Build Cassandra-Connected ETL Processes in Google Data Fusion

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Cassandra JDBC Driver

Connect Java applications with the Cassandra real-time NoSQL cloud database service. Use Apache Cassandra as the big data backend that powers your Java/J2EE applications.



Load the CData JDBC Driver into Google Data Fusion and create ETL processes with access live Cassandra data.

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Cassandra enables users to access live Cassandra data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Cassandra data to any data source natively supported in Google Data Fusion, this article walks through piping data from Cassandra to Google BigQuery,

Upload the CData JDBC Driver for Cassandra to Google Data Fusion

Upload the CData JDBC Driver for Cassandra to your Google Data Fusion instance to work with live Cassandra data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatacassandra-2020.jar

  1. Open your Google Data Fusion instance
  2. Click the to add an entity and upload a driver
  3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
  4. On the "Driver configuration" tab:
    • Name: Create a name for the driver (cdata.jdbc.cassandra) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.cassandra.CassandraDriver)
  5. Click "Finish"

Connect to Cassandra Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Cassandra data in Google Data Fusion Pipelines.

  1. Navigate to the Pipeline Studio to create a new Pipeline
  2. From the "Source" options, click "Database" to add a source for the JDBC Driver
  3. Click "Properties" on the Database source to edit the properties

    NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

    • Set the Label
    • Set Reference Name to a value for any future references (i.e.: cdata-cassandra)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for Cassandra. For example:

      jdbc:cassandra:RTK=5246...;Database=MyCassandraDB;Port=7000;Server=127.0.0.1;

      Set the Server, Port, and Database connection properties to connect to Cassandra. Additionally, to use internal authentication set the User and Password connection properties.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.cassandra.jar

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

    • Set Import Query to a SQL query that will extract the data you want from Cassandra, i.e.:
      SELECT * FROM Customer
  4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
  5. Click "Properties" on the BigQuery sink to edit the properties
    • Set the Label
    • Set Reference Name to a value like cassandra-bigquery
    • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
    • Set Dataset to a specific Google BigQuery dataset
    • Set Table to the name of the table you wish to insert Cassandra data into

With the Source and Sink configured, you are ready to pipe Cassandra data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Cassandra and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Cassandra pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Cassandra and start working with your live Cassandra data in Google Data Fusion today.