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@ -0,0 +1,319 @@
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# 基于 Flink CDC 构建 MySQL 和 Postgres 的 Streaming ETL
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This tutorial is to show how to quickly build streaming ETL for MySQL and Postgres with Flink CDC.
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Assuming we are running an e-commerce business. The product and order data stored in MySQL, the shipment data related to the order is stored in Postgres.
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We want to enrich the orders using the product and shipment table, and then load the enriched orders to ElasticSearch in real time.
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In the following sections, we will describe how to use Flink Mysql/Postgres CDC to implement it.
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All exercises in this tutorial are performed in the Flink SQL CLI, and the entire process uses standard SQL syntax, without a single line of Java/Scala code or IDE installation.
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The overview of the architecture is as follows:
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## Preparation
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Prepare a Linux or MacOS computer with Docker installed.
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### Starting components required
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The components required in this demo are all managed in containers, so we will use `docker-compose` to start them.
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Create `docker-compose.yml` file using following contents:
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```
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version: '2.1'
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services:
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postgres:
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image: debezium/example-postgres:1.1
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ports:
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- "5432:5432"
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environment:
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- POSTGRES_PASSWORD=1234
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- POSTGRES_DB=postgres
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- POSTGRES_USER=postgres
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- POSTGRES_PASSWORD=postgres
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mysql:
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image: debezium/example-mysql:1.1
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ports:
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- "3306:3306"
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environment:
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- MYSQL_ROOT_PASSWORD=123456
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- MYSQL_USER=mysqluser
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- MYSQL_PASSWORD=mysqlpw
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elasticsearch:
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image: elastic/elasticsearch:7.6.0
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environment:
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- cluster.name=docker-cluster
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- bootstrap.memory_lock=true
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- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
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- discovery.type=single-node
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ports:
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- "9200:9200"
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- "9300:9300"
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ulimits:
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memlock:
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soft: -1
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hard: -1
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nofile:
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soft: 65536
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hard: 65536
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kibana:
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image: elastic/kibana:7.6.0
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ports:
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- "5601:5601"
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```
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The Docker Compose environment consists of the following containers:
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- MySQL: the `products`,`orders` tables will be store in the database. They will be joined with data in Postgres to enrich the orders.
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- Postgres: the `shipments` table will be store in the database.
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- Elasticsearch: mainly used as a data sink to store enriched orders.
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- Kibana: used to visualize the data in Elasticsearch.
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To start all containers, run the following command in the directory that contains the `docker-compose.yml` file.
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```shell
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docker-compose up -d
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```
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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.
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We can also visit [http://localhost:5601/](http://localhost:5601/) to see if Kibana is running normally.
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Don’t forget to run the following command to stop all containers after finishing the tutorial:
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```shell
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docker-compose down
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```
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### Preparing Flink and JAR package required
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1. Download [Flink 1.13.2](https://downloads.apache.org/flink/flink-1.13.2/flink-1.13.2-bin-scala_2.11.tgz) and unzip it to the directory `flink-1.13.2`
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2. Download following JAR package required and put them under `flink-1.13.2/lib/`:
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**Download links are available only for stable releases.**
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- [flink-sql-connector-elasticsearch7_2.11-1.13.2.jar](https://repo.maven.apache.org/maven2/org/apache/flink/flink-sql-connector-elasticsearch7_2.11/1.13.2/flink-sql-connector-elasticsearch7_2.11-1.13.2.jar)
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- [flink-sql-connector-mysql-cdc-2.1-SNAPSHOT.jar](https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-mysql-cdc/2.1-SNAPSHOT/flink-sql-connector-mysql-cdc-2.1-SNAPSHOT.jar)
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- [flink-sql-connector-postgres-cdc-2.1-SNAPSHOT.jar](https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-postgres-cdc/2.1-SNAPSHOT/flink-sql-connector-postgres-cdc-2.1-SNAPSHOT.jar)
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### Preparing data in databases
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#### Preparing data in MySQL
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1. Enter mysql's container:
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```shell
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docker-compose exec mysql mysql -uroot -p123456
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```
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2. Create tables and populate data:
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```sql
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-- MySQL
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CREATE DATABASE mydb;
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USE mydb;
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CREATE TABLE products (
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id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY,
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name VARCHAR(255) NOT NULL,
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description VARCHAR(512)
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);
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ALTER TABLE products AUTO_INCREMENT = 101;
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INSERT INTO products
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VALUES (default,"scooter","Small 2-wheel scooter"),
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(default,"car battery","12V car battery"),
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(default,"12-pack drill bits","12-pack of drill bits with sizes ranging from #40 to #3"),
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(default,"hammer","12oz carpenter's hammer"),
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(default,"hammer","14oz carpenter's hammer"),
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(default,"hammer","16oz carpenter's hammer"),
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(default,"rocks","box of assorted rocks"),
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(default,"jacket","water resistent black wind breaker"),
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(default,"spare tire","24 inch spare tire");
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CREATE TABLE orders (
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order_id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY,
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order_date DATETIME NOT NULL,
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customer_name VARCHAR(255) NOT NULL,
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price DECIMAL(10, 5) NOT NULL,
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product_id INTEGER NOT NULL,
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order_status BOOLEAN NOT NULL -- Whether order has been placed
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) AUTO_INCREMENT = 10001;
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INSERT INTO orders
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VALUES (default, '2020-07-30 10:08:22', 'Jark', 50.50, 102, false),
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(default, '2020-07-30 10:11:09', 'Sally', 15.00, 105, false),
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(default, '2020-07-30 12:00:30', 'Edward', 25.25, 106, false);
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```
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#### Preparing data in Postgres
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1. Enter postgres's container:
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```shell
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docker-compose exec postgres psql -h localhost -U postgres
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```
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2. Create tables and populate data
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```sql
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-- PG
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CREATE TABLE shipments (
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shipment_id SERIAL NOT NULL PRIMARY KEY,
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order_id SERIAL NOT NULL,
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origin VARCHAR(255) NOT NULL,
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destination VARCHAR(255) NOT NULL,
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is_arrived BOOLEAN NOT NULL
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);
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ALTER SEQUENCE public.shipments_shipment_id_seq RESTART WITH 1001;
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ALTER TABLE public.shipments REPLICA IDENTITY FULL;
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INSERT INTO shipments
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VALUES (default,10001,'Beijing','Shanghai',false),
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(default,10002,'Hangzhou','Shanghai',false),
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(default,10003,'Shanghai','Hangzhou',false);
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```
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## Starting Flink cluster and Flink SQL CLI
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1. Use the following command to change to the Flink directory:
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```
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cd flink-1.13.2
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```
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2. Change the value of `taskmanager.numberOfTaskSlots` to 2 in `conf/flink-conf.yaml` for we will run two tasks at the same time.
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3. Use the following command to start a Flink cluster:
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```shell
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./bin/start-cluster.sh
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```
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Then we can visit [http://localhost:8081/](http://localhost:8081/) to see if Flink is running normally, and the web page looks like:
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Don’t forget to run the following command to stop the Flink cluster after finishing the tutorial:
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```shell
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./bin/stop-cluster.sh
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```
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4. Use the following command to start a Flink SQL CLI:
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```shell
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./bin/sql-client.sh
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```
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We should see the welcome screen of the CLI client.
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## Creating tables using Flink DDL in Flink SQL CLI
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First, enable checkpoints every 3000 milliseconds
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```sql
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-- Flink SQL
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Flink SQL> SET execution.checkpointing.interval = 3s;
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```
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Then, create tables that capture the change data from the corresponding database tables.
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```sql
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-- Flink SQL
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Flink SQL> CREATE TABLE products (
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id INT,
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name STRING,
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description STRING,
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PRIMARY KEY (id) NOT ENFORCED
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) WITH (
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'connector' = 'mysql-cdc',
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'hostname' = 'localhost',
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'port' = '3306',
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'username' = 'root',
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'password' = '123456',
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'database-name' = 'mydb',
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'table-name' = 'products'
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);
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Flink SQL> CREATE TABLE orders (
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order_id INT,
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order_date TIMESTAMP(0),
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customer_name STRING,
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price DECIMAL(10, 5),
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product_id INT,
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order_status BOOLEAN,
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PRIMARY KEY (order_id) NOT ENFORCED
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) WITH (
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'connector' = 'mysql-cdc',
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'hostname' = 'localhost',
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'port' = '3306',
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'username' = 'root',
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'password' = '123456',
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'database-name' = 'mydb',
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'table-name' = 'orders'
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);
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Flink SQL> CREATE TABLE shipments (
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shipment_id INT,
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order_id INT,
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origin STRING,
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destination STRING,
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is_arrived BOOLEAN,
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PRIMARY KEY (shipment_id) NOT ENFORCED
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) WITH (
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'connector' = 'postgres-cdc',
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'hostname' = 'localhost',
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'port' = '5432',
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'username' = 'postgres',
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'password' = 'postgres',
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'database-name' = 'postgres',
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'schema-name' = 'public',
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'table-name' = 'shipments'
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);
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```
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Finally, create `enriched_orders` table that is used to load data to the Elasticsearch.
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```sql
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-- Flink SQL
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Flink SQL> CREATE TABLE enriched_orders (
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order_id INT,
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order_date TIMESTAMP(0),
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customer_name STRING,
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price DECIMAL(10, 5),
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product_id INT,
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order_status BOOLEAN,
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product_name STRING,
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product_description STRING,
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shipment_id INT,
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origin STRING,
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destination STRING,
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is_arrived BOOLEAN,
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PRIMARY KEY (order_id) NOT ENFORCED
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) WITH (
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'connector' = 'elasticsearch-7',
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'hosts' = 'http://localhost:9200',
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'index' = 'enriched_orders'
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);
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```
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## Enriching orders and load to ElasticSearch
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Use Flink SQL to join the `order` table with the `products` and `shipments` table to enrich orders and write to the Elasticsearch.
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```sql
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-- Flink SQL
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Flink SQL> INSERT INTO enriched_orders
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SELECT o.*, p.name, p.description, s.shipment_id, s.origin, s.destination, s.is_arrived
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FROM orders AS o
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LEFT JOIN products AS p ON o.product_id = p.id
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LEFT JOIN shipments AS s ON o.order_id = s.order_id;
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```
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Now, the enriched orders should be shown in Kibana.
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Visit [http://localhost:5601/app/kibana#/management/kibana/index_pattern](http://localhost:5601/app/kibana#/management/kibana/index_pattern) to create an index pattern `enriched_orders`.
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Visit [http://localhost:5601/app/kibana#/discover](http://localhost:5601/app/kibana#/discover) to find the enriched orders.
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Next, do some change in the databases, and then the enriched orders shown in Kibana will be updated after each step in real time.
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1. Insert a new order in MySQL
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```sql
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--MySQL
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INSERT INTO orders
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VALUES (default, '2020-07-30 15:22:00', 'Jark', 29.71, 104, false);
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```
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2. Insert a shipment in Postgres
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```sql
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--PG
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INSERT INTO shipments
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VALUES (default,10004,'Shanghai','Beijing',false);
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```
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3. Update order status in MySQL
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```sql
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--MySQL
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UPDATE orders SET order_status = true WHERE order_id = 10004;
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```
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4. Update the shipment status in Postgres
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```sql
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--PG
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UPDATE shipments SET is_arrived = true WHERE shipment_id = 1004;
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```
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5. Delete the shipment in Postgres
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```sql
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--MySQL
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DELETE FROM orders WHERE order_id = 10004;
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```
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The changes of enriched orders in Kibana are as follows:
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Jark Wu
3 years ago