Sql

pg_stat_statements is useful to gather performance information about queries so lets add it to our dockerized postgres database. Using docker-compose Using docker-compose we just need to add the following docker-compose.yaml: docker-compose.yml version: '3.5' services: postgres: container_name: postgres_container image: postgres ports: - "5432:5432" volumes: - /var/lib/postgresql/data # used for query profiling, deactivate for enhanced performance command: postgres -c shared_preload_libraries=pg_stat_statements -c pg_stat_statements.track=all -c max_connections=200 environment: POSTGRES_USER: postgres POSTGRES_PASSWORD: thepassword We simply start our Postgres database with docker-compose: ...

A simple setup when two Postgres databases prefilled with schema/data needed. docker-compose.yml version: '3.6' services: postgres1: image: postgres restart: always environment: - DATABASE_HOST=127.0.0.1 - POSTGRES_USER=root - POSTGRES_PASSWORD=root - POSTGRES_DB=root ports: - "15432:15432" volumes: - ./postgres1-init.sql:/docker-entrypoint-initdb.d/docker_postgres_init.sql postgres2: image: postgres restart: always environment: - DATABASE_HOST=127.0.0.1 - POSTGRES_USER=root - POSTGRES_PASSWORD=root - POSTGRES_DB=root ports: - "25432:25432" volumes: - ./postgres2-init.sql:/docker-entrypoint-initdb.d/docker_postgres_init.sql And our sample init scripts: CREATE USER tester WITH PASSWORD 'tester' CREATEDB; CREATE DATABASE testdb WITH OWNER = tester ENCODING = 'UTF8' LC_COLLATE = 'en_US.utf8' LC_CTYPE = 'en_US.utf8' TABLESPACE = pg_default CONNECTION LIMIT = -1; ...

Goals Run WordPress via Docker / Docker-Compose Increase the Upload Filesize Limit Create Docker Compose Configuration Create a docker-compose.yml: version: '3.1' services: wordpress: image: wordpress restart: always ports: - 8080:80 environment: WORDPRESS_DB_HOST: db WORDPRESS_DB_USER: exampleuser WORDPRESS_DB_PASSWORD: examplepass WORDPRESS_DB_NAME: exampledb volumes: - wordpress:/var/www/html db: image: mysql:5.7 restart: always environment: MYSQL_DATABASE: exampledb MYSQL_USER: exampleuser MYSQL_PASSWORD: examplepass MYSQL_RANDOM_ROOT_PASSWORD: '1' volumes: - db:/var/lib/mysql volumes: wordpress: db: Run Docker Compose / Start Containers docker-compose up WARNING: Found orphan containers (wordpress-docker_phpmyadmin_1) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up. Starting wordpress-docker_db_1 ... done Starting wordpress-docker_wordpress_1 ... done Attaching to wordpress-docker_db_1, wordpress-docker_wordpress_1 [..] db_1 | 2021-04-03T18:58:17.247963Z 0 [Note] mysqld: ready for connections. db_1 | Version: '5.7.33' socket: '/var/run/mysqld/mysqld.sock' port: 3306 MySQL Community Server (GPL) ...

When you need to derive meta-models from existing databases and want to create type-safe queries with an elegant, fluent-API, jOOQ definitely is a tool to consider here. In the following tutorial I’d like to demonstrate how to integrate the jOOQ meta-model generator into a Maven build using the jOOQ Maven Plug-in, the Build Helper Maven Plug-in and Maven profiles to finally create a running application to query an existing RDBMS using such a generated meta-model. ...

Querydsl is a framework that allows us to create elegant, type-safe queries for a variety of different data-sources like Java Persistence API (JPA) entities, Java Data Objects (JDO), mongoDB with Morphia, SQL, Hibernate Search up to Lucene. In the following tutorial we’re implementing example queries for different environments – Java Persistence API compared with a JPQL and a criteria API query, mongoDB with Morphia and last but not least for Lucene. ...

Use List of Parameters in Annotation-based Query Possible using MyBatis Dynamic SQL feature package com.hascode.example.mybatis; import org.apache.ibatis.annotations.Mapper; import org.apache.ibatis.annotations.Param; import org.apache.ibatis.annotations.Select; import java.util.List; @Mapper public interface SampleMapper { @Select({"<script>", "SELECT sample.bar", "FROM sampletable sample", "WHERE sample.id IN", "<foreach item='item' index='index' collection='ids'", "open='(' separator=',' close=')'>", "#{item}", "</foreach>", "</script>"}) List<Foo> getSamplesMatchingIds(@Param("ids") List<String> ids); } The mapper may now be used with a list of parameter objects: var samples = sampleMapper.getSamplesMatchingIds(List.of("24059e5b-aa07-424d-855e-50f499b8f697", "65140fc0-fc9f-42d2-9531-5e5d6caeba30")); Call a Procedure package com.hascode.example.mybatis; import org.apache.ibatis.annotations.Mapper; import org.apache.ibatis.annotations.Options; import org.apache.ibatis.annotations.Select; import org.apache.ibatis.mapping.StatementType; @Mapper public interface SampleMapper { @Select("CALL SCHEMA.CL.setScope(#{scope})") @Options(statementType = StatementType.CALLABLE) void setScope(int scope); } ...

Get size of a table SELECT pg_size_pretty(pg_total_relation_size('schemaname.tablename')); Select unique combination of fields / tuples SELECT DISTINCT ON(field1, field2) field1, field2 FROM thetable Select rows where a combination of fields is not unique SELECT columnA, columnB, count(*) AS count FROM thetable GROUP BY columnA, columnB HAVING count(*) > 1 Search for rows with array containing value Assuming, the field appointments has the type date[] SELECT * FROM mtable WHERE appointments @> ARRAY['2023-09-19'::date] ...

Count unique / all values SELECT COUNT(DISTINCT <FIELDNAME>), COUNT(ALL <FIELDNAME>) FROM <TABLE>; Partially anonymize e-mail addresses UPDATE <TABLE_NAME> SET <EMAIL_FIELD>= INSERT( <EMAIL_FIELD>, POSITION('@' IN <EMAIL_FIELD>), 100, CONCAT(FLOOR(1 + (RAND() * 100)),'@hascode.com')) WHERE POSITION('@' IN <EMAIL_FIELD>)>0; Find duplicate entries SELECT COUNT(*), <FIELDNAME> FROM <TABLENAME> GROUP BY <FIELDNAME> HAVING COUNT(*)>1; MySQL Fix Zero Dates for Data Imports Error: ERROR 1067 (42000) at line 1234: Invalid default value for ‘datefield’ In newer MySQL Versions zero in date or zero dates are forbidden .. check this with: ...