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Kafka Connect

confluent官网:https://debezium.io/documentation/reference/stable/connectors/sqlserver.html

Debezium官网:https://debezium.io/documentation/reference/stable/connectors/sqlserver.html

一、什么是 Kafka Connect?

Kafka Connect 是 Apache Kafka® 的一个免费开源组件,可作为集中式数据中心,用于在数据库、键值存储、搜索索引和文件系统之间进行简单的数据集成。
您可以使用 Kafka Connect 在 Apache Kafka 和其他数据系统之间流式传输数据,并快速创建用于将大型数据集移入和移出 Kafka® 的连接器。

二、Kafka Connect 下载(sql server下载举例)

confluent官网下载地址:
https://www.confluent.io/hub/debezium/debezium-connector-sqlserver
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三、Kafka Connect 启动

1、修改配置文件(文件在kafka的安装目录有)

vim /opt/kafka/connect-config/connect-distributed.properties

bootstrap.servers=192.168.26.25:9092
 
group.id=connect-cluster

key.converter=org.apache.kafka.connect.json.JsonConverter
value.converter=org.apache.kafka.connect.json.JsonConverter
 
key.converter.schemas.enable=true
value.converter.schemas.enable=true
 
 
offset.storage.topic=connect-offsets
offset.storage.replication.factor=1
 
config.storage.topic=connect-configs
config.storage.replication.factor=1
 
 
status.storage.topic=connect-status
status.storage.replication.factor=1
 
offset.flush.interval.ms=10000
 
plugin.path=/data/qys/infra/kafka_2.12-3.6.1/plugins
topic.creation.default.partitions=1
topic.creation.default.replication.factor=1

主要修改内容:

  • 指定好bootstrap server地址 bootstrap.servers
  • 默认分区与分片 topic.creation.default.partitions=1 topic.creation.default.replication.factor=1
  • 插件地址 plugin.path=

2、下载插件

参照

二、Kafka Connect 下载

3、启动kafka-connect进程(前提kafka已经启动)

/opt/kafka/bin/connect-distributed.sh -daemon /opt/kafka/config/connect-distributed.properties

**

postman查看

**
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四、docker-compose启动kafka-connect示例

1、修改配置文件(文件在kafka的安装目录有)

vim ./kafka-connect/conf/connect-distributed.properties(参照上文

1

)

2、下载sql server

参照

二、Kafka Connect 下载

3、docker-compose.yaml

version: '2.4'
services:
  zookeeper:
    image: wurstmeister/zookeeper
    container_name: zk
    ports:
      -"2181:2181"
    restart: always
    volumes:
      -./zookeeper_data:/opt/zookeeper-3.4.13/data

  kafka1:
    image: wurstmeister/kafka:2.12-2.3.0
    container_name: kafka1
    ports:
      -"32771:9092" 
    environment:
      TZ: Asia/Shanghai  # 设置为所需的时区
      KAFKA_ADVERTISED_HOST_NAME: 192.168.180.46
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'true'
    volumes:
      -/var/run/docker.sock:/var/run/docker.sock
      -./kafka_data/kafka1_data:/kafka
    restart: always
    depends_on:
      - zookeeper

  kafka2:
    image: wurstmeister/kafka:2.12-2.3.0
    container_name: kafka2
    ports:
      -"32772:9092" 
    environment:
      TZ: Asia/Shanghai  # 设置为所需的时区
      KAFKA_ADVERTISED_HOST_NAME: 192.168.180.46
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'true'
    volumes:
      -/var/run/docker.sock:/var/run/docker.sock
      -./kafka_data/kafka2_data:/kafka
    restart: always
    depends_on:
      - zookeeper

  kafka3:
    image: wurstmeister/kafka:2.12-2.3.0
    container_name: kafka3
    ports:
      -"32773:9092" 
    environment:
      TZ: Asia/Shanghai  # 设置为所需的时区
      KAFKA_ADVERTISED_HOST_NAME: 192.168.180.46
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'true'
    volumes:
      -/var/run/docker.sock:/var/run/docker.sock
      -./kafka_data/kafka3_data:/kafka
    restart: always
    depends_on:
      - zookeeper

  kafka-connect:
    image: wurstmeister/kafka:2.12-2.3.0
    container_name: connect
    ports:
      -"38083:8083"
    entrypoint:
      -/opt/kafka/bin/connect-distributed.sh 
      -/opt/kafka/connect-config/connect-distributed.properties
    volumes:
      -/etc/localtime:/usr/share/zoneinfo/Asia/Shanghai
      -/var/run/docker.sock:/var/run/docker.sock
      -./kafka-connect/conf:/opt/kafka/connect-config-./kafka-connect/plugins:/opt/bitnami/kafka/plugin
    restart: always
    depends_on:
      - zookeeper

  kafka-client:
    image: wurstmeister/kafka:2.12-2.3.0
    entrypoint:
      - tail
      --f
      -/etc/hosts
    volumes:
      -/var/run/docker.sock:/var/run/docker.sock
      -./kafka-connect/conf:/opt/kafka/connect-config-./kafka-connect/plugins:/opt/kafka/plugins
    restart: always
    depends_on:
      - zookeeper

  kafdrop:
    image: obsidiandynamics/kafdrop
    container_name: kafdrop
    restart: "no"
    ports:
      -"9000:9000"
    environment:
      KAFKA_BROKERCONNECT: "kafka1:9092,kafka2:9092,kafka3:9092"
      TZ: Asia/Shanghai  # 设置为所需的时区
    depends_on:
      - zookeeper
      - kafka1
      - kafka2
      - kafka3

五、postman创建SQLserver的connec

1、sqlserver数据库开启cdc

-- 开启该库cdc
USE 库名
EXEC sys.sp_cdc_enable_db 
GO

-- 开启表CDC
use 库名;
EXEC sys.sp_cdc_enable_table 
@source_schema = N'schema名', 
@source_name = N'表名', 
@role_name = NULL, 
@supports_net_changes = 1 
GO

-- 关闭数据库CDC
USE 库名;
GO
EXEC sys.sp_cdc_disable_db

-- 关闭表的CDC功能
USE  库名;
GO
    EXEC sys.sp_cdc_disable_table
    @source_schema = N'schema名',
    @source_name   = N'表名',
    @capture_instance = N'schema名_表名'
GO

-- 查看数据库开启cdc检查
SELECT name ,is_cdc_enabled FROM sys.databases WHERE is_cdc_enabled = 1

-- 查看表cdc开启情况
use Libby;SELECT name ,is_tracked_by_cdc FROM sys.tables WHERE is_tracked_by_cdc = 1

2、创建sqlserver的connect

  • postman创建connect在这里插入图片描述
{"name": "cdc_mdata_test_3","config": {"connector.class": "io.debezium.connector.sqlserver.SqlServerConnector","database.hostname": "192.168.180.44","database.port": "1433","database.user": "sdp","database.password": "shared@123","database.dbname": "Libby","table.whitelist": "MappingData.test","database.server.name": "cdc_mdata_test_3","database.history.kafka.bootstrap.servers": "192.168.180.46:32771","database.history.kafka.topic": "cdc_mdata_test_3","transforms": "Reroute","transforms.Reroute.type": "io.debezium.transforms.ByLogicalTableRouter","transforms.Reroute.topic.regex": "cdc_mdata_(.*)","transforms.Reroute.topic.replacement": "cdc_md_combine","errors.tolerance": "all"}}
  • postman查看创建的connect在这里插入图片描述

六、connect的restapi

1、参考网址:

https://docs.confluent.io/platform/current/connect/references/restapi.html

2、常用restapi举例

infomethodurlconnect Clustergethttp://192.168.180.46:38083/connectorsgethttp://192.168.180.46:38083/connectorsexpand=status&expand=infogethttp://192.168.180.46:38083/connectors?expand=status&expand=infocreate-connectorposthttp://192.168.180.46:38083/connectorsdelete-connectordeletehttp://192.168.180.46:38083/connectors/cdc_mdata_test_3(connector名称)connector-configgethttp://192.168.180.46:38083/connectors/cdc_mdata_test_3(connector名称)/configconnector-statusgethttp://192.168.180.46:38083/connectors/cdc_mdata_test_3(connector名称)/statusconnector-pauseputhttp://192.168.180.46:38083/connectors/cdc_mdata_test_3/pauseconnector-resumeputhttp://192.168.180.46:38083/connectors/cdc_mdata_test_3/resumeconnector-stopputhttp://192.168.180.46:38083/connectors/mysql-connector-test46/stoptask-restartposthttp://192.168.180.46:38083/connectors/cdc_mdata_test_3/tasks/0/restarttask-statusgethttp://192.168.180.46:38083/connectors/cdc_mdata_test_3/tasks/0/status


本文转载自: https://blog.csdn.net/lihongbao80/article/details/136937970
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