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

Prerequisites

Before connecting the CData JDBC Driver for streaming Databricks 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 Databricks data

1. Download CData JDBC Driver for Databricks 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 Databricks mkdir Databricks
   2. Move the downloaded driver file (.zip) into this new directory mv DatabricksJDBCDriver.zip Databricks/
   3. Unzip the CData DatabricksJDBCDriver contents into this new directory unzip DatabricksJDBCDriver.zip
3. Open the Databricks directory and navigate to the lib folder ls cd lib/
4. Copy the contents of the lib folder of Databricks into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.databricks.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 Databricks JDBC driver license using the given command, followed by your Name and Email ID java -jar cdata.jdbc.databricks.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 Databricks to stream messages using Kafka Connect Driver into Kafka Topics on ksqlDB.

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_databricks_01", "config": { "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", "connection.url": "jdbc:databricks:Server=127.0.0.1;Port=443;TransportMode=HTTP;HTTPPath=MyHTTPPath;UseSSL=True;User=MyUser;Password=MyPassword;", "topic.prefix": "databricks-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 Databricks data.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.databricks.jar

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

     To connect to a Databricks cluster, set the properties as described below.

     Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

     • Server: Set to the Server Hostname of your Databricks cluster.
     • HTTPPath: Set to the HTTP Path of your Databricks cluster.
     • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).

   • topic.prefix: A prefix that will be added to the Kafka topics created by the connector. It's set to "databricks-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 Databricks 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;
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 Databricks and start streaming Databricks data into Apache Kafka. Reach out to our Support Team if you have any questions.