关于Flink:Flink-最佳实践之使用-Canal-同步-MySQL-数据至-TiDB

一. 背景介绍

本文将介绍如何将 MySQL 中的数据，通过 Binlog + Canal 的模式导入到 Kafka 中，继而被 Flink 生产的案例。

为了可能疾速的验证整套流程的功能性，所有的组件都以单机的模式部署。如果手上的物理资源有余，能够将本文中的所有组件一台 4G 1U 的虚拟机环境中。

如果须要在生产环境中部署，倡议将每一个组件替换成高可用的集群部署计划。

其中，咱们独自创立了一套 Zookeeper 单节点环境，Flink、Kafka、Canal 等组件共用这个 Zookeeper 环境。

针对于所有须要 JRE 的组件，如 Flink，Kafka，Canal，Zookeeper，思考到降级 JRE 可能会影响到其余的利用，咱们抉择每个组件独立应用本人的 JRE 环境。

本文分为两个局部，其中，前七大节次要介绍根底环境的搭建，最初一个大节介绍了数据是如何在各个组件中流通的。

数据的流动通过以下组件：

• MySQL 数据源生成 Binlog。
• Canal 读取 Binlog，生成 Canal json，推送到 Kafka 指定的 Topic 中。
• Flink 应用 flink-sql-connector-kafka API，生产 Kafka Topic 中的数据。
• Flink 在通过 flink-connector-jdbc，将数据写入到 TiDB 中。

TiDB + Flink 的构造，反对开发与运行多种不同品种的应用程序。

目前次要的个性次要包含：

• 批流一体化。
• 精细的状态治理。
• 事件工夫反对。
• 准确的一次状态一致性保障。

Flink 能够运行在包含 YARN、Mesos、Kubernetes 在内的多种资源管理框架上，还反对裸机集群上独立部署。TiDB 能够部署 AWS、Kubernetes、GCP GKE 上，同时也反对应用 TiUP 在裸机集群上独立部署。

TiDB + Flink 构造常见的几类利用如下：

• 事件驱动型利用：

  • 反欺诈。
  • 异样检测。
  • 基于规定的报警。
  • 业务流程监控。

• 数据分析利用：

  • 网络品质监控。
  • 产品更新及试验评估剖析。
  • 事实数据即席剖析。
  • 大规模图剖析。

• 数据管道利用：

  • 电商实时查问索引构建。
  • 电商继续 ETL。

二. 环境介绍

2.1 操作系统环境

[root@r20 topology]# cat /etc/redhat-release
CentOS Stream release 8

2.2 软件环境

2.3 机器调配

三. 部署 TiDB Cluster

与传统的单机数据库相比，TiDB 具备以下劣势：

• 纯分布式架构，领有良好的扩展性，反对弹性的扩缩容。
• 反对 SQL，对外裸露 MySQL 的网络协议，并兼容大多数 MySQL 的语法，在大多数场景下能够间接替换 MySQL。
• 默认反对高可用，在多数正本生效的状况下，数据库自身可能主动进行数据修复和故障转移，对业务通明。
• 反对 ACID 事务，对于一些有强统一需要的场景敌对，例如：银行转账。
• 具备丰盛的工具链生态，笼罩数据迁徙、同步、备份等多种场景。

在内核设计上，TiDB 分布式数据库将整体架构拆分成了多个模块，各模块之间相互通信，组成残缺的 TiDB 零碎。对应的架构图如下：

在本文中，咱们只做最简略的功能测试，所以部署了一套单节点但正本的 TiDB，波及到了以下的三个模块：

• TiDB Server：SQL 层，对外裸露 MySQL 协定的连贯 endpoint，负责承受客户端的连贯，执行 SQL 解析和优化，最终生成分布式执行打算。
• PD (Placement Driver) Server：整个 TiDB 集群的元信息管理模块，负责存储每个 TiKV 节点实时的数据分布状况和集群的整体拓扑构造，提供 TiDB Dashboard 管控界面，并为分布式事务调配事务 ID。
• TiKV Server：负责存储数据，从内部看 TiKV 是一个分布式的提供事务的 Key-Value 存储引擎。

3.1 TiUP 部署模板文件

# # Global variables are applied to all deployments and used as the default value of
# # the deployments if a specific deployment value is missing.
global:
  user: "tidb"
  ssh_port: 22
  deploy_dir: "/opt/tidb-c1/"
  data_dir: "/opt/tidb-c1/data/"
# # Monitored variables are applied to all the machines.
#monitored:
#  node_exporter_port: 19100
#  blackbox_exporter_port: 39115
#  deploy_dir: "/opt/tidb-c3/monitored"
#  data_dir: "/opt/tidb-c3/data/monitored"
#  log_dir: "/opt/tidb-c3/log/monitored"
# # Server configs are used to specify the runtime configuration of TiDB components.
# # All configuration items can be found in TiDB docs:
# # - TiDB: https://pingcap.com/docs/stable/reference/configuration/tidb-server/configuration-file/
# # - TiKV: https://pingcap.com/docs/stable/reference/configuration/tikv-server/configuration-file/
# # - PD: https://pingcap.com/docs/stable/reference/configuration/pd-server/configuration-file/
# # All configuration items use points to represent the hierarchy, e.g:
# #   readpool.storage.use-unified-pool
# #
# # You can overwrite this configuration via the instance-level `config` field.
server_configs:
  tidb:
    log.slow-threshold: 300
    binlog.enable: false
    binlog.ignore-error: false
    tikv-client.copr-cache.enable: true
  tikv:
    server.grpc-concurrency: 4
    raftstore.apply-pool-size: 2
    raftstore.store-pool-size: 2
    rocksdb.max-sub-compactions: 1
    storage.block-cache.capacity: "16GB"
    readpool.unified.max-thread-count: 12
    readpool.storage.use-unified-pool: false
    readpool.coprocessor.use-unified-pool: true
    raftdb.rate-bytes-per-sec: 0
  pd:
    schedule.leader-schedule-limit: 4
    schedule.region-schedule-limit: 2048
    schedule.replica-schedule-limit: 64
pd_servers:
  - host: 192.168.12.21
    ssh_port: 22
    name: "pd-2"
    client_port: 12379
    peer_port: 12380
    deploy_dir: "/opt/tidb-c1/pd-12379"
    data_dir: "/opt/tidb-c1/data/pd-12379"
    log_dir: "/opt/tidb-c1/log/pd-12379"
    numa_node: "0"
    # # The following configs are used to overwrite the `server_configs.pd` values.
    config:
      schedule.max-merge-region-size: 20
      schedule.max-merge-region-keys: 200000
tidb_servers:
  - host: 192.168.12.21
    ssh_port: 22
    port: 14000
    status_port: 12080
    deploy_dir: "/opt/tidb-c1/tidb-14000"
    log_dir: "/opt/tidb-c1/log/tidb-14000"
    numa_node: "0"
    # # The following configs are used to overwrite the `server_configs.tidb` values.
    config:
      log.slow-query-file: tidb-slow-overwrited.log
      tikv-client.copr-cache.enable: true
tikv_servers:
  - host: 192.168.12.21
    ssh_port: 22
    port: 12160
    status_port: 12180
    deploy_dir: "/opt/tidb-c1/tikv-12160"
    data_dir: "/opt/tidb-c1/data/tikv-12160"
    log_dir: "/opt/tidb-c1/log/tikv-12160"
    numa_node: "0"
    # # The following configs are used to overwrite the `server_configs.tikv` values.
    config:
      server.grpc-concurrency: 4
      #server.labels: {zone: "zone1", dc: "dc1", host: "host1"}
#monitoring_servers:
#  - host: 192.168.12.21
#    ssh_port: 22
#    port: 19090
#    deploy_dir: "/opt/tidb-c1/prometheus-19090"
#    data_dir: "/opt/tidb-c1/data/prometheus-19090"
#    log_dir: "/opt/tidb-c1/log/prometheus-19090"
#grafana_servers:
#  - host: 192.168.12.21
#    port: 13000
#    deploy_dir: "/opt/tidb-c1/grafana-13000"
#alertmanager_servers:
#  - host: 192.168.12.21
#    ssh_port: 22
#    web_port: 19093
#    cluster_port: 19094
#    deploy_dir: "/opt/tidb-c1/alertmanager-19093"
#    data_dir: "/opt/tidb-c1/data/alertmanager-19093"
#    log_dir: "/opt/tidb-c1/log/alertmanager-19093"

3.2 TiDB Cluster 环境

本文重点非部署 TiDB Cluster，作为疾速试验环境，只在一台机器上部署单正本的 TiDB Cluster 集群。不须要部署监控环境。

[root@r20 topology]# tiup cluster display tidb-c1-v409
Starting component `cluster`: /root/.tiup/components/cluster/v1.3.2/tiup-cluster display tidb-c1-v409
Cluster type:       tidb
Cluster name:       tidb-c1-v409
Cluster version:    v4.0.9
SSH type:           builtin
Dashboard URL:      http://192.168.12.21:12379/dashboard
ID                   Role  Host           Ports        OS/Arch       Status   Data Dir                      Deploy Dir
--                   ----  ----           -----        -------       ------   --------                      ----------
192.168.12.21:12379  pd    192.168.12.21  12379/12380  linux/x86_64  Up|L|UI  /opt/tidb-c1/data/pd-12379    /opt/tidb-c1/pd-12379
192.168.12.21:14000  tidb  192.168.12.21  14000/12080  linux/x86_64  Up       -                             /opt/tidb-c1/tidb-14000
192.168.12.21:12160  tikv  192.168.12.21  12160/12180  linux/x86_64  Up       /opt/tidb-c1/data/tikv-12160  /opt/tidb-c1/tikv-12160
Total nodes: 4

创立用于测试的表

mysql> show create table t1;
+-------+-------------------------------------------------------------------------------------------------------------------------------+
| Table | Create Table                                                                                                                  |
+-------+-------------------------------------------------------------------------------------------------------------------------------+
| t1    | CREATE TABLE `t1` (`id` int(11) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin |
+-------+-------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)

四. 部署 Zookeeper 环境

在本试验中独自配置 Zookeeper 环境，为 Kafka 和 Flink 环境提供服务。

作为试验演示计划，只部署单机环境。

4.1 解压 Zookeeper 包

[root@r24 soft]# tar vxzf apache-zookeeper-3.6.2-bin.tar.gz
[root@r24 soft]# mv apache-zookeeper-3.6.2-bin /opt/zookeeper

4.2 部署用于 Zookeeper 的 jre

[root@r24 soft]# tar vxzf jre1.8.0_281.tar.gz
[root@r24 soft]# mv jre1.8.0_281 /opt/zookeeper/jre

批改 /opt/zookeeper/bin/zkEnv.sh 文件，减少 JAVA_HOME 环境变量

## add bellowing env var in the head of zkEnv.sh
JAVA_HOME=/opt/zookeeper/jre

4.3 创立 Zookeeper 的配置文件

[root@r24 conf]# cat zoo.cfg | grep -v "#"
tickTime=2000
initLimit=10
syncLimit=5
dataDir=/opt/zookeeper/data
clientPort=2181

4.4 启动 Zookeeper

[root@r24 bin]# /opt/zookeeper/bin/zkServer.sh start

4.5 查看 Zookeeper 的状态

## check zk status
[root@r24 bin]# ./zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /opt/zookeeper/bin/../conf/zoo.cfg
Client port found: 2181. Client address: localhost. Client SSL: false.
Mode: standalone
## check OS port status
[root@r24 bin]# netstat -ntlp
Active Internet connections (only servers)
Proto Recv-Q Send-Q Local Address           Foreign Address         State       PID/Program name
tcp        0      0 0.0.0.0:22              0.0.0.0:*               LISTEN      942/sshd
tcp6       0      0 :::2181                 :::*                    LISTEN      15062/java
tcp6       0      0 :::8080                 :::*                    LISTEN      15062/java
tcp6       0      0 :::22                   :::*                    LISTEN      942/sshd
tcp6       0      0 :::44505                :::*                    LISTEN      15062/java
## use zkCli tool to check zk connection
[root@r24 bin]# ./zkCli.sh -server 192.168.12.24:2181

4.6 对于 Zookeeper 的倡议

我集体有一个对于 Zookeeper 的不成熟的小倡议：

Zookeeper 集群版本肯定要开启网络监控。特地是要关注 system metrics 外面的 network bandwidth。

五. 部署 Kafka

Kafka 是一个分布式流解决平台，次要利用于两大类的利用中：

• 结构实时流数据管道，它能够在零碎或利用之间牢靠地获取数据。(相当于 message queue)
• 构建实时流式应用程序，对这些流数据进行转换或者影响。(就是流解决，通过 kafka stream topic 和 topic 之间外部进行变动)

Kafka 有四个外围的 API：

• The Producer API 容许一个应用程序公布一串流式的数据到一个或者多个 Kafka topic。
• The Consumer API 容许一个应用程序订阅一个或多个 topic，并且对公布给他们的流式数据进行解决。
• The Streams API 容许一个应用程序作为一个 流处理器，生产一个或者多个 topic 产生的输出流，而后生产一个输入流到一个或多个 topic 中去，在输入输出流中进行无效的转换。
• The Connector API 容许构建并运行可重用的生产者或者消费者，将 Kafka topics 连贯到已存在的应用程序或者数据系统。比方，连贯到一个关系型数据库，捕获表（table）的所有变更内容。

在本试验中只做功能性验证，只搭建一个单机版的 Kafka 环境。

5.1 下载并解压 Kafka

[root@r22 soft]# tar vxzf kafka_2.13-2.7.0.tgz
[root@r22 soft]# mv kafka_2.13-2.7.0 /opt/kafka

5.2 部署用于 Kafka 的 jre

[root@r22 soft]# tar vxzf jre1.8.0_281.tar.gz
[root@r22 soft]# mv jre1.8.0_281 /opt/kafka/jre

批改 Kafka 的 jre 环境变量

[root@r22 bin]# vim /opt/kafka/bin/kafka-run-class.sh
## add bellowing line in the head of kafka-run-class.sh
JAVA_HOME=/opt/kafka/jre

5.3 批改 Kafka 配置文件

批改 Kafka 配置文件 /opt/kafka/config/server.properties

## change bellowing variable in /opt/kafka/config/server.properties
broker.id=0
listeners=PLAINTEXT://192.168.12.22:9092
log.dirs=/opt/kafka/logs
zookeeper.connect=i192.168.12.24:2181

5.4 启动 Kafka

[root@r22 bin]# /opt/kafka/bin/kafka-server-start.sh /opt/kafka/config/server.properties

5.5 查看 Kafka 的版本信息

Kafka 并没有提供 –version 的 optional 来查看 Kafka 的版本信息。

[root@r22 ~]# ll /opt/kafka/libs/ | grep kafka
-rw-r--r-- 1 root root  4929521 Dec 16 09:02 kafka_2.13-2.7.0.jar
-rw-r--r-- 1 root root      821 Dec 16 09:03 kafka_2.13-2.7.0.jar.asc
-rw-r--r-- 1 root root    41793 Dec 16 09:02 kafka_2.13-2.7.0-javadoc.jar
-rw-r--r-- 1 root root      821 Dec 16 09:03 kafka_2.13-2.7.0-javadoc.jar.asc
-rw-r--r-- 1 root root   892036 Dec 16 09:02 kafka_2.13-2.7.0-sources.jar
-rw-r--r-- 1 root root      821 Dec 16 09:03 kafka_2.13-2.7.0-sources.jar.asc
... ...

其中 2.13 是 scale 的版本信息，2.7.0 是 Kafka 的版本信息。

六. 部署 Flink

Apache Flink 是一个框架和分布式解决引擎，用于在 无边界 和有边界 数据流上进行有状态的计算。Flink 能在所有常见集群环境中运行，并能以内存速度和任意规模进行计算。

反对高吞吐、低提早、高性能的分布式解决框架 Apache Flink 是一个框架和分布式解决引擎，用于对无界和有界数据流进行有状态计算。Flink 被设计在所有常见的集群环境中运行，以内存执行速度和任意规模来执行计算。

本试验只做功能性测试，仅部署单机 Flink 环境。

6.1 下载并散发 Flink

[root@r23 soft]# tar vxzf flink-1.12.1-bin-scala_2.11.tgz
[root@r23 soft]# mv flink-1.12.1 /opt/flink

6.2 部署 Flink 的 jre

[root@r23 soft]# tar vxzf jre1.8.0_281.tar.gz
[root@r23 soft]# mv jre1.8.0_281 /opt/flink/jre

6.3 增加 Flink 须要的 lib

Flink 生产 Kafka 数据，须要 flink-sql-connector-kafka 包。

Flink 链接 MySQL/TiDB，须要 flink-connector-jdbc 包。

[root@r23 soft]# mv flink-sql-connector-kafka_2.12-1.12.0.jar /opt/flink/lib/
[root@r23 soft]# mv flink-connector-jdbc_2.12-1.12.0.jar /opt/flink/lib/

6.4 批改 Flink 配置文件

## add or modify bellowing lines in /opt/flink/conf/flink-conf.yaml
jobmanager.rpc.address: 192.168.12.23
env.java.home: /opt/flink/jre

6.5 启动 Flink

[root@r23 ~]# /opt/flink/bin/start-cluster.sh
Starting cluster.
Starting standalonesession daemon on host r23.
Starting taskexecutor daemon on host r23.

6.6 查看 Flink GUI

七. 部署 MySQL

7.1 解压 MySQL package

[root@r25 soft]# tar vxf mysql-8.0.23-linux-glibc2.12-x86_64.tar.xz
[root@r25 soft]# mv mysql-8.0.23-linux-glibc2.12-x86_64 /opt/mysql/

7.2 创立 MySQL Service 文件

[root@r25 ~]# touch /opt/mysql/support-files/mysqld.service
[root@r25 support-files]# cat mysqld.service
[Unit]
Description=MySQL 8.0 database server
After=syslog.target
After=network.target
[Service]
Type=simple
User=mysql
Group=mysql
#ExecStartPre=/usr/libexec/mysql-check-socket
#ExecStartPre=/usr/libexec/mysql-prepare-db-dir %n
# Note: we set --basedir to prevent probes that might trigger SELinux alarms,
# per bug #547485
ExecStart=/opt/mysql/bin/mysqld_safe
#ExecStartPost=/opt/mysql/bin/mysql-check-upgrade
#ExecStopPost=/opt/mysql/bin/mysql-wait-stop
# Give a reasonable amount of time for the server to start up/shut down
TimeoutSec=300
# Place temp files in a secure directory, not /tmp
PrivateTmp=true
Restart=on-failure
RestartPreventExitStatus=1
# Sets open_files_limit
LimitNOFILE = 10000
# Set enviroment variable MYSQLD_PARENT_PID. This is required for SQL restart command.
Environment=MYSQLD_PARENT_PID=1
[Install]
WantedBy=multi-user.target
## copy mysqld.service to /usr/lib/systemd/system/
[root@r25 support-files]# cp mysqld.service  /usr/lib/systemd/system/

7.3 创立 my.cnf 文件

[root@r34 opt]# cat /etc/my.cnf
[mysqld]
port=3306
basedir=/opt/mysql
datadir=/opt/mysql/data
socket=/opt/mysql/data/mysql.socket
max_connections = 100
default-storage-engine = InnoDB
character-set-server=utf8
log-error = /opt/mysql/log/error.log
slow_query_log = 1
long-query-time = 30
slow_query_log_file = /opt/mysql/log/show.log
min_examined_row_limit = 1000
log-slow-slave-statements
log-queries-not-using-indexes
#skip-grant-tables

7.4 初始化并启动 MySQL

[root@r25 ~]# /opt/mysql/bin/mysqld --initialize --user=mysql --console
[root@r25 ~]# chown -R mysql:mysql /opt/mysql
[root@r25 ~]# systemctl start mysqld
## check mysql temp passord from /opt/mysql/log/error.log
2021-02-24T02:45:47.316406Z 6 [Note] [MY-010454] [Server] A temporary password is generated for root@localhost: I?nDjijxa3>-

7.5 创立一个新的 MySQL 用户用以连贯 Canal

## change mysql temp password firstly
mysql> alter user 'root'@'localhost' identified by 'mysql';
Query OK, 0 rows affected (0.00 sec)
## create a management user 'root'@'%'
mysql> create user 'root'@'%' identified by 'mysql';
Query OK, 0 rows affected (0.01 sec)
mysql> grant all privileges on *.* to 'root'@'%';
Query OK, 0 rows affected (0.00 sec)
## create a canal replication user 'canal'@'%'
mysql> create user 'canal'@'%' identified by 'canal';
Query OK, 0 rows affected (0.01 sec)
mysql> grant select, replication slave, replication client on *.* to 'canal'@'%';
Query OK, 0 rows affected (0.00 sec)
mysql> flush privileges;
Query OK, 0 rows affected (0.00 sec)

7.6 在 MySQL 中创立用于测试的表

mysql> show create table test.t2;
+-------+----------------------------------------------------------------------------------+
| Table | Create Table                                                                     |
+-------+----------------------------------------------------------------------------------+
| t2    | CREATE TABLE `t2` (`id` int DEFAULT NULL) ENGINE=InnoDB DEFAULT CHARSET=utf8 |
+-------+----------------------------------------------------------------------------------+
1 row in set (0.00 sec)

八. 部署 Canal

Canal 主要用途是基于 MySQL 数据库增量日志解析，提供增量数据订阅和生产。

晚期阿里巴巴因为杭州和美国双机房部署，存在跨机房同步的业务需要，实现形式次要是基于业务 trigger 获取增量变更。

从 2010 年开始，业务逐渐尝试数据库日志解析获取增量变更进行同步，由此衍生出了大量的数据库增量订阅和生产业务。

基于日志增量订阅和生产的业务包含：

• 数据库镜像。
• 数据库实时备份。
• 索引构建和实时保护(拆分异构索引、倒排索引等)。
• 业务 cache 刷新。
• 带业务逻辑的增量数据处理。

以后的 canal 反对源端 MySQL 版本包含 5.1.x , 5.5.x , 5.6.x , 5.7.x , 8.0.x。

8.1 解压 Canal 包

[root@r26 soft]# mkdir /opt/canal && tar vxzf canal.deployer-1.1.4.tar.gz -C /opt/canal

8.2 部署 Canal 的 jre

[root@r26 soft]# tar vxzf jre1.8.0_281.tar.gz
[root@r26 soft]# mv jre1.8.0_281 /opt/canal/jre
## configue jre, add bellowing line in the head of /opt/canal/bin/startup.sh 
JAVA=/opt/canal/jre/bin/java

8.3 批改 Canal 的配置文件

批改 /opt/canal/conf/canal.properties 配置文件

## modify bellowing configuration
canal.zkServers =192.168.12.24:2181
canal.serverMode = kafka
canal.destinations = example        ## 须要在 /opt/canal/conf 目录下创立一个 example 文件夹，用于寄存 destination 的配置
canal.mq.servers = 192.168.12.22:9092

批改 /opt/canal/conf/example/instance.properties 配置文件

## modify bellowing configuration
canal.instance.master.address=192.168.12.25:3306
canal.instance.dbUsername=canal
canal.instance.dbPassword=canal
canal.instance.filter.regex=.*\\..*                    ## 过滤数据库的表
canal.mq.topic=canal-kafka

九. 配置数据流向

9.1 MySQL Binlog -> Canal -> Kafka 通路

9.1.1 查看 MySQL Binlog 信息

查看 MySQL Binlog 信息，确保 Binlog 是失常的。

mysql> show master status;
+---------------+----------+--------------+------------------+-------------------+
| File          | Position | Binlog_Do_DB | Binlog_Ignore_DB | Executed_Gtid_Set |
+---------------+----------+--------------+------------------+-------------------+
| binlog.000001 |     2888 |              |                  |                   |
+---------------+----------+--------------+------------------+-------------------+
1 row in set (0.00 sec)

9.1.2 在 Kafka 中创立一个 Topic

在 Kafka 中创立一个 Topic canal-kafka，这个 Topic 的名字要与 Canal 配置文件 /opt/canal/conf/example/instance.properties 中的 canal.mq.topic=canal-kafka 对应：

[root@r22 kafka]# /opt/kafka/bin/kafka-topics.sh --create \
> --zookeeper 192.168.12.24:2181 \
> --config max.message.bytes=12800000 \
> --config flush.messages=1 \
> --replication-factor 1 \
> --partitions 1 \
> --topic canal-kafka
Created topic canal-kafka.
[2021-02-24 01:51:55,050] INFO [ReplicaFetcherManager on broker 0] Removed fetcher for partitions Set(canal-kafka-0) (kafka.server.ReplicaFetcherManager)
[2021-02-24 01:51:55,052] INFO [Log partition=canal-kafka-0, dir=/opt/kafka/logs] Loading producer state till offset 0 with message format version 2 (kafka.log.Log)
[2021-02-24 01:51:55,053] INFO Created log for partition canal-kafka-0 in /opt/kafka/logs/canal-kafka-0 with properties {compression.type -> producer, message.downconversion.enable -> true, min.insync.replicas -> 1, segment.jitter.ms -> 0, cleanup.policy -> [delete], flush.ms -> 9223372036854775807, segment.bytes -> 1073741824, retention.ms -> 604800000, flush.messages -> 1, message.format.version -> 2.7-IV2, file.delete.delay.ms -> 60000, max.compaction.lag.ms -> 9223372036854775807, max.message.bytes -> 12800000, min.compaction.lag.ms -> 0, message.timestamp.type -> CreateTime, preallocate -> false, min.cleanable.dirty.ratio -> 0.5, index.interval.bytes -> 4096, unclean.leader.election.enable -> false, retention.bytes -> -1, delete.retention.ms -> 86400000, segment.ms -> 604800000, message.timestamp.difference.max.ms -> 9223372036854775807, segment.index.bytes -> 10485760}. (kafka.log.LogManager)
[2021-02-24 01:51:55,053] INFO [Partition canal-kafka-0 broker=0] No checkpointed highwatermark is found for partition canal-kafka-0 (kafka.cluster.Partition)
[2021-02-24 01:51:55,053] INFO [Partition canal-kafka-0 broker=0] Log loaded for partition canal-kafka-0 with initial high watermark 0 (kafka.cluster.Partition)

查看 Kafka 中所有的 Topic：

[root@r22 kafka]# /opt/kafka/bin/kafka-topics.sh --list --zookeeper 192.168.12.24:2181
__consumer_offsets
canal-kafka
ticdc-test

查看 Kafka 中 Topic ticdc-test 的信息：

[root@r22 ~]# /opt/kafka/bin/kafka-topics.sh --describe --zookeeper 192.168.12.24:2181  --topic canal-kafka
Topic: ticdc-test       PartitionCount: 1       ReplicationFactor: 1    Configs: max.message.bytes=12800000,flush.messages=1
        Topic: ticdc-test       Partition: 0    Leader: 0       Replicas: 0     Isr: 0

9.1.3 启动 Canal

在启动 Canal 之前，须要在 Canal 节点上查看一下端口的状况：

## check MySQL 3306 port
## canal.instance.master.address=192.168.12.25:3306
[root@r26 bin]# telnet 192.168.12.25 3306
## check Kafka 9092 port
## canal.mq.servers = 192.168.12.22:9092
[root@r26 bin]# telnet 192.168.12.22 9092
## check zookeeper 2181 port
## canal.zkServers = 192.168.12.24:2181
[root@r26 bin]# telnet 192.168.12.24 2181

启动 Canal：

[root@r26 bin]# /opt/canal/bin/startup.sh
cd to /opt/canal/bin for workaround relative path
LOG CONFIGURATION : /opt/canal/bin/../conf/logback.xml
canal conf : /opt/canal/bin/../conf/canal.properties
CLASSPATH :/opt/canal/bin/../conf:/opt/canal/bin/../lib/zookeeper-3.4.5.jar:/opt/canal/bin/../lib/zkclient-0.10.jar:/opt/canal/bin/../lib/spring-tx-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-orm-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-jdbc-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-expression-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-core-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-context-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-beans-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/spring-aop-3.2.18.RELEASE.jar:/opt/canal/bin/../lib/snappy-java-1.1.7.1.jar:/opt/canal/bin/../lib/snakeyaml-1.19.jar:/opt/canal/bin/../lib/slf4j-api-1.7.12.jar:/opt/canal/bin/../lib/simpleclient_pushgateway-0.4.0.jar:/opt/canal/bin/../lib/simpleclient_httpserver-0.4.0.jar:/opt/canal/bin/../lib/simpleclient_hotspot-0.4.0.jar:/opt/canal/bin/../lib/simpleclient_common-0.4.0.jar:/opt/canal/bin/../lib/simpleclient-0.4.0.jar:/opt/canal/bin/../lib/scala-reflect-2.11.12.jar:/opt/canal/bin/../lib/scala-logging_2.11-3.8.0.jar:/opt/canal/bin/../lib/scala-library-2.11.12.jar:/opt/canal/bin/../lib/rocketmq-srvutil-4.5.2.jar:/opt/canal/bin/../lib/rocketmq-remoting-4.5.2.jar:/opt/canal/bin/../lib/rocketmq-logging-4.5.2.jar:/opt/canal/bin/../lib/rocketmq-common-4.5.2.jar:/opt/canal/bin/../lib/rocketmq-client-4.5.2.jar:/opt/canal/bin/../lib/rocketmq-acl-4.5.2.jar:/opt/canal/bin/../lib/protobuf-java-3.6.1.jar:/opt/canal/bin/../lib/oro-2.0.8.jar:/opt/canal/bin/../lib/netty-tcnative-boringssl-static-1.1.33.Fork26.jar:/opt/canal/bin/../lib/netty-all-4.1.6.Final.jar:/opt/canal/bin/../lib/netty-3.2.2.Final.jar:/opt/canal/bin/../lib/mysql-connector-java-5.1.47.jar:/opt/canal/bin/../lib/metrics-core-2.2.0.jar:/opt/canal/bin/../lib/lz4-java-1.4.1.jar:/opt/canal/bin/../lib/logback-core-1.1.3.jar:/opt/canal/bin/../lib/logback-classic-1.1.3.jar:/opt/canal/bin/../lib/kafka-clients-1.1.1.jar:/opt/canal/bin/../lib/kafka_2.11-1.1.1.jar:/opt/canal/bin/../lib/jsr305-3.0.2.jar:/opt/canal/bin/../lib/jopt-simple-5.0.4.jar:/opt/canal/bin/../lib/jctools-core-2.1.2.jar:/opt/canal/bin/../lib/jcl-over-slf4j-1.7.12.jar:/opt/canal/bin/../lib/javax.annotation-api-1.3.2.jar:/opt/canal/bin/../lib/jackson-databind-2.9.6.jar:/opt/canal/bin/../lib/jackson-core-2.9.6.jar:/opt/canal/bin/../lib/jackson-annotations-2.9.0.jar:/opt/canal/bin/../lib/ibatis-sqlmap-2.3.4.726.jar:/opt/canal/bin/../lib/httpcore-4.4.3.jar:/opt/canal/bin/../lib/httpclient-4.5.1.jar:/opt/canal/bin/../lib/h2-1.4.196.jar:/opt/canal/bin/../lib/guava-18.0.jar:/opt/canal/bin/../lib/fastsql-2.0.0_preview_973.jar:/opt/canal/bin/../lib/fastjson-1.2.58.jar:/opt/canal/bin/../lib/druid-1.1.9.jar:/opt/canal/bin/../lib/disruptor-3.4.2.jar:/opt/canal/bin/../lib/commons-logging-1.1.3.jar:/opt/canal/bin/../lib/commons-lang3-3.4.jar:/opt/canal/bin/../lib/commons-lang-2.6.jar:/opt/canal/bin/../lib/commons-io-2.4.jar:/opt/canal/bin/../lib/commons-compress-1.9.jar:/opt/canal/bin/../lib/commons-codec-1.9.jar:/opt/canal/bin/../lib/commons-cli-1.2.jar:/opt/canal/bin/../lib/commons-beanutils-1.8.2.jar:/opt/canal/bin/../lib/canal.store-1.1.4.jar:/opt/canal/bin/../lib/canal.sink-1.1.4.jar:/opt/canal/bin/../lib/canal.server-1.1.4.jar:/opt/canal/bin/../lib/canal.protocol-1.1.4.jar:/opt/canal/bin/../lib/canal.prometheus-1.1.4.jar:/opt/canal/bin/../lib/canal.parse.driver-1.1.4.jar:/opt/canal/bin/../lib/canal.parse.dbsync-1.1.4.jar:/opt/canal/bin/../lib/canal.parse-1.1.4.jar:/opt/canal/bin/../lib/canal.meta-1.1.4.jar:/opt/canal/bin/../lib/canal.instance.spring-1.1.4.jar:/opt/canal/bin/../lib/canal.instance.manager-1.1.4.jar:/opt/canal/bin/../lib/canal.instance.core-1.1.4.jar:/opt/canal/bin/../lib/canal.filter-1.1.4.jar:/opt/canal/bin/../lib/canal.deployer-1.1.4.jar:/opt/canal/bin/../lib/canal.common-1.1.4.jar:/opt/canal/bin/../lib/aviator-2.2.1.jar:/opt/canal/bin/../lib/aopalliance-1.0.jar:
cd to /opt/canal/bin for continue

9.1.4 查看 Canal 日志

查看 /opt/canal/logs/example/example.log

2021-02-24 01:41:40.293 [destination = example , address = /192.168.12.25:3306 , EventParser] WARN  c.a.o.c.p.inbound.mysql.rds.RdsBinlogEventParserProxy - ---> begin to find start position, it will be long time for reset or first position
2021-02-24 01:41:40.293 [destination = example , address = /192.168.12.25:3306 , EventParser] WARN  c.a.o.c.p.inbound.mysql.rds.RdsBinlogEventParserProxy - prepare to find start position just show master status
2021-02-24 01:41:40.542 [destination = example , address = /192.168.12.25:3306 , EventParser] WARN  c.a.o.c.p.inbound.mysql.rds.RdsBinlogEventParserProxy - ---> find start position successfully, EntryPosition[included=false,journalName=binlog.000001,position=4,serverId=1,gtid=<null>,timestamp=1614134832000] cost : 244ms , the next step is binlog dump

9.1.5 查看 Kafka 中 consumer 信息

在 MySQL 中插入一条测试信息：

mysql> insert into t2 values(1);
Query OK, 1 row affected (0.00 sec)

查看 consumer 的信息，曾经有了方才插入的测试数据：

/opt/kafka/bin/kafka-console-consumer.sh --bootstrap-server 192.168.12.22:9092 --topic canal-kafka --from-beginning
{"data":null,"database":"test","es":1614151725000,"id":2,"isDdl":false,"mysqlType":null,"old":null,"pkNames":null,"sql":"create database test","sqlType":null,"table":"","ts":1614151725890,"type":"QUERY"}
{"data":null,"database":"test","es":1614151746000,"id":3,"isDdl":true,"mysqlType":null,"old":null,"pkNames":null,"sql":"create table t2(id int)","sqlType":null,"table":"t2","ts":1614151746141,"type":"CREATE"}
{"data":[{"id":"1"}],"database":"test","es":1614151941000,"id":4,"isDdl":false,"mysqlType":{"id":"int"},"old":null,"pkNames":null,"sql":"","sqlType":{"id":4},"table":"t2","ts":1614151941235,"type":"INSERT"}

9.2 Kafka -> Flink 通路

在 Flink 中创立 t2 表，connector 类型为 kafka。

## create a test table t2 in Flink
Flink SQL> create table t2(id int)
> WITH (
>  'connector' = 'kafka',
>  'topic' = 'canal-kafka',
>  'properties.bootstrap.servers' = '192.168.12.22:9092',
>  'properties.group.id' = 'canal-kafka-consumer-group',
>  'format' = 'canal-json',
>  'scan.startup.mode' = 'latest-offset'
> );
Flink SQL> select * from t1;

在 MySQL 中在插入一条测试数据：

mysql> insert into test.t2 values(2);
Query OK, 1 row affected (0.00 sec)

从 Flink 中能够实时同步数据：

Flink SQL> select * from t1;
 Refresh: 1 s                                                                                                             Page: Last of 1                                                                                                     Updated: 02:49:27.366
                        id
                         2

9.3 Flink -> TiDB 通路

9.3.1 在 上游的 TiDB 中创立用于测试的表

[root@r20 soft]# mysql -uroot -P14000 -hr21
mysql> create table t3 (id int);
Query OK, 0 rows affected (0.31 sec)

9.3.2 在 Flink 中创立测试表

Flink SQL> CREATE TABLE t3 (
>     id int
> ) with (
>     'connector' = 'jdbc',
>     'url' = 'jdbc:mysql://192.168.12.21:14000/test',
>     'table-name' = 't3',
>     'username' = 'root',
>     'password' = 'mysql'
> );
Flink SQL> insert into t3 values(3);
[INFO] Submitting SQL update statement to the cluster...
[INFO] Table update statement has been successfully submitted to the cluster:
Job ID: a0827487030db177ee7e5c8575ef714e

9.3.3 在上游 TiDB 中查看插入的数据

mysql> select * from test.t3;
+------+
| id   |
+------+
|    3 |
+------+
1 row in set (0.00 sec)