Stream CSV Data into Apache Kafka Topics

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 the CData JDBC Driver for 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 -r /path/to/CData JDBC Driver for CSV/lib/* /usr/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
   cd /usr/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:URI=/PATH/TO/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 CData JDBC Driver for CSV. 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.

     Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

     CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

     Setting connection properties for local files

     Set the URI property to local folder path.

     Setting connection properties for files stored in Amazon S3

     To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

     • AWSAccessKey: AWS Access Key (username)
     • AWSSecretKey: AWS Secret Key

     Setting connection properties for files stored in Box

     To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

     Dropbox

     To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

     SharePoint Online (SOAP)

     To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

     SharePoint Online REST

     To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

     Google Drive

     To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

     👁 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.

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.