Conduktor kafka 20m series1/9/2024 ![]() ![]() The events are written to the following topics with the dbserver1 prefix (the name of the connector): Open the Topics tab in Conduktor to see all of the newly created topics that will show the change data capture as part of the debezium connector.Īfter we have added the Debezium MySQL connector in Conduktor we can see it starts monitoring the database for data change events, in this case, it is a database for inventory with specific topics related to different tables. Step 4: View all created topics in Conduktor Initially, it might take a few seconds for the topics to get created. We can now see our Debezium MySql connector with its current status and all topics. ![]() We will carry out the following four steps.ġ - 2 version: '2' 3 4 services: 5 zookeeper: 6 image: confluentinc/cp-zookeeper:6.0.0 7 hostname: zookeeper 8 container_name: zookeeper 9 ports: 10 - "2181:2181" 11 environment: 12 ZOOKEEPER_CLIENT_PORT: 2181 13 ZOOKEEPER_TICK_TIME: 2000 14 15 broker: 16 image: confluentinc/cp-kafka:6.0.0 17 hostname: broker 18 container_name: broker 19 depends_on: 20 - zookeeper 21 ports: 22 - "29092:29092" 23 - "9999:9999" 24 environment: 25 KAFKA_BROKER_ID: 1 26 KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181' 27 KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT 28 KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://broker:9092,PLAINTEXT_HOST://localhost:29092 29 KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1 30 KAFKA_TRANSACTION_STATE_LOG_MIN_ISR: 1 31 KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR: 1 32 KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS: 0 33 KAFKA_JMX_PORT: 9999 34 KAFKA_JMX_HOSTNAME: localhost 35 36 connect: 37 image: confluentinc/cp-kafka-connect:latest 38 hostname: connect 39 container_name: connect 40 depends_on: 41 - broker 42 ports: 43 - "8083:8083" 44 command: 45 - bash 46 -c 47 - |Ĥ8 confluent-hub install -no-prompt confluentinc/kafka-connect-jdbc:latestĤ9 confluent-hub install -no-prompt confluentinc/kafka-connect-datagen:latestĥ0 confluent-hub install -no-prompt debezium/debezium-connector-mysql:latestĥ2 environment: 53 CONNECT_BOOTSTRAP_SERVERS: "broker:9092" 54 CONNECT_REST_ADVERTISED_HOST_NAME: connect 55 CONNECT_REST_PORT: 8083 56 CONNECT_GROUP_ID: compose-connect-group 57 CONNECT_CONFIG_STORAGE_TOPIC: docker-connect-configs 58 CONNECT_CONFIG_STORAGE_REPLICATION_FACTOR: 1 59 CONNECT_OFFSET_FLUSH_INTERVAL_MS: 10000 60 CONNECT_OFFSET_STORAGE_TOPIC: docker-connect-offsets 61 CONNECT_OFFSET_STORAGE_REPLICATION_FACTOR: 1 62 CONNECT_STATUS_STORAGE_TOPIC: docker-connect-status 63 CONNECT_STATUS_STORAGE_REPLICATION_FACTOR: 1 64 CONNECT_KEY_CONVERTER: .storage.StringConverter 65 CONNECT_VALUE_CONVERTER: .json.JsonConverter 66 CONNECT_PLUGIN_PATH: "/usr/share/java,/usr/share/confluent-hub-components" 67 CONNECT_LOG4J_LOGGERS: =ERROR,=ERROR,org.reflections=ERROR 68 KAFKA_JMX_OPTS: =true .authenticate=false .ssl=false =connect .local.only=false .rmi.port=5555 .port=5555 69 70 mysql: 71 image: debezium/example-mysql:1.7 72 hostname: mysql 73 container_name: mysql 74 depends_on: 75 - broker 76 environment: 77 - MYSQL_ROOT_PASSWORD=debezium 78 - MYSQL_USER=mysqluser 79 - MYSQL_PASSWORD=mysqlpw 80 ports: 81 - '3306:3306'Īfter saving the above YAML file as docker-compose.yml, open your command line interface or terminal and run the following command:Ĥ "connector.class" : "io." ,ġ1 "" : "dbserver1" ,ġ2 "" : "inventory" ,ġ3 ".servers" : "broker:9092" ,ġ4 "" : "schema-changes.inventory" 15 } TutorialĪs an example, we are going to look at utilizing Debezium in Conduktor and accomplishing this with Docker. Ultimately, Debezium lets you track data changes, replicate data, update caches, sync data between microservices, and create audit logs among much more. ![]() He goes into more detail on the plans for Debezium going forward in this talk. Debezium Use CasesĪccording to Gunnar Morling from Redhat, tech lead for Debezium, CDC means "liberation for your data". The processed data can then be streamed out to a sink database such as ElasticSearch or a data warehouse. The changelog itself can be stored in Kafka, where a series of deployed programs are able to transform, aggregate, and join the data together. As your database has a change occur you can track that directly in Kafka.Īs illustrated in figure 2, one method of achieving this is by capturing the changelogs of a database upstream in either a Postgres or MySql database using the Debezium Kafka connectors. Thanks to Kafka Connect and Debezium, change data capture, or CDC is now a common pattern that allows you to expose database changes as events into Kafka. ![]()
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