Stream CSV Data into Apache Kafka Topics



Access and stream CSV 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 CSV, Kafka can work with live CSV data. This article describes how to connect, access and stream CSV data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the CSV 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 CSV data. When you issue complex SQL queries to CSV, the driver pushes supported SQL operations, like filters and aggregations, directly to CSV 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 CSV data using native data types.

Prerequisites

Before connecting the CData JDBC Driver for streaming CSV 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 CSV data

  1. Download CData JDBC Driver for CSV 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 CSV mkdir CSV
    2. Move the downloaded driver file (.zip) into this new directory mv CSVJDBCDriver.zip CSV/
    3. Unzip the CData CSVJDBCDriver contents into this new directory unzip CSVJDBCDriver.zip
  3. Open the CSV directory and navigate to the lib folder ls cd lib/
  4. Copy the contents of the lib folder of CSV into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.csv.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 CSV JDBC driver license using the given command, followed by your Name and Email ID java -jar cdata.jdbc.csv.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 CSV 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_csv_01", "config": { "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", "connection.url": "jdbc:csv:DataSource=MyCSVFilesFolder;", "topic.prefix": "csv-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 CSV data.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.csv.jar

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

      The DataSource property must be set to a valid local folder name.

      Also, specify the IncludeFiles property to work with text files having extensions that differ from .csv, .tab, or .txt. Specify multiple file extensions in a comma-separated list. You can also set Extended Properties compatible with the Microsoft Jet OLE DB 4.0 driver. Alternatively, you can provide the format of text files in a Schema.ini file.

      Set UseRowNumbers to true if you are deleting or updating in CSV. This will create a new column with the name RowNumber which will be used as key for that table.

      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 "csv-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 CSV 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 CSV and start streaming CSV data into Apache Kafka. Reach out to our Support Team if you have any questions.

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