Visualize Live Spark Data in Tableau

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Apache Spark Tableau Connector

The fastest and easiest way to connect Tableau to Apache Spark data. Includes comprehensive high-performance data access, real-time integration, extensive metadata discovery, and robust SQL-92 support.

Use the CData Tableau Connector for Spark and Tableau Desktop to visualize live Spark data.

Tableau is a visual analytics platform transforming the way businesses use data to solve problems. When paired with the CData Tableau Connector for Spark, you can easily get access to live Spark data within Tableau. This article shows how to connect to Spark in Tableau and build a simple chart.

The CData Tableau Connectors enable high-speed access to live Spark data in Tableau. Once you install the connector, you simply authenticate with Spark and you can immediately start building responsive, dynamic visualizations and dashboards. By surfacing Spark data using native Tableau data types and handling complex filters, aggregations, & other operations automatically, CData Tableau Connectors grant seamless access to Spark data.

NOTE: The CData Tableau Connectors require Tableau 2020.3 or higher. If you are using an older version of Tableau, you will need to use the CData JDBC Driver for Spark. If you wish to connect to Spark data in Tableau Cloud, you will need to use CData Connect Cloud.

Connect to Spark in Tableau

Open Tableau and click More under Connect -> To a Server. Select "Spark by CData," then configure the connection and click "Sign In."

Set the Server, Database, User, and Password connection properties to connect to SparkSQL.

Discover Schemas and Query Data

  1. Select CData from the Database pull-down menu.
  2. Select SparkSQL from the Schema pull-down menu.
  3. Drag the tables and views you wish to visualize onto the join area. You can include multiple tables.
  4. Select Update Now or Automatically Update. Update Now lets you preview the first 10,000 rows of the data source (or enter the number of rows you want to see in the Rows text box). Automatically Update automatically reflects the changes in the preview area.
  5. Click the tab for your worksheet. Columns are listed as Dimensions and Measures, depending on the data type. The CData Tableau Connector discovers data types automatically, allowing you to leverage the powerful data processing and visualization features of Tableau.
  6. Drag a field from the Dimensions or Measures area to Rows or Columns. Tableau creates column or row headers.
  7. Select one of the chart types from the Show Me tab. Tableau displays the chart type that you selected.

Using the CData Tableau Connector for Spark with Tableau, you can easily create robust visualizations and reports on Spark data. Download a free, 30-day trial and get started today.