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Dataiku is a data science and machine learning platform used for data preparation, analysis, visualization, and AI/ML model deployment, enabling collaborative and efficient data-driven decision-making. When paired with the CData JDBC Driver for Apache Kafka, Dataiku enhances data integration, preparation, real-time analysis, and reliable model deployment for Kafka data.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Kafka data. When you issue complex SQL queries to Kafka, the driver pushes supported SQL operations, like filters and aggregations, directly to Kafka 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 Kafka data using native data types.
This article shows how you can easily integrate to Kafka using CData JDBC Driver for Apache Kafka in Dataiku DSS (Data Science Studio) platform, allowing you to prepare the data and build custom AI/ML models.
In this section, we will explore how to set up Dataiku, as previously introduced, with Kafka data. Be sure to install Dataiku DSS (On-Prem version) for your preferred operating system, beforehand.
First, install the CData JDBC Driver for Apache Kafka on the same machine as Dataiku. The JDBC Driver will be installed in the following path:
C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.apachekafka.jar
To use the CData JDBC driver in Dataiku, you must create a new SQL database connection and add the JDBC Driver JAR file in the DSS connection settings.
Generate a JDBC URL for connecting to Kafka, beginning with jdbc:apachekafka: followed by a series of semicolon-separated connection string properties.
Set BootstrapServers and the Topic properties to specify the address of your Apache Kafka server, as well as the topic you would like to interact with.
You may be required to trust the server certificate. In such cases, specify the TrustStorePath and the TrustStorePassword if necessary.
For assistance in constructing the JDBC URL, use the connection string designer built into the Kafka JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.apachekafka.jar
Fill in the connection properties and copy the connection string to the clipboard.
π Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)A typical JDBC URL is given below:
jdbc:apachekafka:User=admin;Password=pass;BootStrapServers=https://localhost:9091;Topic=MyTopic;
Next, select the SQL dialect of your choice. Here, we have selected 'SQL Server' as the preferred dialect. Click on Create. If the connection is successful, a prompt will display, saying 'Connection OK'.
To prepare data flows, create dashboards, analyze the Kafka data, and build AI and ML models in the Dataiku DSS platform, you need to first create a new project.
To test the Kafka connection and analyze the Kafka data, write a query in the query compiler and click Run. The queried/filtered Kafka data results will then appear on the screen.
π Query the datasource to test the connection.Download a free, 30-day trial of the CData JDBC Driver for Apache Kafka to integrate with Dataiku, and effortlessly build custom AI/ML models from Kafka data.
Reach out to our Support Team if you have any questions.
Download a free trial of the Apache Kafka Driver to get started:
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