文章目录
简介
本文介绍了通过 Flink CDC + Flink SQL 同步 MySQL 数据到 ElasticSearch 的案例。案例包含了 Insert/Update/Delete 的操作。
系统环境和软件版本
Ubuntu 20.04
JDK 1.8
Maven 3.6.3
Flink 1.13.6
ElasticSearch 7.16.2
MySQL 测试数据准备
mysql> CREATE DATABASE mydb;
mysql> USE mydb;
mysql> CREATE TABLE products (
id INTEGER NOT NULL AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(255) NOT NULL,
description VARCHAR(512)
);
mysql> INSERT INTO products VALUES (default,"scooter1","Small 1-wheel scooter");
Query OK, 1 row affected (0.01 sec)
ElasticSearch 安装
1. 安装包选择和下载
官网下载地址：
https://www.elastic.co/cn/downloads/past-releases/elasticsearch-7-16-2
根据自己的操作系统（和芯片）选择一个合适的安装包。苹果M1芯片或者在苹果M1芯片安装的虚拟机都是选择后缀ARRCH64的安装包。
笔者当前的系统环境是基于苹果M1芯片安装Ubuntu 20.04操作系统，因此选择了 LINUX ARRCH64 的安装包。
下载命令
axel -n 20 https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.16.2-linux-aarch64.tar.gz
2. 解压
tar xvf elasticsearch-7.16.2-linux-aarch64.tar.gz
3. 启动 ElasticeSearch
cd elasticsearch-7.16.2
bin/elasticsearch
4. 验证是否启动成功
curl http://localhost:9200
如下图所示，说明启动成功了
Flink 集群准备
1. 下载 flink 1.13.6 的二进制安装包
axel -n 20 https://archive.apache.org/dist/flink/flink-1.13.6/flink-1.13.6-bin-scala_2.11.tgz
2. 解压
tar xvf flink-1.13.6-bin-scala_2.11.tgz
3. 将flink-sql-connector-mysql-cdc-2.2-SNAPSHOT.jar 拷贝到 flink lib 目录下，该文件由 Flink CDC 源码编译得到
cp /opt/flink-cdc-connectors/flink-sql-connector-mysql-cdc/target/flink-sql-connector-mysql-cdc-2.2-SNAPSHOT.jar /opt/flink-1.13.6/lib
如何通过 Flink CDC 源码编译得到 flink-sql-connector-mysql-cdc-2.2-SNAPSHOT.jar，请参考：
《Flink CDC 系列（2）—— Flink CDC 源码编译》
4. 修改 /opt/flink-1.13.6/conf/workers
vi /opt/flink-1.13.6/conf/workers
workers文件内容：
localhost
localhost
意思是要在本机启动两个work进程
5. 修改 /opt/flink-1.13.6/conf/flink-conf.yaml
vi /opt/flink-1.13.6/conf/flink-conf.yaml
设置参数： taskmanager.numberOfTaskSlots: 2
6. 下载 flink hadoop uber jar 文件
flink-shaded-hadoop-2-uber-2.7.5-10.0.jar， 文件拷贝到 /opt/flink-1.13.6/lib 目录下
7. 下载 flink elasticsearch connector jar 文件
flink-sql-connector-elasticsearch7_2.11-1.13.6.jar
，文件拷贝到 /opt/flink-1.13.6/lib 目录下
8. 启动单机集群
cd /opt/flink-1.13.6
bin/start-cluster.sh
9. 查看 jobmanager 和 taskmanager 的进程是否存活
$ jps -m
9824 Jps -m
9143 TaskManagerRunner --configDir /opt/flink-1.13.6/conf -D taskmanager.memory.network.min=67108864b -D taskmanager.cpu.cores=2.0 -D taskmanager.memory.task.off-heap.size=0b -D taskmanager.memory.jvm-metaspace.size=268435456b -D external-resources=none -D taskmanager.memory.jvm-overhead.min=201326592b -D taskmanager.memory.framework.off-heap.size=134217728b -D taskmanager.memory.network.max=67108864b -D taskmanager.memory.framework.heap.size=134217728b -D taskmanager.memory.managed.size=241591914b -D taskmanager.memory.task.heap.size=26843542b -D taskmanager.numberOfTaskSlots=2 -D taskmanager.memory.jvm-overhead.max=201326592b
8875 StandaloneSessionClusterEntrypoint --configDir /opt/flink-1.13.6/conf --executionMode cluster -D jobmanager.memory.off-heap.size=134217728b -D jobmanager.memory.jvm-overhead.min=201326592b -D jobmanager.memory.jvm-metaspace.size=268435456b -D jobmanager.memory.heap.size=469762048b -D jobmanager.memory.jvm-overhead.max=201326592b
9403 TaskManagerRunner --configDir /opt/flink-1.13.6/conf -D taskmanager.memory.network.min=67108864b -D taskmanager.cpu.cores=2.0 -D taskmanager.memory.task.off-heap.size=0b -D taskmanager.memory.jvm-metaspace.size=268435456b -D external-resources=none -D taskmanager.memory.jvm-overhead.min=201326592b -D taskmanager.memory.framework.off-heap.size=134217728b -D taskmanager.memory.network.max=67108864b -D taskmanager.memory.framework.heap.size=134217728b -D taskmanager.memory.managed.size=241591914b -D taskmanager.memory.task.heap.size=26843542b -D taskmanager.numberOfTaskSlots=2 -D taskmanager.memory.jvm-overhead.max=201326592b
9727 TaskManagerRunner --configDir /opt/flink-1.13.6/conf -D taskmanager.memory.network.min=67108864b -D taskmanager.cpu.cores=2.0 -D taskmanager.memory.task.off-heap.size=0b -D taskmanager.memory.jvm-metaspace.size=268435456b -D external-resources=none -D taskmanager.memory.jvm-overhead.min=201326592b -D taskmanager.memory.framework.off-heap.size=134217728b -D taskmanager.memory.network.max=67108864b -D taskmanager.memory.framework.heap.size=134217728b -D taskmanager.memory.managed.size=241591914b -D taskmanager.memory.task.heap.size=26843542b -D taskmanager.numberOfTaskSlots=2 -D taskmanager.memory.jvm-overhead.max=201326592b
ubuntu@ubuntu:/opt/flink-1.13.6$
演示开始
1. 启动 Flink SQL Client
cd /opt/flink-1.13.6
bin/sql-client.sh
2. 在 Flink SQL Client 中执行 DDL 和 查询
-- 创建 mysql-cdc source
Flink SQL> CREATE TABLE products (
id INT,
name STRING,
description STRING,
PRIMARY KEY (id) NOT ENFORCED
) WITH (
'connector' = 'mysql-cdc',
'hostname' = '192.168.64.6',
'port' = '3306',
'username' = 'test',
'password' = 'test',
'database-name' = 'mydb',
'table-name' = 'products'
);
[INFO] Execute statement succeed.
Flink SQL> select * from products;
id name description
1 scooter1 Small 1-wheel scooter
Flink SQL> CREATE TABLE products_es_sink (
id INT,
name STRING,
description STRING,
PRIMARY KEY (id) NOT ENFORCED
) WITH (
'connector' = 'elasticsearch-7',
'hosts' = 'http://localhost:9200',
'index' = 'products'
);
[INFO] Execute statement succeed.
Flink SQL> insert into products_es_sink select * from products;
[INFO] Submitting SQL update statement to the cluster...
[INFO] SQL update statement has been successfully submitted to the cluster:
Job ID: b962baa7f6a8890cc45e43a7c95765d2
3. 查看 Elasticearch Index 的数据
curl http://localhost:9200/products/_search?pretty
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "products",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"id" : 1,
"name" : "scooter1",
"description" : "Small 1-wheel scooter"
}
}
]
}
}
4. 在Mysql客户端插入新的数据
mysql> INSERT INTO products VALUES (default,"scooter2","Small 2-wheel scooter");
5. 查看 Elasticearch Index 的数据
在命令行执行：
curl http://localhost:9200/products/_search?pretty
{
"took" : 433,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "products",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"id" : 1,
"name" : "scooter1",
"description" : "Small 1-wheel scooter"
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"id" : 2,
"name" : "scooter2",
"description" : "Small 2-wheel scooter"
}
}
]
}
}
-- 新数据写到了elasticsearch
6. 在Mysql客户端更新的数据
mysql> update products set name = 'scooter----1' where id = 1;
7. 查看 Elasticearch Index 的数据
在命令行执行：
curl http://localhost:9200/products/_search?pretty
{
"took" : 154,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "products",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"id" : 2,
"name" : "scooter2",
"description" : "Small 2-wheel scooter"
}
},
{
"_index" : "products",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"id" : 1,
"name" : "scooter----1",
"description" : "Small 1-wheel scooter"
}
}
]
}
}
-- id=1的数据被更新到了elasticsearch
7. 在Mysql客户端删除的数据
mysql> delete from products where id = 1;
8. 查看 Elasticearch Index 的数据
在命令行执行：
curl http://localhost:9200/products/_search?pretty
{
"took" : 347,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "products",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"id" : 2,
"name" : "scooter2",
"description" : "Small 2-wheel scooter"
}
}
]
}
}
-- id=1的数据被删除
总结
通过 Flink CDC 可以捕获到 MySQL 的 insert/update/delete 操作日志，并通过 Flink SQL 可对 ElasticSearch 的索引数据进行 insert/update/delete。
