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基于K8s、Strimzi的Kafka Connect实战

程序员文章站 2022-03-01 13:42:40
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0. 源码地址

https://github.com/wiselyman/kafka-in-battle

1. Operator Framework

Operator Framework是一个用来管理k8s原生应用(Operator)的开源工具。

Operator Framework支持的Operator分享地址:https://operatorhub.io

如安装Kafka使用Strimzi Apache Kafka Operator,地址为:https://operatorhub.io/operator/strimzi-kafka-operator 。

打开Strimzi Apache Kafka Operator页面,右侧有install按钮,按照页面提示进行Operator安装。

2. 安装Operator Lifecycle Manager

Operator Lifecycle Manager是Operator Framework的一部分,OLM扩展了k8s提供声明式方法安装、管理、更新Operator以及他们的依赖。

点击页面上的install显示如何安装Strimzi Apache Kafka Operator,我们首先第一步要安装Operator Lifecycle Manager(不要执行下句命令):

curl -sL https://github.com/operator-framework/operator-lifecycle-manager/releases/download/0.12.0/install.sh | bash -s 0.12.0

该命令需要使用quay.io的镜像,我们需采取从源码安装,并修改源码中的镜像地址加速。

源码地址:https://github.com/operator-framework/operator-lifecycle-manager/releases,当前最新版本为0.12.0

olm.yml中:

quay.io ->  quay.azk8s.cn

执行安装:

kubectl apply -f crds.yaml
kubectl apply -f olm.yaml

3. 安装Strimzi Apache Kafka Operator

kubectl create -f https://operatorhub.io/install/strimzi-kafka-operator.yaml

使用下面命令观察Operator启动情况

kubectl get csv -n operators

显示如下则安装成功

wangyunfeis-MacBook-Pro:olm wangyunfei$ kubectl get csv -n operators
NAME                               DISPLAY                         VERSION   REPLACES                           PHASE
strimzi-cluster-operator.v0.14.0   Strimzi Apache Kafka Operator   0.14.0    strimzi-cluster-operator.v0.13.0   Succeeded

4. 安装Kafka集群

下载https://raw.githubusercontent.com/strimzi/strimzi-kafka-operator/0.14.0/examples/kafka/kafka-persistent.yaml,主要修改的是所需存储空间为5Gi作为测试条件,这里的存储需要K8s集群中有默认的StorageClass

apiVersion: kafka.strimzi.io/v1beta1
kind: Kafka
metadata:
  name: my-cluster
spec:
  kafka:
    version: 2.3.0
    replicas: 3
    listeners:
      plain: {}
      tls: {}
    config:
      offsets.topic.replication.factor: 3
      transaction.state.log.replication.factor: 3
      delete.topic.enable: "true"
      transaction.state.log.min.isr: 2
      log.message.format.version: "2.3"
    storage:
      type: jbod
      volumes:
      - id: 0
        type: persistent-claim
        size: 5Gi
        deleteClaim: false
  zookeeper:
    replicas: 3
    storage:
      type: persistent-claim
      size: 5Gi
      deleteClaim: false
  entityOperator:
    topicOperator: {}
    userOperator: {}
kubectl apply -f kafka-persistent.yml -n kafka 
  • 发送消息测试
kubectl exec -i -n kafka my-cluster-kafka-0 -- bin/kafka-console-producer.sh --broker-list my-cluster-kafka-bootstrap:9092 --topic strimizi-my-topic
  • 接受消息测试
kubectl exec -i -n kafka  my-cluster-kafka-0 -- bin/kafka-console-consumer.sh --bootstrap-server my-cluster-kafka-bootstrap:9092 --topic strimizi-my-topic --from-beginning
  • 显示集群Topic
kubectl exec -n kafka my-cluster-kafka-0   -- bin/kafka-topics.sh --list --zookeeper localhost:2181

5. Kafka Connect

本节将外部的SQL Server中的表person(字段只有idname)通过Kafka Connect同步至K8s集群里的PostgreSQL中。

5.1 开启SQL Server数据库的CDC(Change Data Capture)功能

5.1.1 启用数据库CDC

USE bs_portal
EXEC sys.sp_cdc_enable_db;

bs_portal为数据库名,此时会自动给我们创建cdc的schema和相关表:

  • captured_columns
  • change_tables
  • dbo_person_CT
  • ddl_history
  • index_columns
  • lsn_time_mapping

可使用下面sql语句查询已开启CDC的数据库:

select * from sys.databases where is_cdc_enabled = 1 

5.1.2 启用表的CDC

USE bs_portal 
EXEC sys.sp_cdc_enable_table  
    @source_schema = 'dbo',  
    @source_name = 'person',  
    @role_name = 'cdc_admin',
    @supports_net_changes = 1;

@source_name为表名,查询表开启CDS的sql语句:

select name, is_tracked_by_cdc from sys.tables where object_id = OBJECT_ID('dbo.person')  

查看新增的job

SELECT job_id,name,enabled,date_created,date_modified FROM msdb.dbo.sysjobs ORDER BY date_created

确定用户有权限访问CDC表

EXEC sys.sp_cdc_help_change_data_capture;

5.1.3 开启“SQL Server 代理”

检查安装了SQL Server的操作系统中“服务”中是否开启了“SQL Server 代理”。

5.1.4 关闭CDC

关闭数据库的CDC

USE bs_portal
EXEC sys.sp_cdc_disable_db;

关闭表的CDC

USE bs_portal
EXEC sys.sp_cdc_disable_table   
    @source_schema = 'dbo',  
    @source_name = 'person',  
    @capture_instance = 'all';

5.2 SQL Server To PosgreSQL

5.2.1 准备Kafka Connect镜像

输入插件(source):下载SQL Server Connector plugin:http://central.maven.org/maven2/io/debezium/debezium-connector-sqlserver/;输出插件(sink):下载Kafka Connect JDBC:https://www.confluent.io/hub/confluentinc/kafka-connect-jdbc

新建Dockerfile文件,将debezium-connector-sqlserver-0.10.0.Final-plugin.zip解压放置到Dockerfile相同目录下的plugins目录;在plugins目录下新建目录kafka-connect-jdbc,解压confluentinc-kafka-connect-jdbc-5.3.1.zip,将lib下的kafka-connect-jdbc-5.3.1.jarpostgresql-9.4.1212.jar放置在kafka-connect-jdbc

编写Dockerfile

FROM strimzi/kafka:0.14.0-kafka-2.3.0
USER root:root
COPY ./plugins/ /opt/kafka/plugins/
USER 1001
MAINTAINER 285414629@qq.com

使用阿里云“容器镜像服务”(https://cr.console.aliyun.com/)编译镜像,目前我们的源码地址位于:https://github.com/wiselyman/kafka-in-battle

  • “镜像仓库”->“创建镜像仓库”:

    1. 仓库名称:kafka-connect-form-sql-to-jdbc

    2. 仓库类型:公开

  • 下一步后,选择“Github”标签页,使用自己的GitHub库,“构建设置”只勾选“海外机器构建”,然后点击“创建镜像仓库”。

  • 点击镜像仓库列表中的“kafka-connect-mysql-postgres”->“构建”->“添加规则”:

    1. 类型:Branch

    2. Branch/Tag:master

    3. Dockerfile目录:/sqlserver-to-jdbc/

    4. Dockfile文件名:Dockerfile

    5. 镜像版本:0.1

  • 确认后,“构建规则设置”->“立即构建”,“构建日志”显示“构建状态”为“成功”即可。

5.2.2 安装Kafka Connect

编写Kafka Connect集群部署文件kafka-connect-sql-postgres.yml

apiVersion: kafka.strimzi.io/v1beta1
kind: KafkaConnect
metadata:
  name: my-connect-cluster
spec:
  version: 2.3.0
  replicas: 1
  bootstrapServers: 'my-cluster-kafka-bootstrap:9093'
  image: registry.cn-hangzhou.aliyuncs.com/wiselyman/kafka-connect-from-sql-to-jdbc:0.1
  tls:
    trustedCertificates:
      - secretName: my-cluster-cluster-ca-cert
        certificate: ca.crt

执行安装

kubectl apply -f kafka-connect-sql-postgres.yml -n kafka

查询已安装的插件

kubectl exec -i -n kafka my-cluster-kafka-0 -- curl -X GET http://my-connect-cluster-connect-api:8083/connector-plugins

结果如:

[{
	"class": "io.confluent.connect.jdbc.JdbcSinkConnector",
	"type": "sink",
	"version": "5.3.1"
}, {
	"class": "io.confluent.connect.jdbc.JdbcSourceConnector",
	"type": "source",
	"version": "5.3.1"
}, {
	"class": "io.debezium.connector.sqlserver.SqlServerConnector",
	"type": "source",
	"version": "0.10.0.Final"
}, {
	"class": "org.apache.kafka.connect.file.FileStreamSinkConnector",
	"type": "sink",
	"version": "2.3.0"
}, {
	"class": "org.apache.kafka.connect.file.FileStreamSourceConnector",
	"type": "source",
	"version": "2.3.0"
}]

5.2.3 使用Helm安装PostgreSQL

使用helm安装PostgreSQL,这里的PostgreSQL库来自于https://kubernetes.oss-cn-hangzhou.aliyuncs.com/charts/,可在Helm中配置。

对PostgreSQL的账号、密码、初始化数据库、服务类型进行定制后安装:

helm install --name my-pg --set global.storageClass=standard,postgresUser=wisely,postgresPassword=zzzzzz,postgresDatabase=center,service.type=NodePort,service.nodePort=5432 stable/postgresql

5.2.4 Kafka Connect Source配置

编写source配置:sql-server-source.json

{
  "name": "sql-server-connector",
  "config": {
    "connector.class" : "io.debezium.connector.sqlserver.SqlServerConnector",
    "tasks.max" : "1",
    "database.server.name" : "exam",
    "database.hostname" : "172.16.8.221",
    "database.port" : "1433",
    "database.user" : "sa",
    "database.password" : "sa",
    "database.dbname" : "bs_portal",
    "database.history.kafka.bootstrap.servers" : "my-cluster-kafka-bootstrap:9092",
    "database.history.kafka.topic": "schema-changes.person",
    "table.whitelist": "dbo.person"
  }
}

编写sink配置:postgres-sink.json

{
  "name": "postgres-sink",
  "config": {
    "connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",
    "tasks.max": "1",
    "topics": "exam.dbo.MH_YCZM",
    "connection.url": "jdbc:postgresql://my-pg-postgresql.default.svc.cluster.local:5432/center?user=wisely&password=zzzzzz",
    "transforms": "unwrap",
    "transforms.unwrap.type": "io.debezium.transforms.ExtractNewRecordState",
    "transforms.unwrap.drop.tombstones": "false",
    "auto.create": "true",
    "insert.mode": "upsert",
    "delete.enabled": "true",
    "pk.fields": "IPDZ",
    "pk.mode": "record_key"
  }
}

5.2.5 使用

将配置文件提交到Kafka Connect

cat sql-server-source.json | kubectl exec -i -n kafka my-cluster-kafka-0 -- curl -X POST -H "Accept:application/json" -H "Content-Type:application/json" http://my-connect-cluster-connect-api:8083/connectors -d @-
cat postgres-sink.json| kubectl exec -i -n kafka my-cluster-kafka-0 -- curl -X POST -H "Accept:application/json" -H "Content-Type:application/json" http://my-connect-cluster-connect-api:8083/connectors -d @-

查看所有的Connector

kubectl exec -i -n kafka my-cluster-kafka-0 -- curl -X GET http://my-connect-cluster-connect-api:8083/connectors

删除Connect

kubectl exec -i -n kafka my-cluster-kafka-0 -- curl -X DELETE http://my-connect-cluster-connect-api:8083/connectors/postgres-sink

查看所有的topic

kubectl exec -n kafka my-cluster-kafka-0   -- bin/kafka-topics.sh --list --zookeeper localhost:2181

查看SQL Server Connector中的数据

kubectl exec -i -n kafka my-cluster-kafka-0 -- bin/kafka-console-consumer.sh --bootstrap-server my-cluster-kafka-bootstrap:9092 --topic exam.dbo.person --from-beginning

我们此时查看PostgreSQL数据库已经有了person表和数据,当对SQL Server新增、修改、删除数据时,PostgreSQL中也会同步更新。