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  1. DZone
  2. Data Engineering
  3. Big Data
  4. Confluent Kafka Installation and Demo

Confluent Kafka Installation and Demo

Learn how to insert rows to SQLite-DB and show those rows on an auto-created topic on Kafka via the JDBC-source connector.

By 
Ersin Gulbahar user avatar
Ersin Gulbahar
·
Oct. 26, 21 · Tutorial
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About KAFKA and Confluent 

Apache Kafka is an open-source community distributed event streaming platform used by thousands of corporations for high-performance streaming, data pipelines, and critical applications. Kafka was developed by the Apache Software Foundation written in Scala and Java. 

Confluent Open Source is a developer-optimized distribution of Apache Kafka. Confluent Platform is a full-scale data streaming platform that enables you to easily access, store, and manage data as continuous, real-time streams. Confluent is a more complete distribution of Apache Kafka. It streamlines the admin operations procedures with much ease.

Confluent Kafka Installation And Demo

The goal is to insert rows to SQLite-DB and show those rows on an auto-created topic on Kafka via the JDBC-source connector.

Environment: Red Hat Linux 7.x

  1. Download Tarball
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    curl -O http://packages.confluent.io/archive/6.0/confluent-6.0.1.tar.gz
  2. Extract tar.gz
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    tar -xvf tar/confluent-6.0.1.tar.gz
  3. Define Confluent variables
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    export CONFLUENT_HOME=/mydata/myuser/confluent-6.0.1
    export PATH=$PATH:$CONFLUENT_HOME/bin
  4. Install confluent-hub and kafka connect jdbc
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    $CONFLUENT_HOME/bin/confluent-hub install --no-prompt confluentinc/kafka-connect-datagen:latest
    confluent-hub install confluentinc/kafka-connect-jdbc:10.0.1

    You can see the confluent hub on your local web.

    http://localhost:9021/clusters
  5. Define JDBC-source file to /mydata/myuser/confluent-6.0.1/etc/kafka-connect-jdbc/:
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    name=test-sqlite-jdbc-autoincrement
    connector.class=io.confluent.connect.jdbc.JdbcSourceConnector
    value.converter=org.apache.kafka.connect.json.JsonConverter
    value.converter.schemas.enable=false 
    tasks.max=1
    connection.url=jdbc:sqlite:test.db
    mode=incrementing
    incrementing.column.name=id
    topic.prefix=turkcell.sqlite-jdbc-
  6. Run confluent services up:
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    confluent local services connect start

    The output like below:Kafka zookeeper output

  7. Load jdbc-source to the connector:
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    confluent local services connect connector load jdbc-source -c /mydata/myuser/confluent-6.0.1/etc/kafka-connect-jdbc/source-quickstart-sqlite.properties
  8. You can create SQLite-DB; create a table and insert rows:
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    cd confluent-6.0.1/
    sqlite3 test.db
    sqlite> CREATE TABLE ttech(id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL, name VARCHAR(255)); 
    sqlite> INSERT INTO ttech(name) VALUES('turkcell'); 

    You can see a row like this:

    Kafka row

  9. Look at the connect log to see if Kafka-source-JDBC fails or works successfully:
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    confluent local services connect log
  10. Finally, look at Kafka topic to see your newly-added record. I use Kafka Tool to check:

Kafka record

Some Useful Commands and Screenshots

  1.  See connector list: confluent local services connect connector --list
  2. See connector content: confluent local services connect connector config jdbc-source
  3. Unload connector: confluent local services connect connector unload jdbc-source
  4. See connect log: confluent local services connect log
  5. Change formatter from Avro to JSON in this file: /mydata/myuser/confluent-6.0.1/etc/kafka/connect-distributed.properties
  6. If you use schema-registry:
    •  Add key-value schema:
      • APL
         
        curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema": "{\"type\":\"record\",\"name\":\"your_table\",\"fields\":[{\"name\":\"ID\",\"type\":\"long\"}]}"}' http://localhost:8091/subjects/your_table-key/versions
    • Check it is installed:
      • APL
         
        curl -X GET http://localhost:8091/subjects
    • Add the connector to sync to the Oracle table:
      • APL
         
        curl -XPOST --header "Content-Type: application/json"  localhost:8083/connectors  -d 
        '{  
            "name": "sink_my_table",  
            "config": {    
                "connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",    
        		"tasks.max": 3,   
        		"connection.url": "jdbc:oracle:thin:@my.db:1961:MYSERVICE",
                "connection.user": "ora_user",    
                "connection.password": "XXXXXX",    
        		"table.name.format": "my_table",
                "topics": "my_table",
                "auto.create": "false",
        		"delete.enabled": "true",
        		"pk.mode": "record_key",
        		"pk.fields": "ID",
        		"insert.mode": "upsert",
        		"transforms": "TimestampConverter1,TimestampConverter2,TimestampConverter3",
        		"transforms.TimestampConverter1.type": "org.apache.kafka.connect.transforms.TimestampConverter$Value",
        		"transforms.TimestampConverter1.field": "RECORDDATE",
        		"transforms.TimestampConverter1.target.type": "Timestamp",
        		"transforms.TimestampConverter2.type": "org.apache.kafka.connect.transforms.TimestampConverter$Value",
        		"transforms.TimestampConverter2.field": "STARTDATE",
        		"transforms.TimestampConverter2.target.type": "Timestamp",
        		"transforms.TimestampConverter3.type": "org.apache.kafka.connect.transforms.TimestampConverter$Value",
        		"transforms.TimestampConverter3.field": "ENDDATE",
        		"transforms.TimestampConverter3.target.type": "Timestamp"
        		
            }
        }' 
    • Look at connector config information:
      • APL
         
        curl -X GET http://localhost:8083/connectors/sink_my_table
    • Look connector status:
      • APL
         
        curl -X GET http://localhost:8083/connectors/sink_my_table/status
    • Delete connector:
      • APL
         
        curl -X DELETE http://localhost:8083/connectors/sink_my_table

Screenshot of Confluent control center

screenshot of confluent overview page

screenshot of topics

screenshot of connect clusters

screenshot of JDBC source

Hope it helps you!

kafka

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Related

  • Event-Driven Pipelines With Apache Pulsar and Go
  • Contract-First Integration: Building Scalable Systems With Flyway, OpenAPI, and Kafka
  • Kafka and Spark Structured Streaming in Enterprise: The Patterns That Hold Up Under Pressure
  • Exactly-Once Processing: Myth vs Reality

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