使用最新版flink tidb cdc 同步数据到StarRocks

新发布的Flink CDC 2.2 版本新增了 OceanBase CE，PolarDB-X，SqlServer，TiDB 四种数据源接入。其中新增 OceanBase CDC，SqlServer CDC，TiDB CDC 三个连接器，而 PolarDB-X 的支持则是通过对 MySQL CDC 连接器进行兼容适配实现。

发布原文链接：https://blog.csdn.net/weixin_44904816/article/details/123836091

最近在测tidb原始的ticdc（PingCap提供）导入数据到kafka，再使用flink StarRocks cdc导入到StarRocks过程中碰到较多问题，刚好可以使用flink新发布的flink tidb cdc来对接，实现从tidb快速同步数据到StarRocks。

tidb环境部署

1. 下载tidb部署安装包tidb-community-server-v4.0.9-linux-amd64.tar.gz，下载地址

https://download.pingcap.org/tidb-community-server-v4.0.9-linux-amd64.tar.gz

1. 安装环境

tar -xvf tidb-community-server-v4.0.9-linux-amd64.tar.gz
cd tidb-community-server-v4.0.9-linux-amd64
sh local_install.sh

1. 使用tidb playground模式启动tidb单节点测试环境

sr@cs03:~/.tiup/bin$pwd
/home/disk1/sr/.tiup/bin
sr@cs03:~/.tiup/bin$./tiup playground
Starting component `playground`: /home/disk1/sr/.tiup/components/playground/v1.3.2/tiup-playground
Use the latest stable version: v4.0.9
Specify version manually: tiup playground 
The stable version: tiup playground v4.0.0
The nightly version: tiup playground nightly
Playground Bootstrapping...
Start pd instance
Start tikv instance
Start tidb instance
Waiting for tidb instances ready
127.0.0.1:4000 ... Done
Start tiflash instance
Waiting for tiflash instances ready
127.0.0.1:3930 ... Done
CLUSTER START SUCCESSFULLY, Enjoy it ^-^
To connect TiDB: mysql --host 127.0.0.1 --port 4000 -u root
To view the dashboard: http://127.0.0.1:2379/dashboard
To view the Prometheus: http://127.0.0.1:37449
To view the Grafana: http://127.0.0.1:3000

Flink tidb cdc connector下载

下载flink tidb cdc connector，放在flink lib下：

wget https://repo1.maven.org/maven2/com/ververica/flink-sql-connector-tidb-cdc/2.2.0/flink-sql-connector-tidb-cdc-2.2.0.jar

sr@cs03:~/app/flink-1.13.3/lib$pwd
/home/disk1/sr/app/flink-1.13.3/lib
sr@cs03:~/app/flink-1.13.3/lib$ll
total 353940
-rw-rw-r-- 1 sr sr 9404460 Mar 19 17:29 flink-connector-starrocks-1.2.1_flink-1.13_2.12.jar
-rw-r--r-- 1 sr sr 92313 Oct 13 2021 flink-csv-1.13.3.jar
-rw-r--r-- 1 sr sr 115418686 Oct 13 2021 flink-dist_2.11-1.13.3.jar
-rw-r--r-- 1 sr sr 19583 Nov 5 21:27 flink-format-changelog-json-1.4.0.jar
-rw-r--r-- 1 sr sr 148127 Oct 13 2021 flink-json-1.13.3.jar
-rw-rw-r-- 1 sr sr 41368997 Feb 12 2020 flink-shaded-hadoop-2-uber-2.7.5-10.0.jar.bak
-rwxrwxr-x 1 sr sr 7709740 Jun 8 2021 flink-shaded-zookeeper-3.4.14.jar
-rw-rw-r-- 1 sr sr 3674114 Oct 12 2021 flink-sql-connector-kafka_2.12-1.13.3.jar
-rw-rw-r-- 1 sr sr 19648014 Dec 16 23:36 flink-sql-connector-mysql-cdc-2.1.1.jar
-rw-rw-r-- 1 sr sr 85355380 Apr 19 17:03 flink-sql-connector-tidb-cdc-2.2.0.jar
-rw-r--r-- 1 sr sr 36453353 Oct 13 2021 flink-table_2.11-1.13.3.jar
-rw-r--r-- 1 sr sr 41061738 Oct 13 2021 flink-table-blink_2.11-1.13.3.jar
-rwxrwxr-x 1 sr sr 67114 Mar 31 2021 log4j-1.2-api-2.12.1.jar
-rwxrwxr-x 1 sr sr 276771 Mar 31 2021 log4j-api-2.12.1.jar
-rwxrwxr-x 1 sr sr 1674433 Mar 31 2021 log4j-core-2.12.1.jar
-rwxrwxr-x 1 sr sr 23518 Mar 31 2021 log4j-slf4j-impl-2.12.1.jar

Yarn session模式启动flink集群

sr@cs03:~/app/flink-1.13.3/bin$./yarn-session.sh
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/disk1/sr/app/flink-1.13.3/lib/log4j-slf4j-impl-2.12.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
......
......
...... ​​​​​​​
2022-04-19 17:23:39,069 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl [] - Submitted application application_1641365150688_0057
2022-04-19 17:23:39,070 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Waiting for the cluster to be allocated
2022-04-19 17:23:39,071 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Deploying cluster, current state ACCEPTED
2022-04-19 17:23:44,097 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - YARN application has been deployed successfully.
2022-04-19 17:23:44,159 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Found Web Interface cs03:38081 of application 'application_1641365150688_0057'.
JobManager Web Interface: http://cs03:38081

tidb环境建表，插入数据，更新等

mysql> create database gong;
mysql> use gong;
mysql> CREATE TABLE orders (
-> order_id INT,
-> order_date TIMESTAMP(3),
-> customer_name varchar(20),
-> price DECIMAL(10, 5),
-> product_id INT,
-> order_status BOOLEAN,
-> PRIMARY KEY(order_id)
-> ) ;
mysql> insert into orders values(1,now(),"gong",13.99,123,1);
Query OK, 1 row affected (0.00 sec)
mysql> insert into orders values(2,now(),"gong",13.99,123,1);
Query OK, 1 row affected (0.00 sec)
mysql> insert into orders values(3,now(),"gong",13.99,123,1);
Query OK, 1 row affected (0.00 sec)
mysql> insert into orders values(4,now(),"gong",13.99,123,1);
Query OK, 1 row affected (0.01 sec)
......
......
mysql> insert into orders values(12,now(),"gong",13.99,123,1);
Query OK, 1 row affected (0.00 sec)
mysql> SELECT * FROM ORDERS;
+----------+-------------------------+---------------+----------+------------+--------------+
| order_id | order_date | customer_name | price | product_id | order_status |
+----------+-------------------------+---------------+----------+------------+--------------+
| 1 | 2022-04-19 17:12:33.000 | gong | 13.99000 | 123 | 1 |
| 2 | 2022-04-19 17:14:20.000 | gong | 13.99000 | 123 | 1 |
| 3 | 2022-04-19 17:14:25.000 | gong | 13.99000 | 123 | 1 |
| 4 | 2022-04-19 17:14:46.000 | gong | 13.99000 | 123 | 1 |
......
......
| 12 | 2022-04-19 17:20:37.000 | gong | 13.99000 | 123 | 1 |
+----------+-------------------------+---------------+----------+------------+--------------+
mysql> update orders set customer_name = "xxxxxx" where order_id = 12;
Query OK, 1 row affected (0.02 sec)
Rows matched: 1 Changed: 1 Warnings: 0

测试tidb数据到flink sql

开启flink sql：

cd $FLINK_HOME/bin
./sql_client.sh embedded

-- checkpoint every 3000 milliseconds
Flink SQL> SET 'execution.checkpointing.interval' = '3s';
-- register a TiDB table 'orders' in Flink SQL
Flink SQL> CREATE TABLE orders (
order_id INT,
order_date TIMESTAMP(3),
customer_name STRING,
price DECIMAL(10, 5),
product_id INT,
order_status BOOLEAN,
PRIMARY KEY(order_id) NOT ENFORCED
) WITH (
'connector' = 'tidb-cdc',
'tikv.grpc.timeout_in_ms' = '20000',
'pd-addresses' = 'localhost:2379',
'database-name' = 'gong',
'table-name' = 'orders'
);
-- read snapshot and binlogs from orders table
Flink SQL> SELECT * FROM orders;

check生成了flink任务正常运行（经常会碰到提交任务失败）：

sr@cs03:~/app/flink-1.13.3/bin$./flink list
SLF4J: Class path contains multiple SLF4J bindings
......
......
2022-04-19 18:16:02,146 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Found Web Interface cs03:38081 of application 'application_1641365150688_0057'.
Waiting for response...
------------------ Running/Restarting Jobs -------------------
19.04.2022 17:25:27 : 4852d0bdb40aba6ae4041f1e36eadd1c : collect (RUNNING)
--------------------------------------------------------------

 从flink sql cli能查询出数据，说明数据flow到flink已经打通，再后面就是对接导入到StarRocks；

对接StarRocks，将数据写入到StarRocks

在StarRocks建表

CREATE TABLE `orders` ( 
`order_id` int(11) NOT NULL COMMENT "",
`order_date` datetime NULL COMMENT "",
`customer_name` varchar(20) NULL COMMENT "",
`price` decimal64(10, 5) NULL COMMENT "",
`product_id` int(11) NULL COMMENT "",
`order_status` boolean NULL COMMENT ""
) ENGINE=OLAP
PRIMARY KEY(`order_id`)
COMMENT "OLAP"
DISTRIBUTED BY HASH(`order_id`) BUCKETS 1
PROPERTIES (
"replication_num" = "3",
"in_memory" = "false",
"storage_format" = "DEFAULT"
);

使用Flink sql将数据同步到StarRocks

先将flink StarRocks cdc 依赖包 flink-connector-starrocks-1.2.1_flink-1.13_2.12.jar下载好，放到flink lib目录下,重启flink服务；(下载链接 Flink StarRocks connector，请注意1.13版本和1.11/1.12版本使用不同的connector）

在flink sql cli端

CREATE TABLE IF NOT EXISTS `orders_sink` (
order_id INT,
order_date TIMESTAMP(3),
customer_name varchar(20),
price DECIMAL(10, 5),
product_id INT,
order_status BOOLEAN,
PRIMARY KEY(`order_id`) NOT ENFORCED
) with (
'load-url' = 'cs01:9011',
'sink.buffer-flush.interval-ms' = '15000',
'sink.properties.row_delimiter' = '\x02',
'sink.properties.column_separator' = '\x01',
'connector' = 'starrocks',
'database-name' = 'gong',
'table-name' = 'orders',
'jdbc-url' = 'jdbc:mysql://cs01:9013',
'password' = '',
'username' = 'root'
);
Flink SQL> show tables;
+-------------+
| table name |
+-------------+
| orders |
| orders_sink |
+-------------+
2 rows in set

将数据插入到StarRocks

Flink SQL> insert into orders_sink select * from orders;
[INFO] Submitting SQL update statement to the cluster...
2022-04-19 18:37:14,581 INFO org.apache.hadoop.yarn.client.RMProxy [] - Connecting to ResourceManager at /172.26.194.184:38035
2022-04-19 18:37:14,582 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2022-04-19 18:37:14,587 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Found Web Interface cs03:38081 of application 'application_1641365150688_0057'.
[INFO] SQL update statement has been successfully submitted to the cluster:
Job ID: 33b03fb9d257b57c5243e721c19a6041

查看新flink sql生成的任务：

sr@cs03:~/app/flink-1.13.3/bin$./flink list
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/disk1/sr/app/flink-1.13.3/lib/log4j-slf4j-impl-2.12.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
......
......
2022-04-19 18:37:46,875 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - No path for the flink jar passed. Using the location of class org.apache.flink.yarn.YarnClusterDescriptor to locate the jar
2022-04-19 18:37:46,953 INFO org.apache.flink.yarn.YarnClusterDescriptor [] - Found Web Interface cs03:38081 of application 'application_1641365150688_0057'.
Waiting for response...
------------------ Running/Restarting Jobs -------------------
19.04.2022 18:37:14 : 33b03fb9d257b57c5243e721c19a6041 : insert-into_default_catalog.default_database.orders_sink (RUNNING)
--------------------------------------------------------------
No scheduled jobs.

在StarRocks验证变更数据是否都已经进去了

mysql> select current_version(); 
+-------------------+
| current_version() |
+-------------------+
| 2.1.0 1864de0 |
+-------------------+
1 row in set (0.02 sec)
mysql> select * from orders;
+----------+---------------------+---------------+----------+------------+--------------+
| order_id | order_date | customer_name | price | product_id | order_status |
+----------+---------------------+---------------+----------+------------+--------------+
| 1 | 2022-04-19 09:12:33 | gong | 13.99000 | 123 | 1 |
| 2 | 2022-04-19 09:14:20 | gong | 13.99000 | 123 | 1 |
| 3 | 2022-04-19 09:14:25 | gong | 13.99000 | 123 | 1 |
| 4 | 2022-04-19 09:14:46 | gong | 13.99000 | 123 | 1 |
......
......
| 12 | 2022-04-19 09:20:37 | gongxiucheng | 13.99000 | 123 | 1 |
| 13 | 2022-04-19 09:26:56 | gong | 13.99000 | 123 | 1 |
| 14 | 2022-04-19 09:33:21 | gong | 13.99000 | 123 | 1 |
| 15 | 2022-04-19 10:08:03 | gong | 13.99000 | 123 | 1 |
+----------+---------------------+---------------+----------+------------+--------------+
15 rows in set (0.01 sec)

总结：

整个测试过程还比较顺滑，比之前测试tidb 原生ticdc少了很多麻烦，且简化整个数据链路，不依赖kafka，是tidb数据到starrocks利器。