Db2 教程

Demo: Db2 CDC to Elasticsearch #

1. Create docker-compose.yml file using following contents:

version: '2.1'
services:
  db2:
    image: ruanhang/db2-cdc-demo:v1
    privileged: true
    ports:
      - 50000:50000
    environment: 
      - LICENSE=accept
      - DB2INSTANCE=db2inst1
      - DB2INST1_PASSWORD=admin
      - DBNAME=testdb    
      - ARCHIVE_LOGS=true
  elasticsearch:
    image: elastic/elasticsearch:7.6.0
    environment:
      - cluster.name=docker-cluster
      - bootstrap.memory_lock=true
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
      - discovery.type=single-node
    ports:
      - "9200:9200"
      - "9300:9300"
    ulimits:
      memlock:
        soft: -1
        hard: -1
      nofile:
        soft: 65536
        hard: 65536
  kibana:
    image: elastic/kibana:7.6.0
    ports:
      - "5601:5601"
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock

The Docker Compose environment consists of the following containers:

  • Db2: db2 server and a pre-populated products table in the database testdb.
  • Elasticsearch: store the result of the products table.
  • Kibana: mainly used to visualize the data in Elasticsearch

To start all containers, run the following command in the directory that contains the docker-compose.yml file.

docker-compose up -d

This command automatically starts all the containers defined in the Docker Compose configuration in a detached mode. Run docker ps to check whether these containers are running properly. You can also visit http://localhost:5601/ to see if Kibana is running normally.

Don’t forget to run the following command to stop all containers after you finished the tutorial:

docker-compose down

2. Download following JAR package to <FLINK_HOME>/lib

Download links are available only for stable releases, SNAPSHOT dependencies need to be built based on master or release branches by yourself.

3. Launch a Flink cluster and start a Flink SQL CLI

Execute following SQL statements in the Flink SQL CLI:

-- Flink SQL
-- checkpoint every 3000 milliseconds                       
Flink SQL> SET execution.checkpointing.interval = 3s;

Flink SQL> CREATE TABLE products (
    ID INT NOT NULL,
    NAME STRING,
    DESCRIPTION STRING,
    WEIGHT DECIMAL(10,3),
    PRIMARY KEY (ID) NOT ENFORCED
  ) WITH (
    'connector' = 'db2-cdc',
    'hostname' = 'localhost',
    'port' = '50000',
    'username' = 'db2inst1',
    'password' = 'admin',
    'database-name' = 'testdb',
    'schema-name' = 'DB2INST1',  
    'table-name' = 'PRODUCTS'
  );
  
Flink SQL> CREATE TABLE es_products (
    ID INT NOT NULL,
    NAME STRING,
    DESCRIPTION STRING,
    WEIGHT DECIMAL(10,3),
    PRIMARY KEY (ID) NOT ENFORCED
 ) WITH (
     'connector' = 'elasticsearch-7',
     'hosts' = 'http://localhost:9200',
     'index' = 'enriched_products_1'
 );

Flink SQL> INSERT INTO es_products SELECT * FROM products;

4. Check result in Elasticsearch

Check the data has been written to Elasticsearch successfully, you can visit Kibana to see the data.

5. Make changes in Db2 and watch result in Elasticsearch

Enter Db2’s container to make some changes in Db2, then you can see the result in Elasticsearch will change after executing every SQL statement:

docker exec -it ${containerId} /bin/bash

su db2inst1

db2 connect to testdb

# enter db2 and execute sqls
db2

UPDATE DB2INST1.PRODUCTS SET DESCRIPTION='18oz carpenter hammer' WHERE ID=106;

INSERT INTO DB2INST1.PRODUCTS VALUES (default,'jacket','water resistent white wind breaker',0.2);

INSERT INTO DB2INST1.PRODUCTS VALUES (default,'scooter','Big 2-wheel scooter ',5.18);

DELETE FROM DB2INST1.PRODUCTS WHERE ID=111;

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