS 'order'; +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_git_project_modtime BEFORE UPDATE - ON public.dinky_git_project + ON ${dinky_schema}.dinky_git_project FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_git_project -INSERT INTO public.dinky_git_project (id, tenant_id, name, url, branch, username, password, private_key, pom, build_args, +-- Records of ${dinky_schema}.dinky_git_project +INSERT INTO ${dinky_schema}.dinky_git_project (id, tenant_id, name, url, branch, username, password, private_key, pom, build_args, code_type, type, last_build, description, build_state, build_step, enabled, udf_class_map_list, order_line) VALUES (1, 1, 'java-udf', 'https://github.com/DataLinkDC/dinky-quickstart-java.git', 'master', NULL, NULL, NULL, NULL, @@ -3249,8 +3249,8 @@ VALUES (1, 1, 'java-udf', 'https://github.com/DataLinkDC/dinky-quickstart-java.g NULL, '', 2, 1, NULL, NULL, 0, 0, true, '[]', 2); --- Table structure for public.dinky_metrics -CREATE TABLE IF NOT EXISTS public.dinky_metrics +-- Table structure for ${dinky_schema}.dinky_metrics +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_metrics ( id SERIAL PRIMARY KEY NOT NULL, task_id INT, @@ -3264,26 +3264,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_metrics create_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON TABLE public.dinky_metrics IS 'metrics layout'; - -COMMENT ON COLUMN public.dinky_metrics.id IS 'id'; -COMMENT ON COLUMN public.dinky_metrics.task_id IS 'task id'; -COMMENT ON COLUMN public.dinky_metrics.vertices IS 'vertices'; -COMMENT ON COLUMN public.dinky_metrics.metrics IS 'metrics'; -COMMENT ON COLUMN public.dinky_metrics.position IS 'position'; -COMMENT ON COLUMN public.dinky_metrics.show_type IS 'show type'; -COMMENT ON COLUMN public.dinky_metrics.show_size IS 'show size'; -COMMENT ON COLUMN public.dinky_metrics.title IS 'title'; -COMMENT ON COLUMN public.dinky_metrics.layout_name IS 'layout_name'; --- public.dinky_git_project +COMMENT ON TABLE ${dinky_schema}.dinky_metrics IS 'metrics layout'; + +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.task_id IS 'task id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.vertices IS 'vertices'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.metrics IS 'metrics'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.position IS 'position'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.show_type IS 'show type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.show_size IS 'show size'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.title IS 'title'; +COMMENT ON COLUMN ${dinky_schema}.dinky_metrics.layout_name IS 'layout_name'; +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_metrics BEFORE UPDATE - ON public.dinky_metrics + ON ${dinky_schema}.dinky_metrics FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_resources -CREATE TABLE IF NOT EXISTS public.dinky_resources +-- Table structure for ${dinky_schema}.dinky_resources +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_resources ( id SERIAL PRIMARY KEY NOT NULL, file_name VARCHAR(64), @@ -3300,29 +3300,29 @@ CREATE TABLE IF NOT EXISTS public.dinky_resources updater INT ); -CREATE UNIQUE INDEX IF NOT EXISTS dinky_resources_un ON public.dinky_resources (full_name, type); +CREATE UNIQUE INDEX IF NOT EXISTS dinky_resources_un ON ${dinky_schema}.dinky_resources (full_name, type); -COMMENT ON TABLE public.dinky_resources IS 'resources'; +COMMENT ON TABLE ${dinky_schema}.dinky_resources IS 'resources'; -COMMENT ON COLUMN public.dinky_resources.id IS 'key'; -COMMENT ON COLUMN public.dinky_resources.file_name IS 'file name'; -COMMENT ON COLUMN public.dinky_resources.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_resources.type IS 'resource type,0:FILE，1:UDF'; -COMMENT ON COLUMN public.dinky_resources.size IS 'resource size'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources.id IS 'key'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources.file_name IS 'file name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources.type IS 'resource type,0:FILE，1:UDF'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources.size IS 'resource size'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_resources BEFORE UPDATE - ON public.dinky_resources + ON ${dinky_schema}.dinky_resources FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Records of public.dinky_resources -INSERT INTO public.dinky_resources (id, file_name, description, user_id, type, size, pid, full_name, is_directory) +-- Records of ${dinky_schema}.dinky_resources +INSERT INTO ${dinky_schema}.dinky_resources (id, file_name, description, user_id, type, size, pid, full_name, is_directory) VALUES (0, 'Root', 'main folder', 1, 0, 0, -1, '/', 1); --- Table structure for public.dinky_sys_login_log -CREATE TABLE IF NOT EXISTS public.dinky_sys_login_log +-- Table structure for ${dinky_schema}.dinky_sys_login_log +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_login_log ( id SERIAL PRIMARY KEY NOT NULL, user_id INT NOT NULL, @@ -3336,26 +3336,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_login_log update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP, is_deleted SMALLINT NOT NULL DEFAULT 0 ); -COMMENT ON TABLE public.dinky_sys_login_log IS 'system login log record'; - -COMMENT ON COLUMN public.dinky_sys_login_log.id IS 'key'; -COMMENT ON COLUMN public.dinky_sys_login_log.username IS 'username'; -COMMENT ON COLUMN public.dinky_sys_login_log.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_sys_login_log.login_type IS 'login type（0:LOCAL,1:LDAP）'; -COMMENT ON COLUMN public.dinky_sys_login_log.ip IS 'ip addr'; -COMMENT ON COLUMN public.dinky_sys_login_log.status IS 'login status'; -COMMENT ON COLUMN public.dinky_sys_login_log.msg IS 'status msg'; -COMMENT ON COLUMN public.dinky_sys_login_log.access_time IS 'access time'; - --- public.dinky_git_project +COMMENT ON TABLE ${dinky_schema}.dinky_sys_login_log IS 'system login log record'; + +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.id IS 'key'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.username IS 'username'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.login_type IS 'login type（0:LOCAL,1:LDAP）'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.ip IS 'ip addr'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.status IS 'login status'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.msg IS 'status msg'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_login_log.access_time IS 'access time'; + +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_sys_login_log BEFORE UPDATE - ON public.dinky_sys_login_log + ON ${dinky_schema}.dinky_sys_login_log FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_sys_operate_log -CREATE TABLE IF NOT EXISTS public.dinky_sys_operate_log +-- Table structure for ${dinky_schema}.dinky_sys_operate_log +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_operate_log ( id BIGSERIAL PRIMARY KEY NOT NULL, module_name VARCHAR(50), @@ -3374,33 +3374,33 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_operate_log operate_time TIMESTAMP WITHOUT TIME ZONE ); -COMMENT ON TABLE public.dinky_sys_operate_log IS 'operate log record'; - -COMMENT ON COLUMN public.dinky_sys_operate_log.id IS 'key'; -COMMENT ON COLUMN public.dinky_sys_operate_log.module_name IS 'module name'; -COMMENT ON COLUMN public.dinky_sys_operate_log.business_type IS 'business type'; -COMMENT ON COLUMN public.dinky_sys_operate_log.method IS 'method name'; -COMMENT ON COLUMN public.dinky_sys_operate_log.request_method IS 'request method'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_name IS 'operate name'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_user_id IS 'operate user id'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_url IS 'operate url'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_ip IS 'ip'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_location IS 'operate location'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_param IS 'request param'; -COMMENT ON COLUMN public.dinky_sys_operate_log.json_result IS 'return json result'; -COMMENT ON COLUMN public.dinky_sys_operate_log.status IS 'operate status'; -COMMENT ON COLUMN public.dinky_sys_operate_log.error_msg IS 'error msg'; -COMMENT ON COLUMN public.dinky_sys_operate_log.operate_time IS 'operate time'; - --- public.dinky_git_project +COMMENT ON TABLE ${dinky_schema}.dinky_sys_operate_log IS 'operate log record'; + +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.id IS 'key'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.module_name IS 'module name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.business_type IS 'business type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.method IS 'method name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.request_method IS 'request method'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_name IS 'operate name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_user_id IS 'operate user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_url IS 'operate url'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_ip IS 'ip'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_location IS 'operate location'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_param IS 'request param'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.json_result IS 'return json result'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.status IS 'operate status'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.error_msg IS 'error msg'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_operate_log.operate_time IS 'operate time'; + +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_sys_operate_log BEFORE UPDATE - ON public.dinky_sys_operate_log + ON ${dinky_schema}.dinky_sys_operate_log FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_sys_menu -CREATE TABLE IF NOT EXISTS public.dinky_sys_menu +-- Table structure for ${dinky_schema}.dinky_sys_menu +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_menu ( id BIGSERIAL PRIMARY KEY not null, parent_id BIGINT NOT NULL, @@ -3416,485 +3416,485 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_menu update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP, note VARCHAR(255) ); -COMMENT ON TABLE public.dinky_sys_menu IS 'menu'; +COMMENT ON TABLE ${dinky_schema}.dinky_sys_menu IS 'menu'; -COMMENT ON COLUMN public.dinky_sys_menu.id IS 'id'; -COMMENT ON COLUMN public.dinky_sys_menu.parent_id IS 'parent menu id'; -COMMENT ON COLUMN public.dinky_sys_menu.name IS 'menu button name'; -COMMENT ON COLUMN public.dinky_sys_menu.path IS 'routing path'; -COMMENT ON COLUMN public.dinky_sys_menu.component IS 'routing component component'; -COMMENT ON COLUMN public.dinky_sys_menu.perms IS 'authority id'; -COMMENT ON COLUMN public.dinky_sys_menu.icon IS 'icon'; -COMMENT ON COLUMN public.dinky_sys_menu.type IS 'type(M:directory C:menu F:button)'; -COMMENT ON COLUMN public.dinky_sys_menu.display IS 'whether the menu is displayed'; -COMMENT ON COLUMN public.dinky_sys_menu.order_num IS 'sort'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.parent_id IS 'parent menu id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.name IS 'menu button name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.path IS 'routing path'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.component IS 'routing component component'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.perms IS 'authority id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.icon IS 'icon'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.type IS 'type(M:directory C:menu F:button)'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.display IS 'whether the menu is displayed'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_menu.order_num IS 'sort'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_sys_menu BEFORE UPDATE - ON public.dinky_sys_menu + ON ${dinky_schema}.dinky_sys_menu FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Records of public.dinky_sys_menu +-- Records of ${dinky_schema}.dinky_sys_menu -- ---------------------------- --- insert into public.dinky_sys_menu +-- insert into ${dinky_schema}.dinky_sys_menu -- values (1, -1, '首页', '/home', './Home', 'home', 'HomeOutlined', 'C', 0, 1, '2023-08-11 14:06:52', -- '2023-09-25 18:26:45', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (2, -1, '运维中心', '/devops', null, 'devops', 'ControlOutlined', 'M', 0, 20, '2023-08-11 14:06:52', '2023-09-26 14:53:34', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (3, -1, '注册中心', '/registration', null, 'registration', 'AppstoreOutlined', 'M', 0, 23, '2023-08-11 14:06:52', '2023-09-26 14:54:03', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (4, -1, '认证中心', '/auth', null, 'auth', 'SafetyCertificateOutlined', 'M', 0, 79, '2023-08-11 14:06:52', '2023-09-26 15:08:42', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (5, -1, '数据开发', '/datastudio', './DataStudio', 'datastudio', 'CodeOutlined', 'C', 0, 4, '2023-08-11 14:06:52', '2023-09-26 14:49:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (6, -1, '配置中心', '/settings', null, 'settings', 'SettingOutlined', 'M', 0, 115, '2023-08-11 14:06:53', '2023-09-26 15:16:03', null); --- insert into public.dinky_sys_menu +-- insert into ${dinky_schema}.dinky_sys_menu -- values (7, -1, '关于', '/about', './Other/About', 'about', 'SmileOutlined', 'C', 0, 143, '2023-08-11 14:06:53', -- '2023-09-26 15:21:21', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (8, -1, '监控', '/metrics', './Metrics', 'metrics', 'DashboardOutlined', 'C', 0, 140, '2023-08-11 14:06:53', '2023-09-26 15:20:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (9, 3, '集群', '/registration/cluster', null, 'registration:cluster', 'GoldOutlined', 'M', 0, 24, '2023-08-11 14:06:54', '2023-09-26 14:54:19', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (10, 3, '数据源', '/registration/datasource', '', 'registration:datasource', 'DatabaseOutlined', 'M', 0, 37, '2023-08-11 14:06:54', '2024-01-18 21:38:56', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (11, -1, '个人中心', '/account/center', './Other/PersonCenter', 'account:center', 'UserOutlined', 'C', 0, 144, '2023-08-11 14:06:54', '2023-09-26 15:21:29', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (12, 3, '告警', '/registration/alert', null, 'registration:alert', 'AlertOutlined', 'M', 0, 43, '2023-08-11 14:06:54', '2023-09-26 15:01:32', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (13, 3, '文档', '/registration/document', './RegCenter/Document', 'registration:document', 'BookOutlined', 'C', 0, 55, '2023-08-11 14:06:54', '2023-09-26 15:03:59', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (14, 3, '全局变量', '/registration/fragment', './RegCenter/GlobalVar', 'registration:fragment', 'RocketOutlined', 'C', 0, 59, '2023-08-11 14:06:54', '2023-09-26 15:04:55', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (15, 3, 'Git 项目', '/registration/gitproject', './RegCenter/GitProject', 'registration:gitproject', 'GithubOutlined', 'C', 0, 63, '2023-08-11 14:06:54', '2023-09-26 15:05:37', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (16, 3, 'UDF 模版', '/registration/udf', './RegCenter/UDF', 'registration:udf', 'ToolOutlined', 'C', 0, 69, '2023-08-11 14:06:54', '2023-09-26 15:06:40', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (17, 2, '任务详情', '/devops/job-detail', './DevOps/JobDetail', 'devops:job-detail', 'InfoCircleOutlined', 'C', 0, 22, '2023-08-11 14:06:54', '2024-01-18 22:36:11', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (18, 2, '任务列表', '/devops/joblist', './DevOps', 'devops:joblist', 'AppstoreFilled', 'C', 0, 21, '2023-08-11 14:06:54', '2024-01-18 22:36:00', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (19, 3, '资源中心', '/registration/resource', './RegCenter/Resource', 'registration:resource', 'FileZipOutlined', 'C', 0, 73, '2023-08-11 14:06:54', '2023-09-26 15:07:25', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (20, 4, '角色', '/auth/role', './AuthCenter/Role', 'auth:role', 'TeamOutlined', 'C', 0, 88, '2023-08-11 14:06:54', '2023-09-26 15:10:19', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (21, 4, '用户', '/auth/user', './AuthCenter/User', 'auth:user', 'UserOutlined', 'C', 0, 80, '2023-08-11 14:06:54', '2023-09-26 15:08:51', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (22, 4, '菜单', '/auth/menu', './AuthCenter/Menu', 'auth:menu', 'MenuOutlined', 'C', 0, 94, '2023-08-11 14:06:54', '2023-09-26 15:11:34', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (23, 4, '租户', '/auth/tenant', './AuthCenter/Tenant', 'auth:tenant', 'SecurityScanOutlined', 'C', 0, 104, '2023-08-11 14:06:54', '2023-09-26 15:13:35', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (24, 6, '全局设置', '/settings/globalsetting', './SettingCenter/GlobalSetting', 'settings:globalsetting', 'SettingOutlined', 'C', 0, 116, '2023-08-11 14:06:54', '2023-09-26 15:16:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (25, 6, '系统日志', '/settings/systemlog', './SettingCenter/SystemLogs', 'settings:systemlog', 'InfoCircleOutlined', 'C', 0, 131, '2023-08-11 14:06:55', '2023-09-26 15:18:53', null); --- insert into public.dinky_sys_menu +-- insert into ${dinky_schema}.dinky_sys_menu -- values (26, 6, '进程', '/settings/process', './SettingCenter/Process', 'settings:process', 'ReconciliationOutlined', -- 'C', 0, 135, '2023-08-11 14:06:55', '2023-09-26 15:19:35', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (27, 4, '行权限', '/auth/rowpermissions', './AuthCenter/RowPermissions', 'auth:rowpermissions', 'SafetyCertificateOutlined', 'C', 0, 100, '2023-08-11 14:06:55', '2023-09-26 15:12:46', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (28, 9, 'Flink 实例', '/registration/cluster/instance', './RegCenter/Cluster/Instance', 'registration:cluster:instance', 'ReconciliationOutlined', 'C', 0, 25, '2023-08-11 14:06:55', '2023-09-26 14:54:29', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (29, 12, '告警组', '/registration/alert/group', './RegCenter/Alert/AlertGroup', 'registration:alert:group', 'AlertOutlined', 'C', 0, 48, '2023-08-11 14:06:55', '2023-09-26 15:02:23', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (30, 9, '集群配置', '/registration/cluster/config', './RegCenter/Cluster/Configuration', 'registration:cluster:config', 'SettingOutlined', 'C', 0, 31, '2023-08-11 14:06:55', '2023-09-26 14:57:57', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (31, 12, '告警实例', '/registration/alert/instance', './RegCenter/Alert/AlertInstance', 'registration:alert:instance', 'AlertFilled', 'C', 0, 44, '2023-08-11 14:06:55', '2023-09-26 15:01:42', null); --- insert into public.dinky_sys_menu +-- insert into ${dinky_schema}.dinky_sys_menu -- values (32, 1, '作业监控', '/home/jobOverView', 'JobOverView', 'home:jobOverView', 'AntCloudOutlined', 'F', 0, 2, -- '2023-08-15 16:52:59', '2023-09-26 14:48:50', null); --- insert into public.dinky_sys_menu +-- insert into ${dinky_schema}.dinky_sys_menu -- values (33, 1, '数据开发', '/home/devOverView', 'DevOverView', 'home:devOverView', 'AimOutlined', 'F', 0, 3, -- '2023-08-15 16:54:47', '2023-09-26 14:49:00', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (34, 5, '项目列表', '/datastudio/left/project', null, 'datastudio:left:project', 'ConsoleSqlOutlined', 'F', 0, 5, '2023-09-01 18:00:39', '2023-09-26 14:49:31', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (35, 5, '数据源', '/datastudio/left/datasource', null, 'datastudio:left:datasource', 'TableOutlined', 'F', 0, 7, '2023-09-01 18:01:09', '2023-09-26 14:49:42', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (36, 5, 'Catalog', '/datastudio/left/catalog', null, 'datastudio:left:catalog', 'DatabaseOutlined', 'F', 0, 6, '2023-09-01 18:01:30', '2024-01-18 22:29:41', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (37, 5, '作业配置', '/datastudio/right/jobConfig', null, 'datastudio:right:jobConfig', 'SettingOutlined', 'F', 0, 8, '2023-09-01 18:02:15', '2023-09-26 14:50:24', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (38, 5, '预览配置', '/datastudio/right/previewConfig', null, 'datastudio:right:previewConfig', 'InsertRowRightOutlined', 'F', 0, 9, '2023-09-01 18:03:08', '2023-09-26 14:50:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (39, 5, '版本历史', '/datastudio/right/historyVision', null, 'datastudio:right:historyVision', 'HistoryOutlined', 'F', 0, 10, '2023-09-01 18:03:29', '2023-09-26 14:51:03', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (40, 5, '保存点', '/datastudio/right/savePoint', null, 'datastudio:right:savePoint', 'FolderOutlined', 'F', 0, 11, '2023-09-01 18:03:58', '2023-09-26 14:51:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (41, 5, '作业信息', '/datastudio/right/jobInfo', null, 'datastudio:right:jobInfo', 'InfoCircleOutlined', 'F', 0, 8, '2023-09-01 18:04:31', '2023-09-25 18:26:45', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (42, 5, '控制台', '/datastudio/bottom/console', null, 'datastudio:bottom:console', 'ConsoleSqlOutlined', 'F', 0, 12, '2023-09-01 18:04:56', '2023-09-26 14:51:24', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (43, 5, '结果', '/datastudio/bottom/result', null, 'datastudio:bottom:result', 'SearchOutlined', 'F', 0, 13, '2023-09-01 18:05:16', '2023-09-26 14:51:36', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (45, 5, '血缘', '/datastudio/bottom/lineage', null, 'datastudio:bottom:lineage', 'PushpinOutlined', 'F', 0, 15, '2023-09-01 18:07:15', '2023-09-26 14:52:00', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (46, 5, '表数据监控', '/datastudio/bottom/table-data', null, 'datastudio:bottom:table-data','TableOutlined', 'F', 0, 16, '2023-09-01 18:07:55', '2023-09-26 14:52:38', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (47, 5, '小工具', '/datastudio/bottom/tool', null, 'datastudio:bottom:tool', 'ToolOutlined', 'F', 0, 17, '2023-09-01 18:08:18', '2023-09-26 14:53:04', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (48, 28, '新建', '/registration/cluster/instance/add', null, 'registration:cluster:instance:add', 'PlusOutlined', 'F', 0, 26, '2023-09-06 08:56:45', '2023-09-26 14:56:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (50, 28, '编辑', '/registration/cluster/instance/edit', null, 'registration:cluster:instance:edit', 'EditOutlined', 'F', 0, 27, '2023-09-06 08:56:45', '2023-09-26 14:56:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (51, 28, '删除', '/registration/cluster/instance/delete', null, 'registration:cluster:instance:delete', 'DeleteOutlined', 'F', 0, 28, '2023-09-06 08:57:30', '2023-09-26 14:56:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (52, 30, '新建', '/registration/cluster/config/add', null, 'registration:cluster:config:add', 'PlusOutlined', 'F', 0, 32, '2023-09-06 09:00:31', '2023-09-26 14:58:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (53, 30, '编辑', '/registration/cluster/config/edit', null, 'registration:cluster:config:edit', 'EditOutlined', 'F', 0, 33, '2023-09-06 08:56:45', '2023-09-26 14:58:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (54, 30, '删除', '/registration/cluster/config/delete', null, 'registration:cluster:config:delete', 'DeleteOutlined', 'F', 0, 34, '2023-09-06 08:57:30', '2023-09-26 14:58:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (55, 149, '新建', '/registration/datasource/list/add', null, 'registration:datasource:list:add', 'PlusOutlined', 'F', 0, 38, '2023-09-06 09:01:05', '2024-01-18 22:08:51', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (56, 149, '编辑', '/registration/datasource/list/edit', null, 'registration:datasource:list:edit', 'EditOutlined', 'F', 0, 39, '2023-09-06 08:56:45', '2024-01-18 22:09:01', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (57, 149, '删除', '/registration/datasource/list/delete', null, 'registration:datasource:list:delete', 'DeleteOutlined', 'F', 0, 40, '2023-09-06 08:57:30', '2024-01-18 22:09:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (58, 31, '新建', '/registration/alert/instance/add', null, 'registration:alert:instance:add', 'PlusOutlined', 'F', 0, 46, '2023-09-06 09:01:05', '2023-09-26 15:02:04', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (59, 31, '编辑', '/registration/alert/instance/edit', null, 'registration:alert:instance:edit', 'EditOutlined', 'F', 0, 45, '2023-09-06 08:56:45', '2023-09-26 15:01:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (60, 31, '删除', '/registration/alert/instance/delete', null, 'registration:alert:instance:delete', 'DeleteOutlined', 'F', 0, 47, '2023-09-06 08:57:30', '2023-09-26 15:02:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (61, 29, '新建', '/registration/alert/group/add', null, 'registration:alert:group:add', 'PlusOutlined', 'F', 0, 49, '2023-09-06 09:01:05', '2023-09-26 15:02:48', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (62, 29, '编辑', '/registration/alert/group/edit', null, 'registration:alert:group:edit', 'EditOutlined', 'F', 0, 49, '2023-09-06 08:56:45', '2023-09-26 15:02:36', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (63, 29, '删除', '/registration/alert/group/delete', null, 'registration:alert:group:delete', 'DeleteOutlined', 'F', 0, 50, '2023-09-06 08:57:30', '2023-09-26 15:03:01', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (64, 13, '新建', '/registration/document/add', null, 'registration:document:add', 'PlusOutlined', 'F', 0, 57, '2023-09-06 09:01:05', '2023-09-26 15:04:22', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (65, 13, '编辑', '/registration/document/edit', null, 'registration:document:edit', 'EditOutlined', 'F', 0, 56, '2023-09-06 08:56:45', '2023-09-26 15:04:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (66, 13, '删除', '/registration/document/delete', null, 'registration:document:delete', 'DeleteOutlined', 'F', 0, 58, '2023-09-06 08:57:30', '2023-09-26 15:04:32', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (68, 14, '新建', '/registration/fragment/add', null, 'registration:fragment:add', 'PlusOutlined', 'F', 0, 61, '2023-09-06 09:01:05', '2023-09-26 15:05:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (69, 14, '编辑', '/registration/fragment/edit', null, 'registration:fragment:edit', 'EditOutlined', 'F', 0, 60, '2023-09-06 08:56:45', '2023-09-26 15:05:04', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (70, 14, '删除', '/registration/fragment/delete', null, 'registration:fragment:delete', 'DeleteOutlined', 'F', 0, 62, '2023-09-06 08:57:30', '2023-09-26 15:05:21', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (72, 15, '新建', '/registration/gitproject/add', null, 'registration:gitproject:add', 'PlusOutlined', 'F', 0, 65, '2023-09-06 09:01:05', '2023-09-26 15:06:01', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (73, 15, '编辑', '/registration/gitproject/edit', null, 'registration:gitproject:edit', 'EditOutlined', 'F', 0, 64, '2023-09-06 08:56:45', '2023-09-26 15:05:52', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (74, 15, '删除', '/registration/gitproject/delete', null, 'registration:gitproject:delete', 'DeleteOutlined', 'F', 0, 66, '2023-09-06 08:57:30', '2023-09-26 15:06:09', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (76, 15, '构建', '/registration/gitproject/build', null, 'registration:gitproject:build', 'PlaySquareOutlined', 'F', 0, 67, '2023-09-06 08:57:30', '2023-09-26 15:06:17', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (77, 15, '查看日志', '/registration/gitproject/showLog', null, 'registration:gitproject:showLog', 'SearchOutlined', 'F', 0, 68, '2023-09-06 08:57:30', '2023-09-26 15:06:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (78, 16, '新建', '/registration/udf/template/add', null, 'registration:udf:template:add', 'PlusOutlined', 'F', 0, 71, '2023-09-06 09:01:05', '2023-09-26 15:07:04', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (79, 16, '编辑', '/registration/udf/template/edit', null, 'registration:udf:template:edit', 'EditOutlined', 'F', 0, 70, '2023-09-06 08:56:45', '2023-09-26 15:06:48', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (80, 16, '删除', '/registration/udf/template/delete', null, 'registration:udf:template:delete', 'DeleteOutlined', 'F', 0, 72, '2023-09-06 08:57:30', '2023-09-26 15:07:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (82, 19, '上传', '/registration/resource/upload', null, 'registration:resource:upload', 'PlusOutlined', 'F', 0, 77, '2023-09-06 09:01:05', '2023-09-26 15:08:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (83, 19, '重命名', '/registration/resource/rename', null, 'registration:resource:rename', 'EditOutlined', 'F', 0, 75, '2023-09-06 08:56:45', '2023-09-26 15:07:45', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (84, 19, '删除', '/registration/resource/delete', null, 'registration:resource:delete', 'DeleteOutlined', 'F', 0, 76, '2023-09-06 08:57:30', '2023-09-26 15:07:54', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (85, 19, '创建文件夹', '/registration/resource/addFolder', null, 'registration:resource:addFolder', 'PlusOutlined', 'F', 0, 74, '2023-09-06 08:57:30', '2023-09-26 15:07:37', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (86, 4, 'Token 令牌', '/auth/token', './AuthCenter/Token', 'auth:token', 'SecurityScanFilled', 'C', 0, 111, '2023-09-05 23:14:23', '2023-09-26 15:15:22', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (87, 21, '添加', '/auth/user/add', null, 'auth:user:add', 'PlusOutlined', 'F', 0, 81, '2023-09-22 22:06:52', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (88, 21, '重置密码', '/auth/user/reset', null, 'auth:user:reset', 'RollbackOutlined', 'F', 0, 84, '2023-09-22 22:08:17', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (89, 21, '恢复用户', '/auth/user/recovery', null, 'auth:user:recovery', 'RadiusSettingOutlined', 'F', 0, 85, '2023-09-22 22:08:53', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (90, 21, '删除', '/auth/user/delete', null, 'auth:user:delete', 'DeleteOutlined', 'F', 0, 83, '2023-09-22 22:09:29', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (91, 21, '修改密码', '/auth/user/changePassword', null, 'auth:user:changePassword', 'EditOutlined', 'F', 0, 86, '2023-09-22 22:10:01', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (92, 21, '分配角色', '/auth/user/assignRole', null, 'auth:user:assignRole', 'ForwardOutlined', 'F', 0, 87, '2023-09-22 22:10:31', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (93, 21, '编辑', '/auth/user/edit', null, 'auth:user:edit', 'EditOutlined', 'F', 0, 82, '2023-09-22 22:11:41', '2023-09-26 15:09:49', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (94, 20, '添加', '/auth/role/add', null, 'auth:role:add', 'PlusOutlined', 'F', 0, 89, '2023-09-22 22:06:52', '2023-09-26 15:11:10', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (95, 20, '删除', '/auth/role/delete', null, 'auth:role:delete', 'DeleteOutlined', 'F', 0, 91, '2023-09-22 22:09:29', '2023-09-26 15:11:10', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (96, 20, '分配菜单', '/auth/role/assignMenu', null, 'auth:role:assignMenu', 'AntDesignOutlined', 'F', 0, 92, '2023-09-22 22:10:31', '2023-09-26 15:11:10', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (97, 20, '编辑', '/auth/role/edit', null, 'auth:role:edit', 'EditOutlined', 'F', 0, 90, '2023-09-22 22:11:41', '2023-09-26 15:11:10', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (98, 20, '查看用户列表', '/auth/role/viewUser', null, 'auth:role:viewUser', 'FundViewOutlined', 'F', 0, 93, '2023-09-22 22:11:41', '2023-09-26 15:11:10', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (99, 86, '添加 Token', '/auth/token/add', null, 'auth:token:add', 'PlusOutlined', 'F', 0, 112, '2023-09-22 22:11:41', '2023-09-26 15:15:46', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (100, 86, '删除 Token', '/auth/token/delete', null, 'auth:token:delete', 'DeleteOutlined', 'F', 0, 114, '2023-09-22 22:11:41', '2023-09-26 15:15:46', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (101, 86, '修改 Token', '/auth/token/edit', null, 'auth:token:edit', 'EditOutlined', 'F', 0, 113, '2023-09-22 22:11:41', '2023-09-26 15:15:46', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (102, 27, '添加', '/auth/rowPermissions/add', null, 'auth:rowPermissions:add', 'PlusOutlined', 'F', 0, 101, '2023-09-22 22:11:41', '2023-09-26 15:13:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (103, 27, '编辑', '/auth/rowPermissions/edit', null, 'auth:rowPermissions:edit', 'EditOutlined', 'F', 0, 102, '2023-09-22 22:11:41', '2023-09-26 15:13:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (104, 27, '删除', '/auth/rowPermissions/delete', null, 'auth:rowPermissions:delete', 'DeleteOutlined', 'F', 0, 103, '2023-09-22 22:11:41', '2023-09-26 15:13:12', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (105, 23, '添加', '/auth/tenant/add', null, 'auth:tenant:add', 'PlusOutlined', 'F', 0, 105, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (106, 23, '编辑', '/auth/tenant/edit', null, 'auth:tenant:edit', 'EditOutlined', 'F', 0, 106, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (107, 23, '删除', '/auth/tenant/delete', null, 'auth:tenant:delete', 'DeleteOutlined', 'F', 0, 107, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (108, 23, '分配用户', '/auth/tenant/assignUser', null, 'auth:tenant:assignUser', 'EuroOutlined', 'F', 0, 108, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (109, 23, '查看用户', '/auth/tenant/viewUser', null, 'auth:tenant:viewUser', 'FundViewOutlined', 'F', 0, 109, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (110, 23, '设置/取消租户管理员', '/auth/tenant/modifyTenantManager', null, 'auth:tenant:modifyTenantManager', 'ExclamationCircleOutlined', 'F', 0, 110, '2023-09-22 22:11:41', '2023-09-26 15:15:02', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (111, 22, '创建根菜单', '/auth/menu/createRoot', null, 'auth:menu:createRoot', 'FolderAddOutlined', 'F', 0, 95, '2023-09-22 22:11:41', '2023-09-26 15:12:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (112, 22, '刷新', '/auth/menu/refresh', null, 'auth:menu:refresh', 'ReloadOutlined', 'F', 0, 97, '2023-09-22 22:11:41', '2023-09-26 15:12:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (113, 22, '编辑', '/auth/menu/edit', null, 'auth:menu:edit', 'EditOutlined', 'F', 0, 98, '2023-09-22 22:11:41', '2023-09-26 15:12:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (114, 22, '添加子项', '/auth/menu/addSub', null, 'auth:menu:addSub', 'PlusOutlined', 'F', 0, 96, '2023-09-22 22:11:41', '2023-09-26 15:12:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (115, 22, '删除', '/auth/menu/delete', null, 'auth:menu:delete', 'DeleteOutlined', 'F', 0, 99, '2023-09-22 22:11:41', '2023-09-26 15:12:26', null); -insert into public.dinky_sys_menu values (116, 6, '告警策略', '/settings/alertrule', './SettingCenter/AlertRule', 'settings:alertrule', 'AndroidOutlined', 'C', 0, 136, '2023-09-22 23:31:10', '2023-09-26 15:19:52', null); -insert into public.dinky_sys_menu values (117, 116, '添加', '/settings/alertrule/add', null, 'settings:alertrule:add', 'PlusOutlined', 'F', 0, 137, '2023-09-22 23:34:51', '2023-09-26 15:20:03', null); -insert into public.dinky_sys_menu values (118, 116, '删除', '/settings/alertrule/delete', null, 'settings:alertrule:delete', 'DeleteOutlined', 'F', 0, 139, '2023-09-22 23:35:20', '2023-09-26 15:20:21', null); -insert into public.dinky_sys_menu values (119, 116, '编辑', '/settings/alertrule/edit', null, 'settings:alertrule:edit', 'EditOutlined', 'F', 0, 138, '2023-09-22 23:36:32', '2023-09-26 15:20:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (116, 6, '告警策略', '/settings/alertrule', './SettingCenter/AlertRule', 'settings:alertrule', 'AndroidOutlined', 'C', 0, 136, '2023-09-22 23:31:10', '2023-09-26 15:19:52', null); +insert into ${dinky_schema}.dinky_sys_menu values (117, 116, '添加', '/settings/alertrule/add', null, 'settings:alertrule:add', 'PlusOutlined', 'F', 0, 137, '2023-09-22 23:34:51', '2023-09-26 15:20:03', null); +insert into ${dinky_schema}.dinky_sys_menu values (118, 116, '删除', '/settings/alertrule/delete', null, 'settings:alertrule:delete', 'DeleteOutlined', 'F', 0, 139, '2023-09-22 23:35:20', '2023-09-26 15:20:21', null); +insert into ${dinky_schema}.dinky_sys_menu values (119, 116, '编辑', '/settings/alertrule/edit', null, 'settings:alertrule:edit', 'EditOutlined', 'F', 0, 138, '2023-09-22 23:36:32', '2023-09-26 15:20:13', null); +insert into ${dinky_schema}.dinky_sys_menu values (120, 8, 'Dinky 服务监控', '/metrics/server', './Metrics/Server', 'metrics:server', 'DashboardOutlined', 'F', 0, 141, '2023-09-22 23:37:43', '2023-09-26 15:21:00', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (121, 8, 'Flink 任务监控', '/metrics/job', './Metrics/Job', 'metrics:job', 'DashboardTwoTone', 'C', 0, 142, '2023-09-22 23:38:34', '2023-09-26 15:21:08', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (122, 24, 'Dinky 环境配置', '/settings/globalsetting/dinky', null, 'settings:globalsetting:dinky', 'SettingOutlined', 'F', 0, 117, '2023-09-22 23:40:30', '2023-09-26 15:16:20', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (123, 24, 'Flink 环境配置', '/settings/globalsetting/flink', null, 'settings:globalsetting:flink', 'SettingOutlined', 'F', 0, 119, '2023-09-22 23:40:30', '2023-09-26 15:16:40', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (124, 24, 'Maven 配置', '/settings/globalsetting/maven', null, 'settings:globalsetting:maven', 'SettingOutlined', 'F', 0, 121, '2023-09-22 23:40:30', '2023-09-26 15:17:04', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (125, 24, 'DolphinScheduler 配置', '/settings/globalsetting/ds', null, 'settings:globalsetting:ds', 'SettingOutlined', 'F', 0, 123, '2023-09-22 23:40:30', '2023-09-26 15:17:23', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (126, 24, 'LDAP 配置', '/settings/globalsetting/ldap', null, 'settings:globalsetting:ldap', 'SettingOutlined', 'F', 0, 125, '2023-09-22 23:40:30', '2023-09-26 15:17:41', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (127, 24, 'Metrics 配置', '/settings/globalsetting/metrics', null, 'settings:globalsetting:metrics', 'SettingOutlined', 'F', 0, 127, '2023-09-22 23:40:30', '2023-09-26 15:18:06', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (128, 24, 'Resource 配置', '/settings/globalsetting/resource', null, 'settings:globalsetting:resource', 'SettingOutlined', 'F', 0, 129, '2023-09-22 23:40:30', '2023-09-26 15:18:27', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (129, 122, '编辑', '/settings/globalsetting/dinky/edit', null, 'settings:globalsetting:dinky:edit', 'EditOutlined', 'F', 0, 118, '2023-09-22 23:44:18', '2023-09-26 15:16:29', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (130, 123, '编辑', '/settings/globalsetting/flink/edit', null, 'settings:globalsetting:flink:edit', 'EditOutlined', 'F', 0, 120, '2023-09-22 23:44:18', '2023-09-26 15:16:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (131, 124, '编辑', '/settings/globalsetting/maven/edit', null, 'settings:globalsetting:maven:edit', 'EditOutlined', 'F', 0, 122, '2023-09-22 23:44:18', '2023-09-26 15:17:13', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (132, 125, '编辑', '/settings/globalsetting/ds/edit', null, 'settings:globalsetting:ds:edit', 'EditOutlined', 'F', 0, 124, '2023-09-22 23:44:18', '2023-09-26 15:17:32', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (133, 126, '编辑', '/settings/globalsetting/ldap/edit', null, 'settings:globalsetting:ldap:edit', 'EditOutlined', 'F', 0, 126, '2023-09-22 23:44:18', '2023-09-26 15:17:51', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (134, 127, '编辑', '/settings/globalsetting/metrics/edit', null, 'settings:globalsetting:metrics:edit', 'EditOutlined', 'F', 0, 128, '2023-09-22 23:44:18', '2023-09-26 15:18:16', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (135, 128, '编辑', '/settings/globalsetting/resource/edit', null, 'settings:globalsetting:resource:edit', 'EditOutlined', 'F', 0, 130, '2023-09-22 23:44:18', '2023-09-26 15:18:39', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (136, 12, '告警模版', '/registration/alert/template', './RegCenter/Alert/AlertTemplate', 'registration:alert:template', 'AlertOutlined', 'C', 0, 51, '2023-09-23 21:34:43', '2023-09-26 15:03:14', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (137, 136, '添加', '/registration/alert/template/add', null, 'registration:alert:template:add', 'PlusOutlined', 'F', 0, 52, '2023-09-23 21:36:37', '2023-09-26 15:03:22', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (138, 136, '编辑', '/registration/alert/template/edit', null, 'registration:alert:template:edit', 'EditOutlined', 'F', 0, 53, '2023-09-23 21:37:00', '2023-09-26 15:03:30', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (139, 136, '删除', '/registration/alert/template/delete', null, 'registration:alert:template:delete', 'DeleteOutlined', 'F', 0, 54, '2023-09-23 21:37:43', '2023-09-26 15:03:37', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (140, 25, '系统日志', '/settings/systemlog/rootlog', null, 'settings:systemlog:rootlog', 'BankOutlined', 'F', 0, 133, '2023-09-23 21:43:57', '2023-09-26 15:19:14', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (141, 25, '日志列表', '/settings/systemlog/loglist', null, 'settings:systemlog:loglist', 'BankOutlined', 'F', 0, 134, '2023-09-23 21:45:05', '2023-09-26 15:19:23', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (142, 30, '部署 Session 集群', '/registration/cluster/config/deploy', null, 'registration:cluster:config:deploy', 'PlayCircleOutlined', 'F', 0, 35, '2023-09-26 13:42:55', '2023-09-26 14:58:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (143, 30, ' 心跳检测', '/registration/cluster/config/heartbeat', null, 'registration:cluster:config:heartbeat', 'HeartOutlined', 'F', 0, 36, '2023-09-26 13:44:23', '2023-09-26 14:58:50', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (144, 28, '心跳检测', '/registration/cluster/instance/heartbeat', null, 'registration:cluster:instance:heartbeat', 'HeartOutlined', 'F', 0, 30, '2023-09-26 13:51:04', '2023-09-26 14:57:42', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (145, 149, '心跳检测', '/registration/datasource/list/heartbeat', null, 'registration:datasource:list:heartbeat', 'HeartOutlined', 'F', 0, 41, '2023-09-26 14:00:06', '2024-01-18 22:09:26', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (146, 149, ' 拷贝', '/registration/datasource/list/copy', null, 'registration:datasource:list:copy', 'CopyOutlined', 'F', 0, 42, '2023-09-26 14:02:28', '2024-01-18 22:09:41', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (147, 28, '停止 Flink 实例', '/registration/cluster/instance/kill', null, 'registration:cluster:instance:kill', 'StopTwoTone', 'F', 0, 145, '2024-01-03 11:08:39', '2024-01-03 11:08:39', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (148, 5, '全局变量', '/datastudio/left/globalVariable', '', 'datastudio:left:globalVariable', 'CloudServerOutlined', 'F', 0, 146, '2024-01-12 21:58:35', '2024-01-12 21:58:35', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (149, 10, '数据源列表', '/registration/datasource/list', './RegCenter/DataSource', 'registration:datasource:list', 'OrderedListOutlined', 'C', 0, 147, '2024-01-18 21:41:04', '2024-01-18 21:42:37', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (150, 10, '数据源详情', '/registration/datasource/detail', './RegCenter/DataSource/components/DataSourceDetail', 'registration:datasource:detail', 'InfoCircleOutlined', 'C', 0, 148, '2024-01-18 21:43:35', '2024-01-18 21:43:35', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (151, 150, '数据源详情列表树', '/registration/datasource/detail/tree', null, 'registration:datasource:detail:tree', 'ControlOutlined', 'F', 0, 149, '2024-01-18 21:50:06', '2024-01-18 21:50:06', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (152, 150, '描述', '/registration/datasource/detail/desc', null, 'registration:datasource:detail:desc', 'SortDescendingOutlined', 'F', 0, 150, '2024-01-18 21:51:02', '2024-01-18 22:10:11', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (153, 150, '查询', '/registration/datasource/detail/query', null, 'registration:datasource:detail:query', 'SearchOutlined', 'F', 0, 151, '2024-01-18 21:51:41', '2024-01-18 22:10:21', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (154, 150, '生成 SQL', '/registration/datasource/detail/gensql', null, 'registration:datasource:detail:gensql', 'ConsoleSqlOutlined', 'F', 0, 152, '2024-01-18 21:52:06', '2024-01-18 22:10:29', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (155, 150, ' 控制台', '/registration/datasource/detail/console', null, 'registration:datasource:detail:console', 'ConsoleSqlOutlined', 'F', 0, 153, '2024-01-18 21:52:47', '2024-01-18 22:10:37', null); -insert into public.dinky_sys_menu +insert into ${dinky_schema}.dinky_sys_menu values (156, 150, ' 刷新', '/registration/datasource/detail/refresh', null, 'registration:datasource:detail:refresh', 'ReloadOutlined', 'F', 0, 154, '2024-01-18 22:13:47', '2024-01-18 22:13:47', null); -- ---------------------------- --- Table structure for public.dinky_sys_role_menu +-- Table structure for ${dinky_schema}.dinky_sys_role_menu -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_sys_role_menu +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_role_menu ( id BIGSERIAL PRIMARY KEY NOT NULL, role_id BIGINT NOT NULL, @@ -3903,25 +3903,25 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_role_menu update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP ); -CREATE UNIQUE INDEX IF NOT EXISTS un_role_menu_inx ON public.dinky_sys_role_menu (role_id, menu_id); +CREATE UNIQUE INDEX IF NOT EXISTS un_role_menu_inx ON ${dinky_schema}.dinky_sys_role_menu (role_id, menu_id); -COMMENT ON COLUMN public.dinky_sys_role_menu.id IS 'id'; -COMMENT ON COLUMN public.dinky_sys_role_menu.role_id IS 'role id'; -COMMENT ON COLUMN public.dinky_sys_role_menu.menu_id IS 'menu id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_role_menu.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_role_menu.role_id IS 'role id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_role_menu.menu_id IS 'menu id'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_sys_role_menu BEFORE UPDATE - ON public.dinky_sys_role_menu + ON ${dinky_schema}.dinky_sys_role_menu FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_alert_template +-- Table structure for ${dinky_schema}.dinky_alert_template -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_template +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_template ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(20), @@ -3933,23 +3933,23 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_template updater INT ); -COMMENT ON COLUMN public.dinky_alert_template.id IS 'id'; -COMMENT ON COLUMN public.dinky_alert_template.name IS 'emplate name'; -COMMENT ON COLUMN public.dinky_alert_template.template_content IS 'template content'; -COMMENT ON COLUMN public.dinky_alert_template.enabled IS 'is enable'; --- public.dinky_git_project +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template.name IS 'emplate name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template.template_content IS 'template content'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template.enabled IS 'is enable'; +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_alert_template BEFORE UPDATE - ON public.dinky_alert_template + ON ${dinky_schema}.dinky_alert_template FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_alert_rules +-- Table structure for ${dinky_schema}.dinky_alert_rules -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_rules +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_rules ( id SERIAL PRIMARY KEY, name VARCHAR(40) NOT NULL, @@ -3964,27 +3964,27 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_rules creator INT, updater INT ); -CREATE UNIQUE INDEX IF NOT EXISTS dinky_alert_rules_name ON public.dinky_alert_rules (name); +CREATE UNIQUE INDEX IF NOT EXISTS dinky_alert_rules_name ON ${dinky_schema}.dinky_alert_rules (name); -COMMENT ON COLUMN public.dinky_alert_rules.id IS 'id'; -COMMENT ON COLUMN public.dinky_alert_rules.name IS 'rule name'; -COMMENT ON COLUMN public.dinky_alert_rules.rule IS 'specify rule'; -COMMENT ON COLUMN public.dinky_alert_rules.template_id IS 'template id'; -COMMENT ON COLUMN public.dinky_alert_rules.rule_type IS 'alert rule type'; -COMMENT ON COLUMN public.dinky_alert_rules.trigger_conditions IS 'trigger conditions'; -COMMENT ON COLUMN public.dinky_alert_rules.description IS 'description'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.name IS 'rule name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.rule IS 'specify rule'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.template_id IS 'template id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.rule_type IS 'alert rule type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.trigger_conditions IS 'trigger conditions'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules.description IS 'description'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_alert_rules BEFORE UPDATE - ON public.dinky_alert_rules + ON ${dinky_schema}.dinky_alert_rules FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_udf_manage +-- Table structure for ${dinky_schema}.dinky_udf_manage -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_udf_manage +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_udf_manage ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(50), @@ -3997,26 +3997,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_udf_manage creator INT, updater INT ); -CREATE INDEX IF NOT EXISTS name_resources_id_idx ON public.dinky_udf_manage (name, resources_id); +CREATE INDEX IF NOT EXISTS name_resources_id_idx ON ${dinky_schema}.dinky_udf_manage (name, resources_id); -COMMENT ON COLUMN public.dinky_udf_manage.id IS 'id'; -COMMENT ON COLUMN public.dinky_udf_manage.name IS 'udf name'; -COMMENT ON COLUMN public.dinky_udf_manage.class_name IS 'Complete class name'; -COMMENT ON COLUMN public.dinky_udf_manage.task_id IS 'task_id'; -COMMENT ON COLUMN public.dinky_udf_manage.resources_id IS 'resources_id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage.name IS 'udf name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage.class_name IS 'Complete class name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage.task_id IS 'task_id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage.resources_id IS 'resources_id'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_udf_manage BEFORE UPDATE - ON public.dinky_udf_manage + ON ${dinky_schema}.dinky_udf_manage FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -- ---------------------------- --- Table structure for public.dinky_sys_token +-- Table structure for ${dinky_schema}.dinky_sys_token -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_sys_token +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_sys_token ( id BIGSERIAL PRIMARY KEY, token_value VARCHAR(255) NOT NULL, @@ -4032,53 +4032,53 @@ CREATE TABLE IF NOT EXISTS public.dinky_sys_token creator BIGINT, updater BIGINT ); -CREATE UNIQUE INDEX IF NOT EXISTS token_value_idx ON public.dinky_sys_token (token_value); -CREATE INDEX IF NOT EXISTS source_idx ON public.dinky_sys_token USING HASH (source); - -COMMENT ON COLUMN public.dinky_sys_token.id IS 'id'; -COMMENT ON COLUMN public.dinky_sys_token.token_value IS 'token value'; -COMMENT ON COLUMN public.dinky_sys_token.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_sys_token.role_id IS 'role id'; -COMMENT ON COLUMN public.dinky_sys_token.tenant_id IS 'tenant id'; -COMMENT ON COLUMN public.dinky_sys_token.expire_type IS '1: never expire, 2: expire after a period of time, 3: expire at a certain time'; -COMMENT ON COLUMN public.dinky_sys_token.expire_start_time IS 'expire start time ,when expire_type = 3 , it is the start time of the period'; -COMMENT ON COLUMN public.dinky_sys_token.expire_end_time IS 'expire end time ,when expire_type = 2,3 , it is the end time of the period'; -COMMENT ON COLUMN public.dinky_sys_token.source IS '1:login 2:custom'; - --- public.dinky_git_project +CREATE UNIQUE INDEX IF NOT EXISTS token_value_idx ON ${dinky_schema}.dinky_sys_token (token_value); +CREATE INDEX IF NOT EXISTS source_idx ON ${dinky_schema}.dinky_sys_token USING HASH (source); + +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.token_value IS 'token value'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.role_id IS 'role id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.tenant_id IS 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.expire_type IS '1: never expire, 2: expire after a period of time, 3: expire at a certain time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.expire_start_time IS 'expire start time ,when expire_type = 3 , it is the start time of the period'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.expire_end_time IS 'expire end time ,when expire_type = 2,3 , it is the end time of the period'; +COMMENT ON COLUMN ${dinky_schema}.dinky_sys_token.source IS '1:login 2:custom'; + +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_sys_token BEFORE UPDATE - ON public.dinky_sys_token + ON ${dinky_schema}.dinky_sys_token FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO ${dinky_schema}.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (3, 'alert.rule.jobFail', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''FAILED''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO ${dinky_schema}.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (4, 'alert.rule.getJobInfoFail', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''UNKNOWN''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO ${dinky_schema}.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (5, 'alert.rule.jobRestart', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''RESTARTING''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO ${dinky_schema}.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (6, 'alert.rule.checkpointFail', '[{"ruleKey":"isCheckpointFailed","ruleOperator":"EQ","ruleValue":"true"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO ${dinky_schema}.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (7, 'alert.rule.jobRunException', '[{"ruleKey":"isException","ruleOperator":"EQ","ruleValue":"true"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_template +INSERT INTO ${dinky_schema}.dinky_alert_template VALUES (1, 'Default', ' - **Job Name :** ${jobName} - **Job Status :** ${jobStatus} diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20240708.1.1.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20240708.1.1.0__release.sql index 8f47b01eea..3e033300a5 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20240708.1.1.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20240708.1.1.0__release.sql @@ -81,7 +81,7 @@ $$ LANGUAGE plpgsql; -update public.dinky_sys_menu +update ${dinky_schema}.dinky_sys_menu set "path"='/registration/alert/rule', "component"='./RegCenter/Alert/AlertRule', "perms"='registration:alert:rule', @@ -93,12 +93,12 @@ set "path"='/registration/alert/rule/add', "perms"='registration:alert:rule:add' where "id" = 117; -update public.dinky_sys_menu +update ${dinky_schema}.dinky_sys_menu set "path"='/registration/alert/rule/delete', "perms"='registration:alert:rule:delete' where "id" = 118; -update public.dinky_sys_menu +update ${dinky_schema}.dinky_sys_menu set "path"='/registration/alert/rule/edit', "perms"='registration:alert:rule:edit' where "id" = 119; @@ -106,21 +106,21 @@ where "id" = 119; -- Increase class_name column's length from 50 to 100. -ALTER TABLE public.dinky_udf_manage ALTER COLUMN class_name TYPE VARCHAR(100); -COMMENT ON COLUMN public.dinky_udf_manage."class_name" IS 'Complete class name'; +ALTER TABLE ${dinky_schema}.dinky_udf_manage ALTER COLUMN class_name TYPE VARCHAR(100); +COMMENT ON COLUMN ${dinky_schema}.dinky_udf_manage."class_name" IS 'Complete class name'; -SELECT add_column_if_not_exists('public','dinky_task', 'first_level_owner', 'int', 'null', 'primary responsible person id'); -SELECT add_column_if_not_exists('public','dinky_task', 'second_level_owners', 'varchar(128)', 'null', 'list of secondary responsible persons ids'); +SELECT add_column_if_not_exists('${dinky_schema}','dinky_task', 'first_level_owner', 'int', 'null', 'primary responsible person id'); +SELECT add_column_if_not_exists('${dinky_schema}','dinky_task', 'second_level_owners', 'varchar(128)', 'null', 'list of secondary responsible persons ids'); -update public.dinky_task set "first_level_owner" = "creator"; +update ${dinky_schema}.dinky_task set "first_level_owner" = "creator"; -UPDATE public.dinky_user SET "password" = 'f4b3a484ee745b98d64cd69c429b2aa2' WHERE "id" =1 and "password"= '21232f297a57a5a743894a0e4a801fc3'; +UPDATE ${dinky_schema}.dinky_user SET "password" = 'f4b3a484ee745b98d64cd69c429b2aa2' WHERE "id" =1 and "password"= '21232f297a57a5a743894a0e4a801fc3'; -ALTER TABLE public.dinky_resources ALTER COLUMN file_name TYPE TEXT; +ALTER TABLE ${dinky_schema}.dinky_resources ALTER COLUMN file_name TYPE TEXT; -SELECT add_column_if_not_exists('public','dinky_udf_manage', 'language', 'varchar(10)', 'null', 'udf language'); +SELECT add_column_if_not_exists('${dinky_schema}','dinky_udf_manage', 'language', 'varchar(10)', 'null', 'udf language'); UPDATE dinky_udf_manage duml diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20240729.1.1.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20240729.1.1.0__release.sql index 64bfa0b9f2..7977cbd424 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20240729.1.1.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20240729.1.1.0__release.sql @@ -1,39 +1,39 @@ -INSERT INTO public.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, +INSERT INTO ${dinky_schema}.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (157, -1, '工作台', '/home', './Home', 'home', 'HomeOutlined', 'C', 0, 1, '2024-07-29 11:53:38', '2024-07-29 11:53:38', NULL); -INSERT INTO public.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, +INSERT INTO ${dinky_schema}.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (158 ,164, '仪表盘列表', '/dashboard/list', './Dashboard', 'dashboard:list', 'UnorderedListOutlined', 'F', 0, 167, '2024-07-29 15:37:46', '2024-07-29 15:37:46', NULL); -UPDATE public.dinky_sys_menu +UPDATE ${dinky_schema}.dinky_sys_menu SET path = '/dashboard/list/add', perms='dashboard:list:add' WHERE path = '/dashboard/add'; -UPDATE public.dinky_sys_menu +UPDATE ${dinky_schema}.dinky_sys_menu SET path = '/dashboard/list/edit', perms='dashboard:list:edit' WHERE path = '/dashboard/edit'; -UPDATE public.dinky_sys_menu +UPDATE ${dinky_schema}.dinky_sys_menu SET path = '/dashboard/list/delete', perms='dashboard:list:delete' WHERE path = '/dashboard/delete'; -UPDATE public.dinky_sys_menu +UPDATE ${dinky_schema}.dinky_sys_menu SET path = '/dashboard/list/view', perms='dashboard:list:view' WHERE path = '/dashboard/view'; -INSERT INTO public.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, +INSERT INTO ${dinky_schema}.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (159, 164, '看板布局', '/dashboard/dashboard-layout', './Dashboard/DashboardLayout', 'dashboard:dashboard-layout', 'DashboardOutlined', 'F', 0, 168, '2024-07-29 16:16:45', '2024-07-29 16:17:28', NULL); -INSERT INTO public.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, +INSERT INTO ${dinky_schema}.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (160, 164, '添加看板', '/dashboard/chart/add', NULL, 'dashboard:chart:add', 'AreaChartOutlined', 'F', 0, 167, '2024-06-21 10:53:33', '2024-06-21 10:53:33', NULL); -INSERT INTO public.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, +INSERT INTO ${dinky_schema}.dinky_sys_menu (id,parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (161, 164, '修改看板', '/dashboard/chart/edit', NULL, 'dashboard:chart:edit', 'BarChartOutlined', 'F', 0, 168, '2024-06-21 10:54:26', '2024-06-21 10:54:26', NULL); \ No newline at end of file diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20240827.1.2.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20240827.1.2.0__release.sql index 29396b2997..b65d0816a9 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20240827.1.2.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20240827.1.2.0__release.sql @@ -1,4 +1,4 @@ -CREATE OR REPLACE FUNCTION public.drop_index_if_exists( +CREATE OR REPLACE FUNCTION ${dinky_schema}.drop_index_if_exists( schema_name text, index_name text, table_name text @@ -23,10 +23,10 @@ END; $$ LANGUAGE plpgsql; -SELECT public.drop_index_if_exists('public', 'cluster_un_idx1', 'dinky_cluster'); +SELECT ${dinky_schema}.drop_index_if_exists('${dinky_schema}', 'cluster_un_idx1', 'dinky_cluster'); -CREATE TABLE IF NOT EXISTS public.dinky_dashboard +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_dashboard ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(255), @@ -37,18 +37,18 @@ CREATE TABLE IF NOT EXISTS public.dinky_dashboard update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON COLUMN public.dinky_dashboard.id IS 'ID'; -COMMENT ON COLUMN public.dinky_dashboard.name IS 'name'; -COMMENT ON COLUMN public.dinky_dashboard.remark IS 'remark'; -COMMENT ON COLUMN public.dinky_dashboard.chart_theme IS 'chart theme'; -COMMENT ON COLUMN public.dinky_dashboard.layouts IS 'layouts'; -COMMENT ON COLUMN public.dinky_dashboard.create_time IS 'create time'; -COMMENT ON COLUMN public.dinky_dashboard.update_time IS 'update time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.name IS 'name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.remark IS 'remark'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.chart_theme IS 'chart theme'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.layouts IS 'layouts'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.create_time IS 'create time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_dashboard.update_time IS 'update time'; CREATE OR REPLACE TRIGGER update_dinky_dashboard_update_time BEFORE UPDATE - ON public.dinky_dashboard + ON ${dinky_schema}.dinky_dashboard FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -SELECT add_column_if_not_exists('public','dinky_metrics', 'vertices_title', 'text', 'null', 'vertices title'); +SELECT add_column_if_not_exists('${dinky_schema}','dinky_metrics', 'vertices_title', 'text', 'null', 'vertices title'); diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20241203.1.2.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20241203.1.2.0__release.sql index 0e45e82425..4549e6a2d0 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20241203.1.2.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20241203.1.2.0__release.sql @@ -1,9 +1,9 @@ --- Table structure for public.dinky_user +-- Table structure for ${dinky_schema}.dinky_user -CREATE TABLE IF NOT EXISTS public.dinky_user_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_user_backup ( id serial PRIMARY KEY NOT NULL, username varchar(50) NOT NULL, @@ -19,23 +19,23 @@ CREATE TABLE IF NOT EXISTS public.dinky_user_backup create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON TABLE public.dinky_user_backup IS 'user'; -COMMENT ON COLUMN public.dinky_user_backup.id IS 'id'; -COMMENT ON COLUMN public.dinky_user_backup.username IS 'username'; -COMMENT ON COLUMN public.dinky_user_backup.password IS 'password'; -COMMENT ON COLUMN public.dinky_user_backup.nickname IS 'nickname'; -COMMENT ON COLUMN public.dinky_user_backup.worknum IS 'worknum'; -COMMENT ON COLUMN public.dinky_user_backup.avatar IS 'avatar'; -COMMENT ON COLUMN public.dinky_user_backup.mobile IS 'mobile phone'; -COMMENT ON COLUMN public.dinky_user_backup.enabled IS 'enabled'; -COMMENT ON COLUMN public.dinky_user_backup.super_admin_flag IS 'is super admin(0:false,1true)'; +COMMENT ON TABLE ${dinky_schema}.dinky_user_backup IS 'user'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.username IS 'username'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.password IS 'password'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.nickname IS 'nickname'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.worknum IS 'worknum'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.avatar IS 'avatar'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.mobile IS 'mobile phone'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.enabled IS 'enabled'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_backup.super_admin_flag IS 'is super admin(0:false,1true)'; -insert into public.dinky_user_backup(id, username, user_type, password, nickname, worknum, avatar, mobile, enabled, super_admin_flag, is_delete, create_time, update_time) +insert into ${dinky_schema}.dinky_user_backup(id, username, user_type, password, nickname, worknum, avatar, mobile, enabled, super_admin_flag, is_delete, create_time, update_time) select id, username, user_type, password, nickname, worknum, avatar, mobile, enabled, case when super_admin_flag = 0 then false else true end as super_admin_flag , is_delete, create_time, update_time -from public.dinky_user; +from ${dinky_schema}.dinky_user; -drop table if exists public.dinky_user; -alter table public.dinky_user_backup rename to dinky_user; +drop table if exists ${dinky_schema}.dinky_user; +alter table ${dinky_schema}.dinky_user_backup rename to dinky_user; diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20241205.1.2.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20241205.1.2.0__release.sql index 21e17a6a61..ed33f11a6d 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20241205.1.2.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20241205.1.2.0__release.sql @@ -1,15 +1,15 @@ CREATE OR REPLACE TRIGGER set_update_time_dinky_user BEFORE UPDATE - ON public.dinky_user + ON ${dinky_schema}.dinky_user FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); --- Table structure for public.dinky_resources -CREATE TABLE IF NOT EXISTS public.dinky_resources_backup +-- Table structure for ${dinky_schema}.dinky_resources +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_resources_backup ( id SERIAL PRIMARY KEY NOT NULL, file_name VARCHAR(64), @@ -26,31 +26,31 @@ CREATE TABLE IF NOT EXISTS public.dinky_resources_backup updater INT ); -CREATE UNIQUE INDEX IF NOT EXISTS dinky_resources_un1 ON public.dinky_resources_backup (full_name, type); +CREATE UNIQUE INDEX IF NOT EXISTS dinky_resources_un1 ON ${dinky_schema}.dinky_resources_backup (full_name, type); -COMMENT ON TABLE public.dinky_resources_backup IS 'resources'; +COMMENT ON TABLE ${dinky_schema}.dinky_resources_backup IS 'resources'; -COMMENT ON COLUMN public.dinky_resources_backup.id IS 'key'; -COMMENT ON COLUMN public.dinky_resources_backup.file_name IS 'file name'; -COMMENT ON COLUMN public.dinky_resources_backup.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_resources_backup.type IS 'resource type,0:FILE，1:UDF'; -COMMENT ON COLUMN public.dinky_resources_backup.size IS 'resource size'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources_backup.id IS 'key'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources_backup.file_name IS 'file name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources_backup.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources_backup.type IS 'resource type,0:FILE，1:UDF'; +COMMENT ON COLUMN ${dinky_schema}.dinky_resources_backup.size IS 'resource size'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_dinky_resources BEFORE UPDATE - ON public.dinky_resources_backup + ON ${dinky_schema}.dinky_resources_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_resources_backup(id, file_name, description, user_id, type, size, pid, full_name, is_directory, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_resources_backup(id, file_name, description, user_id, type, size, pid, full_name, is_directory, create_time, update_time, creator, updater) select id, file_name, description, user_id, type, size, pid, full_name, case when is_directory = 0 then false else true end as is_directory , create_time, update_time, creator, updater -from public.dinky_resources; +from ${dinky_schema}.dinky_resources; -drop table if exists public.dinky_resources; -alter table public.dinky_resources_backup rename to dinky_resources; +drop table if exists ${dinky_schema}.dinky_resources; +alter table ${dinky_schema}.dinky_resources_backup rename to dinky_resources; @@ -59,11 +59,11 @@ alter table public.dinky_resources_backup rename to dinky_resources; -- ---------------------------- --- Table structure for public.dinky_alert_instance +-- Table structure for ${dinky_schema}.dinky_alert_instance -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_instance_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_instance_backup ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(50) NOT NULL, @@ -79,44 +79,44 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_instance_backup ); COMMENT - ON COLUMN public.dinky_alert_instance_backup.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.id IS 'id'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.name IS 'alert instance name'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.name IS 'alert instance name'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.type IS 'alert instance type such as: DingTalk,Wechat(Webhook,app) Feishu ,email'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.type IS 'alert instance type such as: DingTalk,Wechat(Webhook,app) Feishu ,email'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.params IS 'configuration'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.params IS 'configuration'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_alert_instance_backup.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_alert_instance_backup.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_alert_instance_backup IS 'Alert instance'; + ON TABLE ${dinky_schema}.dinky_alert_instance_backup IS 'Alert instance'; CREATE OR REPLACE TRIGGER set_update_time_dinky_alert_instance BEFORE UPDATE - ON public.dinky_alert_instance_backup + ON ${dinky_schema}.dinky_alert_instance_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_alert_instance_backup(id, name, tenant_id, type, params, enabled, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_alert_instance_backup(id, name, tenant_id, type, params, enabled, create_time, update_time, creator, updater) select id, name, tenant_id, type, params, - case when enabled = 0 then false else true end as enabled + case when enabled::int = 0 then false else true end as enabled , create_time, update_time, creator, updater -from public.dinky_alert_instance; +from ${dinky_schema}.dinky_alert_instance; -drop table if exists public.dinky_alert_instance; -alter table public.dinky_alert_instance_backup rename to dinky_alert_instance; +drop table if exists ${dinky_schema}.dinky_alert_instance; +alter table ${dinky_schema}.dinky_alert_instance_backup rename to dinky_alert_instance; @@ -127,10 +127,10 @@ alter table public.dinky_alert_instance_backup rename to dinky_alert_instance; -- ---------------------------- --- Table structure for public.dinky_alert_group +-- Table structure for ${dinky_schema}.dinky_alert_group -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_group_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_group_backup ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(50) NOT NULL, @@ -146,49 +146,49 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_group_backup ); COMMENT - ON COLUMN public.dinky_alert_group_backup.id IS 'id'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.id IS 'id'; COMMENT - ON COLUMN public.dinky_alert_group_backup.name IS 'alert group name'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.name IS 'alert group name'; COMMENT - ON COLUMN public.dinky_alert_group_backup.tenant_id IS 'tenant id'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.tenant_id IS 'tenant id'; COMMENT - ON COLUMN public.dinky_alert_group_backup.alert_instance_ids IS 'Alert instance IDS'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.alert_instance_ids IS 'Alert instance IDS'; COMMENT - ON COLUMN public.dinky_alert_group_backup.note IS 'note'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.note IS 'note'; COMMENT - ON COLUMN public.dinky_alert_group_backup.enabled IS 'is enable'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.enabled IS 'is enable'; COMMENT - ON COLUMN public.dinky_alert_group_backup.create_time IS 'create time'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.create_time IS 'create time'; COMMENT - ON COLUMN public.dinky_alert_group_backup.update_time IS 'update time'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.update_time IS 'update time'; COMMENT - ON COLUMN public.dinky_alert_group_backup.creator IS 'creator user id'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.creator IS 'creator user id'; COMMENT - ON COLUMN public.dinky_alert_group_backup.updater IS 'updater user id'; + ON COLUMN ${dinky_schema}.dinky_alert_group_backup.updater IS 'updater user id'; COMMENT - ON TABLE public.dinky_alert_group_backup IS 'Alert group'; + ON TABLE ${dinky_schema}.dinky_alert_group_backup IS 'Alert group'; CREATE OR REPLACE TRIGGER set_update_time_dinky_alert_group BEFORE UPDATE - ON public.dinky_alert_group_backup + ON ${dinky_schema}.dinky_alert_group_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_alert_group_backup(id, name, tenant_id, alert_instance_ids, note, enabled, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_alert_group_backup(id, name, tenant_id, alert_instance_ids, note, enabled, create_time, update_time, creator, updater) select id, name, tenant_id, alert_instance_ids, note, - case when enabled = 0 then false else true end as enabled + case when enabled::int = 0 then false else true end as enabled , create_time, update_time, creator, updater -from public.dinky_alert_group; -drop table if exists public.dinky_alert_group; -alter table public.dinky_alert_group_backup rename to dinky_alert_group; +from ${dinky_schema}.dinky_alert_group; +drop table if exists ${dinky_schema}.dinky_alert_group; +alter table ${dinky_schema}.dinky_alert_group_backup rename to dinky_alert_group; -- ---------------------------- --- Table structure for public.dinky_alert_template +-- Table structure for ${dinky_schema}.dinky_alert_template -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_template_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_template_backup ( id SERIAL PRIMARY KEY NOT NULL, name VARCHAR(20), @@ -201,32 +201,32 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_template_backup CONSTRAINT dinky_alert_template_unx_idx UNIQUE (name) ); -COMMENT ON COLUMN public.dinky_alert_template_backup.id IS 'id'; -COMMENT ON COLUMN public.dinky_alert_template_backup.name IS 'emplate name'; -COMMENT ON COLUMN public.dinky_alert_template_backup.template_content IS 'template content'; -COMMENT ON COLUMN public.dinky_alert_template_backup.enabled IS 'is enable'; --- public.dinky_git_project +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template_backup.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template_backup.name IS 'emplate name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template_backup.template_content IS 'template content'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_template_backup.enabled IS 'is enable'; +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_alert_template BEFORE UPDATE - ON public.dinky_alert_template_backup + ON ${dinky_schema}.dinky_alert_template_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_alert_template_backup(id, name, template_content, enabled, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_alert_template_backup(id, name, template_content, enabled, create_time, update_time, creator, updater) select id, name, template_content, - case when enabled = 0 then false else true end as enabled + case when enabled::int = 0 then false else true end as enabled , create_time, update_time, creator, updater -from public.dinky_alert_template; -drop table if exists public.dinky_alert_template; -alter table public.dinky_alert_template_backup rename to dinky_alert_template; +from ${dinky_schema}.dinky_alert_template; +drop table if exists ${dinky_schema}.dinky_alert_template; +alter table ${dinky_schema}.dinky_alert_template_backup rename to dinky_alert_template; -- ---------------------------- --- Table structure for public.dinky_alert_rules +-- Table structure for ${dinky_schema}.dinky_alert_rules -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_alert_rules_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_alert_rules_backup ( id SERIAL PRIMARY KEY, name VARCHAR(40) NOT NULL, @@ -241,41 +241,41 @@ CREATE TABLE IF NOT EXISTS public.dinky_alert_rules_backup creator INT, updater INT ); -CREATE UNIQUE INDEX IF NOT EXISTS dinky_alert_rules_name_unx ON public.dinky_alert_rules (name); +CREATE UNIQUE INDEX IF NOT EXISTS dinky_alert_rules_name_unx ON ${dinky_schema}.dinky_alert_rules (name); -COMMENT ON COLUMN public.dinky_alert_rules_backup.id IS 'id'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.name IS 'rule name'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.rule IS 'specify rule'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.template_id IS 'template id'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.rule_type IS 'alert rule type'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.trigger_conditions IS 'trigger conditions'; -COMMENT ON COLUMN public.dinky_alert_rules_backup.description IS 'description'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.name IS 'rule name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.rule IS 'specify rule'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.template_id IS 'template id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.rule_type IS 'alert rule type'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.trigger_conditions IS 'trigger conditions'; +COMMENT ON COLUMN ${dinky_schema}.dinky_alert_rules_backup.description IS 'description'; --- public.dinky_git_project +-- ${dinky_schema}.dinky_git_project CREATE OR REPLACE TRIGGER update_dinky_alert_rules BEFORE UPDATE - ON public.dinky_alert_rules_backup + ON ${dinky_schema}.dinky_alert_rules_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_alert_rules_backup(id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_alert_rules_backup(id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) select id, name, rule, template_id, rule_type, trigger_conditions, description, - case when enabled = 0 then false else true end as enabled + case when enabled::int = 0 then false else true end as enabled , create_time, update_time, creator, updater -from public.dinky_alert_rules; -drop table if exists public.dinky_alert_rules; -alter table public.dinky_alert_rules_backup rename to dinky_alert_rules; +from ${dinky_schema}.dinky_alert_rules; +drop table if exists ${dinky_schema}.dinky_alert_rules; +alter table ${dinky_schema}.dinky_alert_rules_backup rename to dinky_alert_rules; -- ---------------------------- --- Table structure for public.dinky_fragment +-- Table structure for ${dinky_schema}.dinky_fragment -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_fragment_backup +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_fragment_backup ( id serial PRIMARY KEY NOT NULL, name varchar(50) NOT NULL, @@ -290,31 +290,31 @@ CREATE TABLE IF NOT EXISTS public.dinky_fragment_backup UNIQUE (name, tenant_id) ); -COMMENT ON TABLE public.dinky_fragment_backup is 'fragment management'; -COMMENT ON COLUMN public.dinky_fragment_backup.id is 'id'; -COMMENT ON COLUMN public.dinky_fragment_backup.name is 'fragment name'; -COMMENT ON COLUMN public.dinky_fragment_backup.tenant_id is 'tenant id'; -COMMENT ON COLUMN public.dinky_fragment_backup.fragment_value is 'fragment value'; -COMMENT ON COLUMN public.dinky_fragment_backup.note is 'note'; -COMMENT ON COLUMN public.dinky_fragment_backup.enabled is 'enabled'; -COMMENT ON COLUMN public.dinky_fragment_backup.create_time is 'create time'; -COMMENT ON COLUMN public.dinky_fragment_backup.update_time is 'update time'; -COMMENT ON COLUMN public.dinky_fragment_backup.creator is 'creator'; -COMMENT ON COLUMN public.dinky_fragment_backup.updater is 'updater'; +COMMENT ON TABLE ${dinky_schema}.dinky_fragment_backup is 'fragment management'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.id is 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.name is 'fragment name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.tenant_id is 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.fragment_value is 'fragment value'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.note is 'note'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.enabled is 'enabled'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.create_time is 'create time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.update_time is 'update time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.creator is 'creator'; +COMMENT ON COLUMN ${dinky_schema}.dinky_fragment_backup.updater is 'updater'; CREATE OR REPLACE TRIGGER update_dinky_fragment_modtime BEFORE UPDATE - ON public.dinky_fragment_backup + ON ${dinky_schema}.dinky_fragment_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_fragment_backup(id, name, tenant_id, fragment_value, note, enabled, create_time, update_time, creator, updater) +insert into ${dinky_schema}.dinky_fragment_backup(id, name, tenant_id, fragment_value, note, enabled, create_time, update_time, creator, updater) select id, name, tenant_id, fragment_value, note, - case when enabled = 0 then false else true end as enabled + case when enabled::int = 0 then false else true end as enabled , create_time, update_time, creator, updater -from public.dinky_fragment; -drop table if exists public.dinky_fragment; -alter table public.dinky_fragment_backup rename to dinky_fragment; +from ${dinky_schema}.dinky_fragment; +drop table if exists ${dinky_schema}.dinky_fragment; +alter table ${dinky_schema}.dinky_fragment_backup rename to dinky_fragment; diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20241217.1.2.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20241217.1.2.0__release.sql index 853b00ecb0..8766d06d0d 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20241217.1.2.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20241217.1.2.0__release.sql @@ -1,6 +1,6 @@ --- Table structure for public.dinky_user_tenant -CREATE TABLE IF NOT EXISTS public.dinky_user_tenant_backup +-- Table structure for ${dinky_schema}.dinky_user_tenant +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_user_tenant_backup ( id serial PRIMARY KEY, user_id int NOT NULL, @@ -10,28 +10,28 @@ CREATE TABLE IF NOT EXISTS public.dinky_user_tenant_backup update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ); -CREATE UNIQUE INDEX IF NOT EXISTS user_tenant_un_idx1 ON public.dinky_user_tenant_backup (user_id, tenant_id); +CREATE UNIQUE INDEX IF NOT EXISTS user_tenant_un_idx1 ON ${dinky_schema}.dinky_user_tenant_backup (user_id, tenant_id); -COMMENT ON TABLE public.dinky_user_tenant_backup IS 'Relationship between users and tenants'; -COMMENT ON COLUMN public.dinky_user_tenant_backup.id IS 'id'; -COMMENT ON COLUMN public.dinky_user_tenant_backup.user_id IS 'user id'; -COMMENT ON COLUMN public.dinky_user_tenant_backup.tenant_id IS 'tenant id'; -COMMENT ON COLUMN public.dinky_user_tenant_backup.tenant_admin_flag IS 'tenant admin flag(0:false,1:true)'; +COMMENT ON TABLE ${dinky_schema}.dinky_user_tenant_backup IS 'Relationship between users and tenants'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant_backup.id IS 'id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant_backup.user_id IS 'user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant_backup.tenant_id IS 'tenant id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_user_tenant_backup.tenant_admin_flag IS 'tenant admin flag(0:false,1:true)'; CREATE OR REPLACE TRIGGER set_update_time_dinky_user_tenant BEFORE UPDATE - ON public.dinky_user_tenant_backup + ON ${dinky_schema}.dinky_user_tenant_backup FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); -insert into public.dinky_user_tenant_backup(id, user_id, tenant_id, tenant_admin_flag, create_time, update_time) +insert into ${dinky_schema}.dinky_user_tenant_backup(id, user_id, tenant_id, tenant_admin_flag, create_time, update_time) select id, user_id, tenant_id, case when tenant_admin_flag = 0 then false else true end as tenant_admin_flag, create_time, update_time -from public.dinky_user_tenant; +from ${dinky_schema}.dinky_user_tenant; -drop table if exists public.dinky_user_tenant; -alter table public.dinky_user_tenant_backup rename to dinky_user_tenant; +drop table if exists ${dinky_schema}.dinky_user_tenant; +alter table ${dinky_schema}.dinky_user_tenant_backup rename to dinky_user_tenant; diff --git a/dinky-admin/src/main/resources/db/migration/postgresql/V20250301.1.3.0__release.sql b/dinky-admin/src/main/resources/db/migration/postgresql/V20250301.1.3.0__release.sql index 3f2638026c..4569ab09af 100644 --- a/dinky-admin/src/main/resources/db/migration/postgresql/V20250301.1.3.0__release.sql +++ b/dinky-admin/src/main/resources/db/migration/postgresql/V20250301.1.3.0__release.sql @@ -22,7 +22,7 @@ -- Table structure for dinky_approval -- ---------------------------- -CREATE TABLE IF NOT EXISTS public.dinky_approval +CREATE TABLE IF NOT EXISTS ${dinky_schema}.dinky_approval ( id SERIAL PRIMARY KEY NOT NULL, task_id INT NOT NULL, @@ -38,26 +38,26 @@ CREATE TABLE IF NOT EXISTS public.dinky_approval update_time TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP ); -COMMENT ON COLUMN public.dinky_approval.id IS 'ID'; -COMMENT ON COLUMN public.dinky_approval.task_id IS 'name'; -COMMENT ON COLUMN public.dinky_approval.tenant_id IS 'tenant_id'; -COMMENT ON COLUMN public.dinky_approval.previous_task_version IS 'previous version of task'; -COMMENT ON COLUMN public.dinky_approval.current_task_version IS 'current version to be reviewed of task'; -COMMENT ON COLUMN public.dinky_approval.status IS 'approval status'; -COMMENT ON COLUMN public.dinky_approval.submitter IS 'submitter user id'; -COMMENT ON COLUMN public.dinky_approval.submitter_comment IS 'submitter comment'; -COMMENT ON COLUMN public.dinky_approval.reviewer IS 'reviewer user id'; -COMMENT ON COLUMN public.dinky_approval.reviewer_comment IS 'reviewer comment'; -COMMENT ON COLUMN public.dinky_approval.create_time IS 'create time'; -COMMENT ON COLUMN public.dinky_approval.update_tIme IS 'update time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.id IS 'ID'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.task_id IS 'name'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.tenant_id IS 'tenant_id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.previous_task_version IS 'previous version of task'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.current_task_version IS 'current version to be reviewed of task'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.status IS 'approval status'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.submitter IS 'submitter user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.submitter_comment IS 'submitter comment'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.reviewer IS 'reviewer user id'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.reviewer_comment IS 'reviewer comment'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.create_time IS 'create time'; +COMMENT ON COLUMN ${dinky_schema}.dinky_approval.update_tIme IS 'update time'; -CREATE INDEX IF NOT EXISTS task_id_current_version_idx ON public.dinky_approval (task_id, current_task_version); -CREATE INDEX IF NOT EXISTS tenant_id_submitter_union_idx ON public.dinky_approval (submitter, tenant_id); -CREATE INDEX IF NOT EXISTS tenant_id_reviewer_union_idx ON public.dinky_approval (reviewer, tenant_id); +CREATE INDEX IF NOT EXISTS task_id_current_version_idx ON ${dinky_schema}.dinky_approval (task_id, current_task_version); +CREATE INDEX IF NOT EXISTS tenant_id_submitter_union_idx ON ${dinky_schema}.dinky_approval (submitter, tenant_id); +CREATE INDEX IF NOT EXISTS tenant_id_reviewer_union_idx ON ${dinky_schema}.dinky_approval (reviewer, tenant_id); CREATE OR REPLACE TRIGGER set_update_time_dinky_approval BEFORE UPDATE - ON public.dinky_approval + ON ${dinky_schema}.dinky_approval FOR EACH ROW EXECUTE FUNCTION trigger_set_timestamp(); @@ -65,20 +65,20 @@ EXECUTE FUNCTION trigger_set_timestamp(); -- approval menu -- ---------------------------- -INSERT INTO public.dinky_sys_menu(id, parent_id, name, path, component, perms, icon, type, display, order_num, +INSERT INTO ${dinky_schema}.dinky_sys_menu(id, parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) VALUES (176, 4, '审批发布', '/auth/approval', './AuthCenter/Approval', 'auth:approval:operate', 'AuditOutlined', 'C', 0, 169, '2024-12-10 12:13:00', '2024-12-10 12:13:00', null); -insert into public.dinky_sys_menu (id, parent_id, name, path, component, perms, icon, type, display, +insert into ${dinky_schema}.dinky_sys_menu (id, parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) values (177, 24, '审批配置', '/settings/globalsetting/approval', null, 'settings:globalsetting:approval', 'SettingOutlined', 'F', 0, 170, '2024-12-30 23:45:30', '2024-12-30 23:45:30', null); -insert into public.dinky_sys_menu (id, parent_id, name, path, component, perms, icon, type, display, +insert into ${dinky_schema}.dinky_sys_menu (id, parent_id, name, path, component, perms, icon, type, display, order_num, create_time, update_time, note) values (178, 177, '编辑', '/settings/globalsetting/approval/edit', null, 'settings:globalsetting:approval:edit', 'EditOutlined', 'F', 0, 171, '2024-12-30 23:45:30', '2024-12-30 23:45:30', null); -ALTER TABLE public.dinky_task ADD COLUMN IF NOT EXISTS auto_restart boolean DEFAULT FALSE; -COMMENT ON COLUMN public.dinky_task.auto_restart IS '是否自动重启，当作业失败或UNKNOWN时自动从最新checkpoint重启'; \ No newline at end of file +ALTER TABLE ${dinky_schema}.dinky_task ADD COLUMN IF NOT EXISTS auto_restart boolean DEFAULT FALSE; +COMMENT ON COLUMN ${dinky_schema}.dinky_task.auto_restart IS '是否自动重启，当作业失败或UNKNOWN时自动从最新checkpoint重启'; \ No newline at end of file diff --git a/script/sql/dinky-pg.sql b/script/sql/dinky-pg.sql index 7cc4417a86..d2197823a6 100644 --- a/script/sql/dinky-pg.sql +++ b/script/sql/dinky-pg.sql @@ -519,205 +519,205 @@ EXECUTE FUNCTION trigger_set_timestamp(); -- Data for Name: dinky_flink_document; Type: TABLE DATA; Schema: public; Owner: postgres -- -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (125, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP(string1, string2)', '如果string1的任何子字符串(可能为空)与Java正则表达式string2匹配，则返回TRUE，否则返回FALSE。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'REGEXP(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (126, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REVERSE(string)', '返回反向字符串。如果字符串为NULL，则返回NULL仅在blink planner中支持。', 'REVERSE(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (127, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SPLIT_INDEX(string1, string2, integer1)', '通过分隔符string2拆分string1，返回拆分字符串的整数(从零开始)字符串。如果整数为负，返回NULL。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'SPLIT_INDEX(${1:}, ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (128, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'STR_TO_MAP(string1[, string2, string3]])', '使用分隔符将string1分割成键/值对后返回一个映射。string2是pair分隔符，默认为''，''。string3是键值分隔符，默认为''=''。仅在blink planner中支持。', 'STR_TO_MAP(${1:})', '1.12', 4, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (129, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SUBSTR(string[, integer1[, integer2]])', '返回一个字符串的子字符串，从位置integer1开始，长度为integer2(默认到末尾)。仅在blink planner中支持。', 'SUBSTR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (130, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHAR_LENGTH(string)', '返回STRING中的字符数。', 'CHAR_LENGTH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (131, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHARACTER_LENGTH(string)', '返回STRING中的字符数。', 'CHARACTER_LENGTH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (132, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DATE string', '返回以“ yyyy-MM-dd”形式从STRING解析的SQL日期。', 'DATE(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (133, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIME string', '返回以“ HH：mm：ss”的形式从STRING解析的SQL时间。', 'TIME(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (134, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMP string', '返回从STRING解析的SQL时间戳，格式为“ yyyy-MM-dd HH：mm：ss [.SSS]”', 'TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (135, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'INTERVAL string range', '解析“dd hh:mm:ss”形式的区间字符串。fff表示毫秒间隔，yyyy-mm表示月间隔。间隔范围可以是天、分钟、天到小时或天到秒，以毫秒为间隔;年或年到月的间隔。', 'INTERVAL ${1:} range', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (136, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_DATE', '返回UTC时区中的当前SQL日期。', 'CURRENT_DATE', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (137, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_TIME', '返回UTC时区的当前SQL时间。', 'CURRENT_TIME', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (138, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CURRENT_TIMESTAMP', '返回UTC时区内的当前SQL时间戳。', 'CURRENT_TIMESTAMP', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (139, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'LOCALTIME', '返回本地时区的当前SQL时间。', 'LOCALTIME', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (140, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'LOCALTIMESTAMP', '返回本地时区的当前SQL时间戳。', 'LOCALTIMESTAMP', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (141, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'EXTRACT(timeintervalunit FROM temporal)', '返回从时域的timeintervalunit部分提取的长值。', 'EXTRACT(${1:} FROM ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (142, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'YEAR(date)', '返回SQL date日期的年份。等价于EXTRACT(YEAR FROM date)。', 'YEAR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (143, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'QUARTER(date)', '从SQL date date返回一年中的季度(1到4之间的整数)。相当于EXTRACT(从日期起四分之一)。', 'QUARTER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (144, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'MONTH(date)', '返回SQL date date中的某月(1到12之间的整数)。等价于EXTRACT(MONTH FROM date)。', 'MONTH(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (145, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'WEEK(date)', '从SQL date date返回一年中的某个星期(1到53之间的整数)。相当于EXTRACT(从日期开始的星期)。', 'WEEK(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (146, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFYEAR(date)', '返回SQL date date中的某一天(1到366之间的整数)。相当于EXTRACT(DOY FROM date)。', 'DAYOFYEAR(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (147, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFMONTH(date)', '从SQL date date返回一个月的哪一天(1到31之间的整数)。相当于EXTRACT(DAY FROM date)。', 'DAYOFMONTH(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (148, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DAYOFWEEK(date)', '返回星期几(1到7之间的整数;星期日= 1)从SQL日期日期。相当于提取(道指从日期)。', 'DAYOFWEEK(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (149, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'HOUR(timestamp)', '从SQL timestamp timestamp返回一天中的小时(0到23之间的整数)。相当于EXTRACT(HOUR FROM timestamp)。', 'HOUR(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (150, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'MINUTE(timestamp)', '从SQL timestamp timestamp返回一小时的分钟(0到59之间的整数)。相当于EXTRACT(分钟从时间戳)。', 'MINUTE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (151, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'SECOND(timestamp)', '从SQL时间戳返回一分钟中的秒(0到59之间的整数)。等价于EXTRACT(从时间戳开始倒数第二)。', 'SECOND(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (152, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'FLOOR(timepoint TO timeintervalunit)', '返回一个将timepoint舍入到时间单位timeintervalunit的值。', 'FLOOR(${1:} TO ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (153, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CEIL(timepoint TO timeintervalunit)', '返回一个将timepoint舍入到时间单位timeintervalunit的值。', 'CEIL(${1:} TO ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (154, 'Function', 'FUN_UDF', 'TIME_FUNCTION', '(timepoint1, temporal1) OVERLAPS (timepoint2, temporal2)', '如果(timepoint1, temporal1)和(timepoint2, temporal2)定义的两个时间间隔重叠，则返回TRUE。时间值可以是时间点或时间间隔。', '(${1:} , ${1:}) OVERLAPS (${2:} , ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (155, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'DATE_FORMAT(timestamp, string)', '注意这个功能有严重的错误，现在不应该使用。请实现一个自定义的UDF，或者使用EXTRACT作为解决方案。', 'DATE_FORMAT(${1:}, ''yyyy-MM-dd'')', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (156, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMPADD(timeintervalunit, interval, timepoint)', '返回一个新的时间值，该值将一个(带符号的)整数间隔添加到时间点。间隔的单位由unit参数给出，它应该是以下值之一:秒、分、小时、日、周、月、季度或年。', 'TIMESTAMPADD(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (39, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IN (sub-query)', '如果value存在于子查询中，则返回TRUE。', '${1:} IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (157, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TIMESTAMPDIFF(timepointunit, timepoint1, timepoint2)', '返回timepointunit在timepoint1和timepoint2之间的(带符号)数。间隔的单位由第一个参数给出，它应该是以下值之一:秒、分、小时、日、月或年。', 'TIMESTAMPDIFF(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (158, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'CONVERT_TZ(string1, string2, string3)', '将时区string2中的datetime string1(默认ISO时间戳格式''yyyy-MM-dd HH:mm:ss'')转换为时区string3。时区的格式可以是缩写，如“PST”;可以是全名，如“America/Los_Angeles”;或者是自定义ID，如“GMT-8:00”。仅在blink planner中支持。', 'CONVERT_TZ(${1:} , ${2:} , ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (159, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'FROM_UNIXTIME(numeric[, string])', '以字符串格式返回数值参数的表示形式(默认为''yyyy-MM-dd HH:mm:ss'')。numeric是一个内部时间戳值，表示从UTC ''1970-01-01 00:00:00''开始的秒数，例如UNIX_TIMESTAMP()函数生成的时间戳。返回值用会话时区表示(在TableConfig中指定)。仅在blink planner中支持。', 'FROM_UNIXTIME(${1:} )', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (160, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'UNIX_TIMESTAMP()', '获取当前Unix时间戳(以秒为单位)。仅在blink planner中支持。', 'UNIX_TIMESTAMP()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (161, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'UNIX_TIMESTAMP(string1[, string2])', '转换日期时间字符串string1，格式为string2(缺省为yyyy-MM-dd HH:mm:ss，如果没有指定)为Unix时间戳(以秒为单位)，使用表配置中指定的时区。仅在blink planner中支持。', 'UNIX_TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (162, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TO_DATE(string1[, string2])', '将格式为string2的日期字符串string1(默认为''yyyy-MM-dd'')转换为日期。仅在blink planner中支持。', 'TO_DATE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (163, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'TO_TIMESTAMP(string1[, string2])', '将会话时区(由TableConfig指定)下的日期时间字符串string1转换为时间戳，格式为string2(默认为''yyyy-MM-dd HH:mm:ss'')。仅在blink planner中支持。', 'TO_TIMESTAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (164, 'Function', 'FUN_UDF', 'TIME_FUNCTION', 'NOW()', '返回UTC时区内的当前SQL时间戳。仅在blink planner中支持。', 'NOW()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (165, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'CASE value WHEN value1_1 [, value1_2 ]* THEN result1 @@ -727,7 +727,7 @@ END', '当第一个时间值包含在(valueX_1, valueX_2，…)中时，返回re WHEN ${2:} THEN ${3:} ELSE ${4:} END AS ${5:}', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (166, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'CASE WHEN condition1 THEN result1 @@ -736,143 +736,143 @@ WHEN condition1 THEN result1 END', '当第一个条件满足时返回resultX。当不满足任何条件时，如果提供了resultZ则返回resultZ，否则返回NULL。', 'CASE WHEN ${1:} THEN ${2:} ELSE ${3:} END AS ${4:}', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (167, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'NULLIF(value1, value2)', '如果value1等于value2，则返回NULL;否则返回value1。', 'NULLIF(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (168, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'COALESCE(value1, value2 [, value3 ]* )', '返回value1, value2， ....中的第一个非空值', 'COALESCE(${1:} )', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (169, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IF(condition, true_value, false_value)', '如果条件满足则返回true值，否则返回false值。仅在blink planner中支持。', 'IF((${1:}, ${2:}, ${3:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (170, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_ALPHA(string)', '如果字符串中所有字符都是字母则返回true，否则返回false。仅在blink planner中支持。', 'IS_ALPHA(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (171, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_DECIMAL(string)', '如果字符串可以被解析为有效的数字则返回true，否则返回false。仅在blink planner中支持。', 'IS_DECIMAL(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (172, 'Function', 'FUN_UDF', 'CONDITIONAL_FUNCTION', 'IS_DIGIT(string)', '如果字符串中所有字符都是数字则返回true，否则返回false。仅在blink planner中支持。', 'IS_DIGIT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (173, 'Function', 'FUN_UDF', 'TYPE_CONVER_FUNCTION', 'CAST(value AS type)', '返回一个要转换为type类型的新值。', 'CAST(${1:} AS ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (174, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'CARDINALITY(array)', '返回数组中元素的数量。', 'CARDINALITY(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (175, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'array ‘[’ integer ‘]’', '返回数组中位于整数位置的元素。索引从1开始。', 'array[${1:}]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (176, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'ELEMENT(array)', '返回数组的唯一元素(其基数应为1);如果数组为空，则返回NULL。如果数组有多个元素，则抛出异常。', 'ELEMENT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (177, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'CARDINALITY(map)', '返回map中的条目数。', 'CARDINALITY(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (178, 'Function', 'FUN_UDF', 'COLLECTION_FUNCTION', 'map ‘[’ value ‘]’', '返回map中key value指定的值。', 'map[${1:}]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (179, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'ARRAY ‘[’ value1 [, value2 ]* ‘]’', '返回一个由一系列值(value1, value2，…)创建的数组。', 'ARRAY[ ${1:} ]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (180, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'MAP ‘[’ value1, value2 [, value3, value4 ]* ‘]’', '返回一个从键值对列表((value1, value2)， (value3, value4)，…)创建的映射。', 'MAP[ ${1:} ]', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (181, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'implicit constructor with parenthesis (value1 [, value2]*)', '返回从值列表(value1, value2，…)创建的行。', '(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (182, 'Function', 'FUN_UDF', 'VALUE_CONSTRUCTION_FUNCTION', 'explicit ROW constructor ROW(value1 [, value2]*)', '返回从值列表(value1, value2，…)创建的行。', 'ROW(${1:}) ', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (183, 'Function', 'FUN_UDF', 'VALUE_ACCESS_FUNCTION', 'tableName.compositeType.field', '按名称从Flink复合类型(例如，Tuple, POJO)中返回一个字段的值。', 'tableName.compositeType.field', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (184, 'Function', 'FUN_UDF', 'VALUE_ACCESS_FUNCTION', 'tableName.compositeType.*', '返回Flink复合类型(例如，Tuple, POJO)的平面表示，它将每个直接子类型转换为一个单独的字段。在大多数情况下，平面表示的字段的名称与原始字段类似，但使用了$分隔符(例如，mypojo$mytuple$f0)。', 'tableName.compositeType.*', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:08:59', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (185, 'Function', 'FUN_UDF', 'GROUP_FUNCTION', 'GROUP_ID()', '返回唯一标识分组键组合的整数', 'GROUP_ID()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (186, 'Function', 'FUN_UDF', 'GROUP_FUNCTION', 'GROUPING(expression1 [, expression2]* ) GROUPING_ID(expression1 [, expression2]* )', '返回给定分组表达式的位向量。', 'GROUPING(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (1, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.async-lookup.buffer-capacity', '异步查找连接可以触发的最大异步操作的操作数。 The max number of async i/o operation that the async lookup join can trigger.', 'Set ''table.exec.async-lookup.buffer-capacity''=''100'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (2, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.async-lookup.timeout', '异步操作完成的超时时间。 The async timeout for the asynchronous operation to complete.', 'Set ''table.exec.async-lookup.timeout''=''3 min'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (3, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.disabled-operators', '禁用指定operators，用逗号分隔 Mainly for testing. A comma-separated list of operator names, each name represents a kind of disabled operator. Operators that can be disabled include "NestedLoopJoin", "ShuffleHashJoin", "BroadcastHashJoin", "SortMergeJoin", "HashAgg", "SortAgg". By default no operator is disabled.', 'Set ''table.exec.disabled-operators''=''SortMergeJoin'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (4, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.allow-latency', '最大等待时间可用于MiniBatch缓冲输入记录。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。MiniBatch以允许的等待时间间隔以及达到最大缓冲记录数触发。注意：如果将table.exec.mini-batch.enabled设置为true，则其值必须大于零.', 'Set ''table.exec.mini-batch.allow-latency''=''-1 ms'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (5, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.enabled', '指定是否启用MiniBatch优化。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。默认情况下禁用此功能。 要启用此功能，用户应将此配置设置为true。注意：如果启用了mini batch 处理，则必须设置“ table.exec.mini-batch.allow-latency”和“ table.exec.mini-batch.size”.', 'Set ''table.exec.mini-batch.enabled''=''false'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (6, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.mini-batch.size', '可以为MiniBatch缓冲最大输入记录数。 MiniBatch是用于缓冲输入记录以减少状态访问的优化。MiniBatch以允许的等待时间间隔以及达到最大缓冲记录数触发。 注意：MiniBatch当前仅适用于非窗口聚合。如果将table.exec.mini-batch.enabled设置为true，则其值必须为正.', 'Set ''table.exec.mini-batch.size''=''-1'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (7, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.resource.default-parallelism', '设置所有Operator的默认并行度。 Sets default parallelism for all operators (such as aggregate, join, filter) to run with parallel instances. This config has a higher priority than parallelism of StreamExecutionEnvironment (actually, this config overrides the parallelism of StreamExecutionEnvironment). A value of -1 indicates that no default parallelism is set, then it will fallback to use the parallelism of StreamExecutionEnvironment.', 'Set ''table.exec.resource.default-parallelism''=''1'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (8, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.sink.not-null-enforcer', '对表的NOT NULL列约束强制执行不能将空值插入到表中。Flink支持“error”（默认）和“drop”强制行为 The NOT NULL column constraint on a table enforces that null values can''t be inserted into the table. Flink supports ''error'' (default) and ''drop'' enforcement behavior. By default, Flink will check values and throw runtime exception when null values writing into NOT NULL columns. Users can change the behavior to ''drop'' to silently drop such records without throwing exception. @@ -880,7 +880,7 @@ Possible values: "ERROR" "DROP"', 'Set ''table.exec.sink.not-null-enforcer''=''ERROR'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (9, 'Variable', 'FLINK_OPTIONS', '', 'set table.exec.sink.upsert-materialize', '由于分布式系统中 Shuffle 导致 ChangeLog 数据混乱，Sink 接收到的数据可能不是全局 upsert 的顺序。因此，在 upsert sink 之前添加 upsert materialize 运算符。它接收上游的变更日志记录并为下游生成一个 upsert 视图。默认情况下，当唯一键出现分布式无序时，会添加具体化操作符。您也可以选择不实现（NONE）或强制实现（FORCE）。 Possible values: @@ -888,7 +888,7 @@ Possible values: "FORCE" "AUTO"', 'Set ''table.exec.sink.upsert-materialize''=''AUTO'';', '1.14', 0, true, '2022-01-20 15:00:00', '2023-12-27 23:58:09', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (10, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.kafka', 'kafka快速建表格式', 'CREATE TABLE Kafka_Table ( `event_time` TIMESTAMP(3) METADATA FROM ''timestamp'', @@ -908,7 +908,7 @@ VALUES (10, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.kafka', 'kafka --可选: ''value.fields-include'' = ''ALL'', --可选: ''json.ignore-parse-errors'' = ''true'', --可选: ''key.fields-prefix'' = ''k_'',', '1.14', 0, true, '2022-01-20 16:59:18', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (11, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.doris', 'Doris快速建表', 'CREATE TABLE doris_table ( cid INT, @@ -924,7 +924,7 @@ VALUES (11, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.doris', 'Doris ''username'' = ''root'', ''password''='''' );', '1.14', 0, true, '2022-01-20 17:08:00', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (12, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.jdbc', 'JDBC建表语句', 'CREATE TABLE JDBC_table ( id BIGINT, @@ -941,7 +941,7 @@ VALUES (12, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.jdbc', 'JDBC建 ); --可选: ''sink.parallelism''=''1'', --可选: ''lookup.cache.ttl''=''1000s'',', '1.14', 0, true, '2022-01-20 17:15:26', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (13, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.catalog.hive', '创建HIVE的catalog', 'CREATE CATALOG hive WITH ( ''type'' = ''hive'', @@ -949,34 +949,34 @@ VALUES (13, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.catalog.hive', '创建 ''hive-conf-dir'' = ''/app/wwwroot/MBDC/hive/conf/'', --hive配置文件 ''hadoop-conf-dir''=''/app/wwwroot/MBDC/hadoop/etc/hadoop/'' --hadoop配置文件，配了环境变量则不需要。 );', '1.14', 0, true, '2022-01-20 17:18:54', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (14, 'Operator', 'SQL_TEMPLATE', 'FlinkSql', 'use.catalog.hive', '使用hive的catalog', 'USE CATALOG hive;', '1.14', 0, true, '2022-01-20 17:22:53', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (15, 'Operator', 'SQL_TEMPLATE', 'FlinkSql', 'use.catalog.default', '使用default的catalog', 'USE CATALOG default_catalog;', '1.14', 0, true, '2022-01-20 17:23:48', '2023-12-28 00:03:53', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (16, 'Variable', 'FLINK_OPTIONS', '', 'set dialect.hive', '使用hive方言', 'Set table.sql-dialect=hive;', '1.14', 0, true, '2022-01-20 17:25:37', '2023-12-28 00:04:44', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (17, 'Variable', 'FLINK_OPTIONS', '', 'set dialect.default', '使用default方言', 'Set table.sql-dialect=default;', '1.14', 0, true, '2022-01-20 17:26:19', '2023-12-28 00:04:44', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (40, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value NOT IN (sub-query)', '如果value不存在于子查询中，则返回TRUE。', '${1:} NOT IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (41, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean1 OR boolean2', '如果BOOLEAN1为TRUE或BOOLEAN2为TRUE，则返回TRUE。支持三值逻辑。 例如，true || Null(Types.BOOLEAN)返回TRUE。', '${1:} OR ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (18, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.stream.table.hive', '创建流式HIVE表', 'CREATE CATALOG hive WITH ( --创建hive的catalog ''type'' = ''hive'', @@ -1000,7 +1000,7 @@ CREATE TABLE hive_stream_table ( ''sink.rolling-policy.check-interval''=''1min'', ''sink.partition-commit.policy.kind''=''metastore,success-file'' );', '1.14', 0, true, '2022-01-20 17:34:06', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (19, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.mysql_cdc', '创建Mysql_CDC表', 'CREATE TABLE mysql_cdc_table( cid INT, @@ -1024,7 +1024,7 @@ VALUES (19, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.mysql_cdc', '创 ''debezium.datetime.format.timestamp''=''yyyy-MM-dd HH-mm-ss'', ''debezium.datetime.format.timestamp.zone''=''UTC+8'', ''table-name'' = ''mysql_cdc_table'');', '1.14', 0, true, '2022-01-20 17:49:14', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (20, 'Module', 'SQL_TEMPLATE', 'FlinkSql', 'create.table.hudi', '创建hudi表', 'CREATE TABLE hudi_table ( @@ -1064,80 +1064,80 @@ WITH ( ''hive_sync.password'' = ''123456'', -- required, HMS 密码 ''hive_sync.skip_ro_suffix'' = ''true'' -- 去除ro后缀 );', '1.14', 0, true, '2022-01-20 17:56:50', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (21, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 <> value2', '如果value1不等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} <> ${2:}', '1.12', 4, true, '2021-02-22 10:05:38', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (22, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 > value2', '如果value1大于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} > ${2:}', '1.12', 2, true, '2021-02-22 14:37:58', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (23, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 >= value2', '如果value1大于或等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} >= ${2:}', '1.12', 2, true, '2021-02-22 14:38:52', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (24, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 < value2', '如果value1小于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} < ${2:}', '1.12', 0, true, '2021-02-22 14:39:15', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (25, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 <= value2', '如果value1小于或等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} <= ${2:}', '1.12', 0, true, '2021-02-22 14:39:40', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (26, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IS NULL', '如果value为NULL，则返回TRUE 。', '${1:} IS NULL', '1.12', 2, true, '2021-02-22 14:40:39', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (27, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value IS NOT NULL', '如果value不为NULL，则返回TRUE 。', '${1:} IS NOT NULL', '1.12', 0, true, '2021-02-22 14:41:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (28, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IS DISTINCT FROM value2', '如果两个值不相等则返回TRUE。NULL值在这里被视为相同的值。', '${1:} IS DISTINCT FROM ${2:}', '1.12', 0, true, '2021-02-22 14:42:39', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (29, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IS NOT DISTINCT FROM value2', '如果两个值相等则返回TRUE。NULL值在这里被视为相同的值。', '${1:} IS NOT DISTINCT FROM ${2:}', '1.12', 0, true, '2021-02-22 14:43:23', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (30, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3', '如果value1大于或等于value2和小于或等于value3 返回true', '${1:} BETWEEN ${2:} AND ${3:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (31, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3', '如果value1小于value2或大于value3 返回true', '${1:} NOT BETWEEN ${2:} AND ${3:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (32, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 LIKE string2 [ ESCAPE char ]', '如果STRING1匹配模式STRING2，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} LIKE ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (33, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 NOT LIKE string2 [ ESCAPE char ]', '如果STRING1不匹配模式STRING2，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} NOT LIKE ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (34, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 SIMILAR TO string2 [ ESCAPE char ]', '如果STRING1与SQL正则表达式STRING2匹配，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} SIMILAR TO ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (35, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'string1 NOT SIMILAR TO string2 [ ESCAPE char ]', '如果STRING1与SQL正则表达式STRING2不匹配，则返回TRUE ；如果STRING1或STRING2为NULL，则返回UNKNOWN 。', '${1:} NOT SIMILAR TO ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (36, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IN (value2 [, value3]* )', '如果value1存在于给定列表（value2，value3，...）中，则返回TRUE 。 @@ -1145,7 +1145,7 @@ VALUES (36, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 IN (value2 [, val 如果value1为NULL，则始终返回UNKNOWN 。', '${1:} IN (${2:} )', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (37, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT IN (value2 [, value3]* )', '如果value1不存在于给定列表（value2，value3，...）中，则返回TRUE 。 @@ -1153,566 +1153,566 @@ VALUES (37, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 NOT IN (value2 [, 如果value1为NULL，则始终返回UNKNOWN 。', '${1:} NOT IN (${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (38, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'EXISTS (sub-query)', '如果value存在于子查询中，则返回TRUE。', 'EXISTS (${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (42, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean1 AND boolean2', '如果BOOLEAN1和BOOLEAN2均为TRUE，则返回TRUE。支持三值逻辑。 例如，true && Null(Types.BOOLEAN)返回未知。', '${1:} AND ${2:}', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (43, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'NOT boolean', '如果BOOLEAN为FALSE，则返回TRUE ；如果BOOLEAN为TRUE，则返回FALSE 。 如果BOOLEAN为UNKNOWN，则返回UNKNOWN。', 'NOT ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (44, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS FALSE', '如果BOOLEAN为FALSE，则返回TRUE ；如果BOOLEAN为TRUE或UNKNOWN，则返回FALSE 。', '${1:} IS FALSE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (45, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT FALSE', '如果BOOLEAN为TRUE或UNKNOWN，则返回TRUE ；如果BOOLEAN为FALSE，则返回FALSE。', '${1:} IS NOT FALSE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (46, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS TRUE', '如果BOOLEAN为TRUE，则返回TRUE；如果BOOLEAN为FALSE或UNKNOWN，则返回FALSE 。', '${1:} IS TRUE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (47, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT TRUE', '如果BOOLEAN为FALSE或UNKNOWN，则返回TRUE ；如果BOOLEAN为TRUE，则返回FALSE 。', '${1:} IS NOT TRUE', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (48, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS UNKNOWN', '如果BOOLEAN为UNKNOWN，则返回TRUE ；如果BOOLEAN为TRUE或FALSE，则返回FALSE 。', '${1:} IS UNKNOWN', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (49, 'Function', 'FUN_UDF', 'LOGICAL_FUNCTION', 'boolean IS NOT UNKNOWN', '如果BOOLEAN为TRUE或FALSE，则返回TRUE ；如果BOOLEAN为UNKNOWN，则返回FALSE 。', '${1:} IS NOT UNKNOWN', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (50, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', '+ numeric', '返回NUMERIC。', '+ ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (51, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', '- numeric', '返回负数NUMERIC。', '- ${1:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (52, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 + numeric2', '返回NUMERIC1加NUMERIC2。', '${1:} + ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (53, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 - numeric2', '返回NUMERIC1减去NUMERIC2。', '${1:} - ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (54, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 * numeric2', '返回NUMERIC1乘以NUMERIC2。', '${1:} * ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (55, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 / numeric2', '返回NUMERIC1除以NUMERIC2。', '${1:} / ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (56, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'numeric1 % numeric2', '返回NUMERIC1除以NUMERIC2的余数（模）。仅当numeric1为负数时，结果为负数。', '${1:} % ${2:} ', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (57, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'POWER(numeric1, numeric2)', '返回NUMERIC1的NUMERIC2 次幂。', 'POWER(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (58, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ABS(numeric)', '返回NUMERIC的绝对值。', 'ABS(${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (59, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'MOD(numeric1, numeric2)', '返回numeric1除以numeric2的余数(模)。只有当numeric1为负数时，结果才为负数', 'MOD(${1:} , ${2:} )', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (60, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SQRT(numeric)', '返回NUMERIC的平方根。', 'SQRT(${1:})', '1.12', 0, true, '2021-02-22 14:44:26', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (61, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LN(numeric)', '返回NUMERIC的自然对数（以e为底）。', 'LN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (62, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG10(numeric)', '返回NUMERIC的以10为底的对数。', 'LOG10(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (63, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG2(numeric)', '返回NUMERIC的以2为底的对数。', 'LOG2(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (64, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'EXP(numeric)', '返回e 的 NUMERIC 次幂。', 'EXP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (65, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'FLOOR(numeric)', '向下舍入NUMERIC，并返回小于或等于NUMERIC的最大整数。', 'FLOOR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (66, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SIN(numeric)', '返回NUMERIC的正弦值。', 'SIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (67, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SINH(numeric)', '返回NUMERIC的双曲正弦值。 返回类型为DOUBLE。', 'SINH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (68, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COS(numeric)', '返回NUMERIC的余弦值。', 'COS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (69, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TAN(numeric)', '返回NUMERIC的正切。', 'TAN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (70, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TANH(numeric)', '返回NUMERIC的双曲正切值。 返回类型为DOUBLE。', 'TANH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (71, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COT(numeric)', '返回NUMERIC的余切。', 'COT(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (72, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ASIN(numeric)', '返回NUMERIC的反正弦值。', 'ASIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (73, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ACOS(numeric)', '返回NUMERIC的反余弦值。', 'ACOS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (74, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ATAN(numeric)', '返回NUMERIC的反正切。', 'ATAN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (75, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ATAN2(numeric1, numeric2)', '返回坐标的反正切（NUMERIC1，NUMERIC2）。', 'ATAN2(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (76, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'COSH(numeric)', '返回NUMERIC的双曲余弦值。 返回值类型为DOUBLE。', 'COSH(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (77, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'DEGREES(numeric)', '返回弧度NUMERIC的度数表示形式', 'DEGREES(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (78, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RADIANS(numeric)', '返回度数NUMERIC的弧度表示。', 'RADIANS(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (79, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'SIGN(numeric)', '返回NUMERIC的符号。', 'SIGN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (80, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'ROUND(numeric, integer)', '返回一个数字，四舍五入为NUMERIC的INT小数位。', 'ROUND(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (81, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'PI', '返回一个比任何其他值都更接近圆周率的值。', 'PI', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (82, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'E()', '返回一个比任何其他值都更接近e的值。', 'E()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (83, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND()', '返回介于0.0（含）和1.0（不含）之间的伪随机双精度值。', 'RAND()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (84, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND(integer)', '返回带有初始种子INTEGER的介于0.0（含）和1.0（不含）之间的伪随机双精度值。 如果两个RAND函数具有相同的初始种子，它们将返回相同的数字序列。', 'RAND(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (85, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND_INTEGER(integer)', '返回介于0（含）和INTEGER（不含）之间的伪随机整数值。', 'RAND_INTEGER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (86, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'RAND_INTEGER(integer1, integer2)', '返回介于0（含）和INTEGER2（不含）之间的伪随机整数值，其初始种子为INTEGER1。 如果两个randInteger函数具有相同的初始种子和边界，它们将返回相同的数字序列。', 'RAND_INTEGER(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (87, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'UUID()', '根据RFC 4122 type 4（伪随机生成）UUID返回UUID（通用唯一标识符）字符串 （例如，“ 3d3c68f7-f608-473f-b60c-b0c44ad4cc4e”）。使用加密强度高的伪随机数生成器生成UUID。', 'UUID()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (88, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'BIN(integer)', '以二进制格式返回INTEGER的字符串表示形式。如果INTEGER为NULL，则返回NULL。 例如，4.bin()返回“ 100”并12.bin()返回“ 1100”。', 'BIN(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (89, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'HEX(numeric) HEX(string)', '以十六进制格式返回整数NUMERIC值或STRING的字符串表示形式。如果参数为NULL，则返回NULL。 例如，数字20导致“ 14”，数字100导致“ 64”，字符串“ hello，world”导致“ 68656C6C6F2C776F726C64”。', 'HEX(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (90, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'TRUNCATE(numeric1, integer2)', '返回一个小数点后被截断为integer2位的数字。', 'TRUNCATE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (91, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'PI()', '返回π (pi)的值。仅在blink planner中支持。', 'PI()', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (92, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG(numeric1)', '如果不带参数调用，则返回NUMERIC1的自然对数。当使用参数调用时，将NUMERIC1的对数返回到基数NUMERIC2。 注意：当前，NUMERIC1必须大于0，而NUMERIC2必须大于1。', 'LOG(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (93, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'LOG(numeric1, numeric2)', '如果不带参数调用，则返回NUMERIC1的自然对数。当使用参数调用时，将NUMERIC1的对数返回到基数NUMERIC2。 注意：当前，NUMERIC1必须大于0，而NUMERIC2必须大于1。', 'LOG(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (94, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'CEIL(numeric)', '将NUMERIC向上舍入，并返回大于或等于NUMERIC的最小整数。', 'CEIL(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (95, 'Function', 'FUN_UDF', 'ARITHMETIC_FUNCTIONS', 'CEILING(numeric)', '将NUMERIC向上舍入，并返回大于或等于NUMERIC的最小整数。', 'CEILING(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (96, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'string1 || string2', '返回string1和string2的连接。', '${1:} || ${2:}', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (97, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'UPPER(string)', '以大写形式返回STRING。', 'UPPER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (98, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LOWER(string)', '以小写形式返回STRING。', 'LOWER(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (99, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'POSITION(string1 IN string2)', '返回STRING1在STRING2中第一次出现的位置（从1开始）； 如果在STRING2中找不到STRING1，则返回0 。', 'POSITION(${1:} IN ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (100, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'TRIM([ BOTH | LEADING | TRAILING ] string1 FROM string2)', '返回一个字符串，该字符串从STRING中删除前导和/或结尾字符。', 'TRIM(${1:} FROM ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (101, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LTRIM(string)', '返回一个字符串，该字符串从STRING除去左空格。 例如，" This is a test String.".ltrim()返回“This is a test String.”。', 'LTRIM(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (102, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RTRIM(string)', '返回一个字符串，该字符串从STRING中删除正确的空格。 例如，"This is a test String. ".rtrim()返回“This is a test String.”。', 'RTRIM(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (103, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REPEAT(string, integer)', '返回一个字符串，该字符串重复基本STRING INT次。 例如，"This is a test String.".repeat(2)返回“This is a test String.This is a test String.”。', 'REPEAT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (104, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP_REPLACE(string1, string2, string3)', '返回字符串STRING1所有匹配正则表达式的子串STRING2连续被替换STRING3。 例如，"foobar".regexpReplace("oo|ar", "")返回“ fb”。', 'REGEXP_REPLACE(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (105, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'OVERLAY(string1 PLACING string2 FROM integer1 [ FOR integer2 ])', '从位置INT1返回一个字符串，该字符串将STRING1的INT2（默认为STRING2的长度）字符替换为STRING2', 'OVERLAY(${1:} PLACING ${2:} FROM ${3:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (106, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'SUBSTRING(string FROM integer1 [ FOR integer2 ])', '返回字符串STRING的子字符串，从位置INT1开始，长度为INT2（默认为结尾）。', 'SUBSTRING${1:} FROM ${2:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (107, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REPLACE(string1, string2, string3)', '返回一个新字符串替换其中出现的所有STRING2与STRING3（非重叠）从STRING1。', 'REPLACE(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (108, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'REGEXP_EXTRACT(string1, string2[, integer])', '从STRING1返回一个字符串，该字符串使用指定的正则表达式STRING2和正则表达式匹配组索引INTEGER1提取。', 'REGEXP_EXTRACT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (109, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'INITCAP(string)', '返回一种新形式的STRING，其中每个单词的第一个字符转换为大写，其余字符转换为小写。', 'INITCAP(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (110, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CONCAT(string1, string2,...)', '返回连接STRING1，STRING2，...的字符串。如果任何参数为NULL，则返回NULL。', 'CONCAT(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (111, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CONCAT_WS(string1, string2, string3,...)', '返回一个字符串，会连接STRING2，STRING3，......与分离STRING1。', 'CONCAT_WS(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (112, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LPAD(string1, integer, string2)', '返回一个新字符串，该字符串从STRING1的左侧填充STRING2，长度为INT个字符。', 'LPAD(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (113, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RPAD(string1, integer, string2)', '返回一个新字符串，该字符串从STRING1右侧填充STRING2，长度为INT个字符。', 'RPAD(${1:} , ${2:} , ${3:} )', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (114, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'FROM_BASE64(string)', '返回来自STRING的base64解码结果；如果STRING为NULL，则返回null 。', 'FROM_BASE64(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (115, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'TO_BASE64(string)', '从STRING返回base64编码的结果；如果STRING为NULL，则返回NULL。', 'TO_BASE64(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (116, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'ASCII(string)', '返回字符串的第一个字符的数值。如果字符串为NULL，则返回NULL。仅在blink planner中支持。', 'ASCII(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (117, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'CHR(integer)', '返回与integer在二进制上等价的ASCII字符。如果integer大于255，我们将首先得到integer的模数除以255，并返回模数的CHR。如果integer为NULL，则返回NULL。仅在blink planner中支持。', 'CHR(${1:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (118, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'DECODE(binary, string)', '使用提供的字符集(''US-ASCII''， ''ISO-8859-1''， ''UTF-8''， ''UTF-16BE''， ''UTF-16LE''， ''UTF-16''之一)将第一个参数解码为字符串。如果任意一个参数为空，结果也将为空。仅在blink planner中支持。', 'DECODE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (119, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'ENCODE(string1, string2)', '使用提供的string2字符集(''US-ASCII''， ''ISO-8859-1''， ''UTF-8''， ''UTF-16BE''， ''UTF-16LE''， ''UTF-16''之一)将string1编码为二进制。如果任意一个参数为空，结果也将为空。仅在blink planner中支持。', 'ENCODE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (120, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'INSTR(string1, string2)', '返回string2在string1中第一次出现的位置。如果任何参数为空，则返回NULL。仅在blink planner中支持。', 'INSTR(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (121, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LEFT(string, integer)', '返回字符串中最左边的整数字符。如果整数为负，则返回空字符串。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'LEFT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (122, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'RIGHT(string, integer)', '返回字符串中最右边的整数字符。如果整数为负，则返回空字符串。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'RIGHT(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (123, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'LOCATE(string1, string2[, integer])', '返回string1在string2中的位置整数之后第一次出现的位置。如果没有找到，返回0。如果任何参数为NULL，则返回NULL仅在blink planner中支持。', 'LOCATE(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (124, 'Function', 'FUN_UDF', 'STRING_FUNCTIONS', 'PARSE_URL(string1, string2[, string3])', '从URL返回指定的部分。string2的有效值包括''HOST''， ''PATH''， ''QUERY''， ''REF''， ''PROTOCOL''， ''AUTHORITY''， ''FILE''和''USERINFO''。如果任何参数为NULL，则返回NULL。仅在blink planner中支持。', 'PARSE_URL(${1:} , ${2:})', '1.12', 0, true, '2021-02-22 15:29:35', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (187, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'MD5(string)', '以32位十六进制数字的字符串形式返回string的MD5哈希值;如果字符串为NULL，则返回NULL。', 'MD5(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (188, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA1(string)', '返回字符串的SHA-1散列，作为一个由40个十六进制数字组成的字符串;如果字符串为NULL，则返回NULL', 'SHA1(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (189, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA224(string)', '以56位十六进制数字的字符串形式返回字符串的SHA-224散列;如果字符串为NULL，则返回NULL。', 'SHA224(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (190, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA256(string)', '以64位十六进制数字的字符串形式返回字符串的SHA-256散列;如果字符串为NULL，则返回NULL。', 'SHA256(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (191, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA384(string)', '以96个十六进制数字的字符串形式返回string的SHA-384散列;如果字符串为NULL，则返回NULL。', 'SHA384(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (192, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA512(string)', '以128位十六进制数字的字符串形式返回字符串的SHA-512散列;如果字符串为NULL，则返回NULL。', 'SHA512(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (193, 'Function', 'FUN_UDF', 'HASH_FUNCTION', 'SHA2(string, hashLength)', '使用SHA-2哈希函数族(SHA-224、SHA-256、SHA-384或SHA-512)返回哈希值。第一个参数string是要散列的字符串，第二个参数hashLength是结果的位长度(224、256、384或512)。如果string或hashLength为NULL，则返回NULL。', 'SHA2(${1:}, ${2:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (194, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COUNT([ ALL ] expression | DISTINCT expression1 [, expression2]*)', '默认情况下或使用ALL时，返回表达式不为空的输入行数。对每个值的唯一实例使用DISTINCT。', 'COUNT( DISTINCT ${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (195, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COUNT(*) COUNT(1)', '返回输入行数。', 'COUNT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (196, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'AVG([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的平均值(算术平均值)。对每个值的唯一实例使用DISTINCT。', 'AVG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (197, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'SUM([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回所有输入行表达式的和。对每个值的唯一实例使用DISTINCT。', 'SUM(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (198, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'MAX([ ALL | DISTINCT ] expression)', '默认情况下或使用关键字ALL，返回表达式在所有输入行中的最大值。对每个值的唯一实例使用DISTINCT。', 'MAX(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (199, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'MIN([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的最小值。对每个值的唯一实例使用DISTINCT。', 'MIN(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (200, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'STDDEV_POP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的总体标准差。对每个值的唯一实例使用DISTINCT。', 'STDDEV_POP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (201, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'STDDEV_SAMP([ ALL | DISTINCT ] expression)', '默认情况下或使用关键字ALL时，返回表达式在所有输入行中的样本标准差。对每个值的唯一实例使用DISTINCT。', 'STDDEV_SAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (202, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VAR_POP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的总体方差(总体标准差的平方)。对每个值的唯一实例使用DISTINCT。', 'VAR_POP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (203, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VAR_SAMP([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，返回表达式在所有输入行中的样本方差(样本标准差的平方)。对每个值的唯一实例使用DISTINCT。', 'VAR_SAMP(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (204, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'COLLECT([ ALL | DISTINCT ] expression)', '默认情况下，或使用关键字ALL，跨所有输入行返回表达式的多集。空值将被忽略。对每个值的唯一实例使用DISTINCT。', 'COLLECT(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (205, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'VARIANCE([ ALL | DISTINCT ] expression)', 'VAR_SAMP的同义词。仅在blink planner中支持。', 'VARIANCE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (206, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'RANK()', '返回值在一组值中的秩。结果是1加上分区顺序中位于当前行之前或等于当前行的行数。这些值将在序列中产生空白。仅在blink planner中支持。', 'RANK()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (207, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'DENSE_RANK()', '返回值在一组值中的秩。结果是1加上前面分配的秩值。与函数rank不同，dense_rank不会在排序序列中产生空隙。仅在blink planner中支持。', 'DENSE_RANK()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (208, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'ROW_NUMBER()', '根据窗口分区中的行顺序，为每一行分配一个惟一的连续数字，从1开始。仅在blink planner中支持。', 'ROW_NUMBER()', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (209, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LEAD(expression [, offset] [, default] )', '返回表达式在窗口中当前行之前的偏移行上的值。offset的默认值是1,default的默认值是NULL。仅在blink planner中支持。', 'LEAD(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (210, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LAG(expression [, offset] [, default])', '返回表达式的值，该值位于窗口中当前行之后的偏移行。offset的默认值是1,default的默认值是NULL。仅在blink planner中支持。', 'LAG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (211, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'FIRST_VALUE(expression)', '返回一组有序值中的第一个值。仅在blink planner中支持。', 'FIRST_VALUE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (212, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LAST_VALUE(expression)', '返回一组有序值中的最后一个值。仅在blink planner中支持。', 'LAST_VALUE(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (213, 'Function', 'FUN_UDF', 'AGGREGATE_FUNCTION', 'LISTAGG(expression [, separator])', '连接字符串表达式的值，并在它们之间放置分隔符值。分隔符没有添加在字符串的末尾。分隔符的默认值是''，''。仅在blink planner中支持。', 'LISTAGG(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (214, 'Function', 'FUN_UDF', 'COLUMN_FUNCTION', 'withColumns(…)', '选择的列', 'withColumns(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (215, 'Function', 'FUN_UDF', 'COLUMN_FUNCTION', 'withoutColumns(…)', '不选择的列', 'withoutColumns(${1:})', '1.12', 0, true, '2021-02-22 15:46:48', '2023-12-28 00:09:00', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (216, 'Function', 'FUN_UDF', 'COMPARE_FUNCTION', 'value1 = value2', '如果value1等于value2 返回true; 如果value1或value2为NULL，则返回UNKNOWN 。', '${1:} =${2:}', '1.12', 9, true, '2021-02-22 10:06:49', '2023-12-28 00:08:58', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (217, 'Function', 'FUN_UDF', 'TABLE_AGGREGATE_FUNCTION', 'TO_MAP(string1,object2[, string3])', '将非规则一维表转化为规则二维表，string1是key。string2是value。string3为非必填项，表示key的值域（维度），用英文逗号分割。', 'TO_MAP(${1:})', '1.12', 8, true, '2021-05-20 19:59:22', '2023-12-28 00:10:10', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (218, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE print', 'Whole library synchronization print', 'EXECUTE CDCSOURCE demo_print WITH ( ''connector'' = ''mysql-cdc'', @@ -1726,7 +1726,7 @@ VALUES (218, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE print', ''table-name'' = ''test\.student,test\.score'', ''sink.connector'' = ''print'' );', 'All Versions', 0, true, '2023-10-31 16:01:45', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (219, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE doris', 'Whole library synchronization doris', 'EXECUTE CDCSOURCE demo_print WITH ( ''connector'' = ''mysql-cdc'', @@ -1740,7 +1740,7 @@ VALUES (219, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE doris', ''table-name'' = ''test\.student,test\.score'', ''sink.connector'' = ''print'' );', 'All Versions', 0, true, '2023-10-31 16:02:21', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (220, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_doris_schema_evolution', 'The entire library is synchronized to doris tape mode evolution', 'EXECUTE CDCSOURCE demo_doris_schema_evolution WITH ( @@ -1763,7 +1763,7 @@ VALUES (220, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_do ''sink.sink.db'' = ''test'', ''sink.table.identifier'' = ''${schemaName}.${tableName}'' );', 'All Versions', 0, true, '2023-10-31 16:04:53', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (230, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2hive', 'The entire library is synchronized to the sql-catalog of hive', 'EXECUTE CDCSOURCE mysql2hive WITH ( @@ -1782,7 +1782,7 @@ VALUES (230, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2h ''sink.default-database'' = ''hdb'', ''sink.hive-conf-dir'' = ''/usr/local/dlink/hive-conf'' );', 'All Versions', 0, true, '2023-10-31 16:14:31', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (231, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2paimon', 'The entire library is synchronized to paimon', 'EXECUTE CDCSOURCE mysql2paimon WITH ( @@ -1800,7 +1800,7 @@ VALUES (231, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2 ''sink.catalog.type'' = ''table-store'', ''sink.catalog.warehouse''=''file:/tmp/table_store'' );', 'All Versions', 0, true, '2023-10-31 16:15:22', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (221, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE StarRocks ', 'The entire library is synchronized to StarRocks ', 'EXECUTE CDCSOURCE demo_hudi WITH ( @@ -1844,7 +1844,7 @@ VALUES (221, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE StarRoc ''sink.hive_sync.table''=''${tableName}'', ''sink.table.prefix.schema''=''true'' );', 'All Versions', 0, true, '2023-10-31 16:05:50', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (222, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_mysql', 'The entire library is synchronized to mysql', 'EXECUTE CDCSOURCE demo_startrocks WITH ( @@ -1873,7 +1873,7 @@ VALUES (222, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_mys ''sink.sink.buffer-flush.interval-ms'' = ''15000'', ''sink.sink.parallelism'' = ''1'' );', 'All Versions', 0, true, '2023-10-31 16:07:08', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (223, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_doris', 'The entire library is synchronized to mysql', 'EXECUTE CDCSOURCE cdc_mysql WITH ( @@ -1900,7 +1900,7 @@ VALUES (223, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_do ''sink.sink.max-retries'' = ''5'', ''sink.auto.create'' = ''true'' );', 'All Versions', 0, true, '2023-10-31 16:07:47', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (224, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_oracle', 'The entire library is synchronized to cdc_oracle', 'EXECUTE CDCSOURCE cdc_oracle WITH ( @@ -1920,7 +1920,7 @@ VALUES (224, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_ora ''password'' = ''123456'', ''table-name'' = ''TEST2.${tableName}'' );', 'All Versions', 0, true, '2023-10-31 16:08:30', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (225, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kafka_one', 'The entire library is synchronized to a topic in kafka', 'EXECUTE CDCSOURCE cdc_kafka_one WITH ( @@ -1937,7 +1937,7 @@ VALUES (225, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kaf ''sink.topic''=''cdctest'', ''sink.brokers''=''bigdata2:9092,bigdata3:9092,bigdata4:9092'' );', 'All Versions', 0, true, '2023-10-31 16:10:13', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (226, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kafka_mul', 'The entire library is synchronized to a single topic in kafka', 'EXECUTE CDCSOURCE cdc_kafka_mul WITH ( @@ -1953,7 +1953,7 @@ VALUES (226, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_kaf ''sink.connector''=''datastream-kafka'', ''sink.brokers''=''bigdata2:9092,bigdata3:9092,bigdata4:9092'' )', 'All Versions', 0, true, '2023-10-31 16:10:59', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (227, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_upsert_kafka', 'The entire library is synchronized to kafka primary key mode', 'EXECUTE CDCSOURCE cdc_upsert_kafka WITH ( @@ -1972,7 +1972,7 @@ VALUES (227, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_ups ''sink.key.format'' = ''json'', ''sink.value.format'' = ''json'' );', 'All Versions', 0, true, '2023-10-31 16:12:14', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (228, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_postgresql ', 'The entire library is synchronized to postgresql', 'EXECUTE CDCSOURCE cdc_postgresql WITH ( @@ -1998,7 +1998,7 @@ VALUES (228, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_pos ''sink.sink.buffer-flush.max-rows'' = ''100'', ''sink.sink.max-retries'' = ''5'' )', 'All Versions', 0, true, '2023-10-31 16:12:54', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (229, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_clickhouse', 'Sync the entire library to clickhouse', 'EXECUTE CDCSOURCE cdc_clickhouse WITH ( @@ -2024,7 +2024,7 @@ VALUES (229, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE cdc_cli ''sink.sink.flush-interval'' = ''1000'', ''sink.sink.max-retries'' = ''3'' );', 'All Versions', 0, true, '2023-10-31 16:13:33', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (232, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2dinky_catalog', 'The entire library is synchronized to dinky''s built-in catalog', 'EXECUTE CDCSOURCE mysql2dinky_catalog WITH ( @@ -2045,7 +2045,7 @@ VALUES (232, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2d ''sink.catalog.url'' = ''jdbc:mysql://127.0.0.1:3306/dlink?useUnicode=true&characterEncoding=utf8&serverTimezone=UTC'', ''sink.sink.db'' = ''default_database'' );', 'All Versions', 0, true, '2023-10-31 16:16:22', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (233, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2multiple_sink', 'Synchronization of the entire library to multiple data sources (sink)', 'EXECUTE CDCSOURCE mysql2multiple_sink WITH ( @@ -2075,19 +2075,19 @@ VALUES (233, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE mysql2m ''sink[1].topic''=''cdc'', ''sink[1].brokers''=''127.0.0.1:9092'' )', 'All Versions', 0, true, '2023-10-31 16:17:27', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (234, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'ADD JAR', 'ADD JAR', 'ADD JAR ${1:}; -- str path ', 'All Versions', 0, true, '2023-10-31 16:19:52', '2023-12-28 00:02:02', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (235, 'Function', 'Other', 'Other', 'SHOW FRAGMENTS', 'SHOW FRAGMENTS', 'SHOW FRAGMENTS;', 'All Versions', 0, true, '2023-10-31 16:20:30', '2023-12-28 09:57:55', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (236, 'Function', 'Other', 'Other', 'SHOW FRAGMENT var1', 'SHOW FRAGMENT var1', 'SHOW FRAGMENT ${1:};', 'All Versions', 0, true, '2023-10-31 16:21:23', '2023-12-28 09:57:54', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (237, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_hudi', 'The entire library is synchronized to hudi', 'EXECUTE CDCSOURCE demo_hudi WITH ( @@ -2131,7 +2131,7 @@ VALUES (237, 'Reference', 'SQL_TEMPLATE', 'FlinkCDC', 'EXECUTE CDCSOURCE demo_hu ''sink.hive_sync.table''=''${tableName}'', ''sink.table.prefix.schema''=''true'' );', 'All Versions', 0, true, '2023-10-31 16:24:47', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (238, 'Reference', 'SQL_TEMPLATE', 'FlinkJar', 'EXECUTE JAR ', 'EXECUTE JAR use sql', 'EXECUTE JAR WITH ( ''uri''=''rs:///jar/flink/demo/SocketWindowWordCount.jar'', @@ -2140,11 +2140,11 @@ VALUES (238, 'Reference', 'SQL_TEMPLATE', 'FlinkJar', 'EXECUTE JAR ', 'EXECUTE J ''parallelism''='''', ''savepoint-path''='''' );', 'All Versions', 0, true, '2023-10-31 16:27:53', '2023-12-28 09:57:54', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (239, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'PRINT tablename', 'PRINT table data', 'PRINT ${1:}', 'All Versions', 0, true, '2023-10-31 16:30:22', '2023-12-28 00:09:39', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (240, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE Like', 'CREATE TABLE Like source table', 'DROP TABLE IF EXISTS sink_table; CREATE TABLE IF not EXISTS sink_table @@ -2152,7 +2152,7 @@ WITH ( ''topic'' = ''motor_vehicle_error'' ) LIKE source_table;', 'All Versions', 0, true, '2023-10-31 16:33:38', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (241, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE like source_table EXCLUDING', 'CREATE TABLE like source_table EXCLUDING', 'DROP TABLE IF EXISTS sink_table; @@ -2169,7 +2169,7 @@ LIKE source_table ( EXCLUDING ALL INCLUDING GENERATED );', 'All Versions', 0, true, '2023-10-31 16:36:13', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (242, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE ctas_kafka', 'CREATE TABLE ctas_kafka', 'CREATE TABLE my_ctas_table WITH ( @@ -2177,7 +2177,7 @@ WITH ( ) AS SELECT id, name, age FROM source_table WHERE mod(id, 10) = 0;', 'All Versions', 0, true, '2023-10-31 16:37:33', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (243, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'CREATE TABLE rtas_kafka', 'CREATE TABLE rtas_kafka', 'CREATE OR REPLACE TABLE my_ctas_table WITH ( @@ -2185,7 +2185,7 @@ WITH ( ) AS SELECT id, name, age FROM source_table WHERE mod(id, 10) = 0;', 'All Versions', 0, true, '2023-10-31 16:41:46', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (244, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'datagen job demo', 'datagen job demo', 'DROP TABLE IF EXISTS source_table3; CREATE TABLE IF NOT EXISTS source_table3( @@ -2240,7 +2240,7 @@ ORDER BY order_time RANGE BETWEEN INTERVAL ''1'' MINUTE PRECEDING AND CURRENT ROW ) as one_minute_sum FROM source_table3;', 'All Versions', 0, true, '2023-11-15 15:42:16', '2023-12-28 00:02:57', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (245, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'checkpoint config', 'checkpoint config', '-- 声明一些调优参数 (checkpoint 等相关配置) set ''execution.checkpointing.checkpoints-after-tasks-finish.enabled'' =''true''; @@ -2254,7 +2254,7 @@ set ''state.checkpoints.num-retained''=''100''; -- 使 solt 均匀分布在 各个 TM 上 set ''cluster.evenly-spread-out-slots''=''true'';', 'All Versions', 0, true, '2023-11-15 15:57:42', '2023-12-28 15:49:20', NULL, NULL); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (246, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'note template', 'note template', '-- ----------------------------------------------------------------- -- @Description(作业描述): ${1:} @@ -2263,7 +2263,7 @@ VALUES (246, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'note template', 'note tem -- ----------------------------------------------------------------- ${4:}', 'All Versions', 0, true, '2023-11-17 17:03:24', '2023-12-28 12:05:20', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (247, 'Reference', 'SQL_TEMPLATE', 'FlinkSql', 'dinky_paimon_auto_create_table', 'dinky paimon auto create table', '-- ----------------------------------------------------------------- @@ -2287,29 +2287,29 @@ WITH ''sink.path'' = ''hdfs:/tmp/paimon/#{schemaName}.db/#{tableName}'', ''sink.auto-create'' = ''true'', );', 'All Versions', 0, true, '2023-12-27 16:53:37', '2023-12-28 12:05:20', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (248, 'Reference', 'FUN_UDF', 'OTHER_FUNCTION', 'add-customjar', 'add CUSTOMJAR 为 Dinky 扩展语法 功能实现和 add jar 类似 , 推荐使用此方式', '-- add CUSTOMJAR 为 Dinky 扩展语法 功能实现和 add jar 类似 , 推荐使用此方式 add CUSTOMJAR ''${1:}'';', 'All Versions', 0, true, '2023-12-28 10:50:17', '2023-12-28 15:49:40', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (249, 'Property', 'FLINK_OPTIONS', 'FlinkSql', 'restart-strategy', '重启策略', 'fixed-delay', '1.15', 0, true, '2024-03-01 15:10:31', '2024-03-01 15:10:31', 1, 1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (250,'Variable','FLINK_OPTIONS','','s3.endpoint',NULL,'''s3.endpoint'' = ''http://localhost:9000''', 'All Versions',0,true,'2025-03-24 18:04:05','2025-03-26 09:01:39',1,1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (251,'Variable','FLINK_OPTIONS','','s3.access-key',NULL,'''s3.access-key'' = ''minio''','All Versions',0,true, '2025-03-24 18:08:07','2025-03-26 09:02:50',1,1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (252,'Variable','FLINK_OPTIONS','','s3.secret-key',NULL,'''s3.secret-key'' = ''your_s3_secret_key''', 'All Versions',0,true,'2025-03-24 18:08:32','2025-03-26 09:04:32',1,1); -INSERT INTO public.dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, +INSERT INTO dinky_flink_document (id, category, type, subtype, name, description, fill_value, version, like_num, enabled, create_time, update_time, creator, updater) VALUES (253,'Variable','FLINK_OPTIONS','','s3.path.style.access',NULL,'''s3.path.style.access'' = ''true''', 'All Versions',0,true,'2025-03-24 18:09:00','2025-03-26 09:04:58',1,1); @@ -4138,31 +4138,31 @@ EXECUTE FUNCTION trigger_set_timestamp(); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (3, 'alert.rule.jobFail', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''FAILED''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (4, 'alert.rule.getJobInfoFail', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''UNKNOWN''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (5, 'alert.rule.jobRestart', '[{"ruleKey":"jobStatus","ruleOperator":"EQ","ruleValue":"''RESTARTING''","rulePriority":"1"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (6, 'alert.rule.checkpointFail', '[{"ruleKey":"isCheckpointFailed","ruleOperator":"EQ","ruleValue":"true"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, +INSERT INTO dinky_alert_rules (id, name, rule, template_id, rule_type, trigger_conditions, description, enabled, create_time, update_time, creator, updater) VALUES (7, 'alert.rule.jobRunException', '[{"ruleKey":"isException","ruleOperator":"EQ","ruleValue":"true"}]', 1, 'SYSTEM', ' or ', '', 1, '1970-01-01 00:00:00', '2023-11-22 17:03:44', null, null); -INSERT INTO public.dinky_alert_template +INSERT INTO dinky_alert_template VALUES (1, 'Default', ' - **Job Name :** ${jobName} - **Job Status :** ${jobStatus}