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Stream DB2 Data into Apache Kafka Topics



Access and stream DB2 data in Apache Kafka using the CData JDBC Driver and the Kafka Connect JDBC connector.

Apache Kafka is an open-source stream processing platform that is primarily used for building real-time data pipelines and event-driven applications. When paired with the CData JDBC Driver for IBM DB2, Kafka can work with live DB2 data. This article describes how to connect, access and stream DB2 data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the DB2 data received using Kafka infrastructure in the Confluent Platform.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live DB2 data. When you issue complex SQL queries to DB2, the driver pushes supported SQL operations, like filters and aggregations, directly to DB2 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze DB2 data using native data types.

Prerequisites

Before connecting the CData JDBC Driver for streaming DB2 data in Apache Kafka Topics, install and configure the following in the client Linux-based system.

  1. Confluent Platform for Apache Kafka
  2. Confluent Hub CLI Installation
  3. Self-Managed Kafka JDBC Source Connector for Confluent Platform

Define a New JDBC Connection to DB2 data

  1. Download CData JDBC Driver for IBM DB2 on a Linux-based system
  2. Follow the given instructions to create a new directory extract all the driver contents into it:
    1. Create a new directory named DB2 mkdir DB2
    2. Move the downloaded driver file (.zip) into this new directory mv DB2JDBCDriver.zip DB2/
    3. Unzip the CData DB2JDBCDriver contents into this new directory unzip DB2JDBCDriver.zip
  3. Open the DB2 directory and navigate to the lib folder ls cd lib/
  4. Copy the contents of the lib folder of DB2 into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.db2.jar file is successfully copied into the lib folder cp * ../../confluent-7.5.0/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/ cd ../../confluent-7.5.0/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
  5. Install the CData DB2 JDBC driver license using the given command, followed by your Name and Email ID java -jar cdata.jdbc.db2.jar -l
  6. Enter the product key or "TRIAL" (In the scenarios of license expiry, please contact our CData Support team)
  7. Start the Confluent local services using the command: confluent local services start

    This starts all the Confluent Services like Zookeeper, Kafka, Schema Registry, Kafka REST, Kafka CONNECT, ksqlDB and Control Center. You are now ready to use the CData JDBC driver for DB2 to stream messages using Kafka Connect Driver into Kafka Topics on ksqlDB.

    Start the Confluent local services
  8. Create the Kafka topics manually using a POST HTTP API Request: curl --location 'server_address:8083/connectors' --header 'Content-Type: application/json' --data '{ "name": "jdbc_source_cdata_db2_01", "config": { "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", "connection.url": "jdbc:db2:Server=10.0.1.2;Port=50000;User=admin;Password=admin;Database=test;", "topic.prefix": "db2-01-", "mode": "bulk" } }'

    Let us understand the fields used in the HTTP POST body (shown above):

    • connector.class: Specifies the Java class of the Kafka Connect connector to be used.
    • connection.url: The JDBC connection URL to connect with DB2 data.

      Built-in Connection String Designer

      For assistance in constructing the JDBC URL, use the connection string designer built into the DB2 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.db2.jar

      Fill in the connection properties and copy the connection string to the clipboard.

      Set the following properties to connect to DB2:

      • Server: Set this to the name of the server running DB2.
      • Port: Set this to the port the DB2 server is listening on.
      • Database: Set this to the name of the DB2 database.
      • User: Set this to the username of a user allowed to access the database.
      • Password: Set this to the password of a user allowed to access the database.

      You will also need to install the corresponding DB2 driver:

      • Windows: Install the IBM Data Server Provider for .NET.

        On Windows, installing the IBM Data Server Provider is sufficient, as the installation registers it in the machine.config.

      • Java: Install the IBM Data Server Driver for JDBC.

        In the Java version, place the IBM Data Server Driver JAR in the www\WEB-INF\lib\ folder for this application.

      Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

    • topic.prefix: A prefix that will be added to the Kafka topics created by the connector. It's set to "db2-01-".
    • mode: Specifies the mode in which the connector operates. In this case, it's set to "bulk", which suggests that the connector is configured to perform bulk data transfer.

    This request adds all the tables/contents from DB2 as Kafka Topics.

    Note: The IP Address (server) to POST the request (shown above) is the Linux Network IP Address.

  9. Run ksqlDB and list the topics. Use the commands: ksql list topics; List the Kafka Topics (BigCommerce is shown)
  10. To view the data inside the topics, type the SQL Statement: PRINT topic FROM BEGINNING;

Connecting with the Confluent Control Center

To access the Confluent Control Center user interface, ensure to run the "confluent local services" as described in the above section and type http://<server address>:9021/clusters/ on your local browser.

Connect with Confluent Control Center

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for IBM DB2 and start streaming DB2 data into Apache Kafka. Reach out to our Support Team if you have any questions.