Connect to and Query Spark Data in QlikView over ODBC

The CData ODBC drivers expand your ability to work with data from more than 200 data sources. QlikView is a business discovery platform that provides self-service BI for all business users in an organization. This article outlines simple steps to connect to Spark data using the CData ODBC driver and create data visualizations in QlikView.

The CData ODBC drivers offer unmatched performance for interacting with live Spark data in QlikView due to optimized data processing built into the driver. When you issue complex SQL queries from QlikView to Spark, the driver pushes supported SQL operations, like filters and aggregations, directly to Spark and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Spark data using native QlikView data types.

Connect to Spark as an ODBC Data Source

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

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

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Populate a Chart with Spark Data

The steps below supply the results of an SQL query to a visualization in QlikView. In this article, you will create a bar chart with the query below:

1. Click File -> Edit Script (or click the Edit Script button in the Toolbar).
2. On the Data tab, select ODBC in the Database menu and click Connect.
3. Select the DSN (CData SparkSQL Sys) in the resulting dialog. A command like the following is generated: ODBC CONNECT TO [CData SparkSQL Sys];
4. Enter the SQL query directly into the script with the SQL command (or click Select to build the query in the SELECT statement wizard). SQL SELECT City, Balance FROM Customers;

   Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to Spark, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed client-side by the CData SQL engine embedded in the driver.

5. Close the script editor and reload the document to execute the script.
6. Click Tools -> Quick Chart Wizard. In the wizard, select the chart type. This example uses a bar chart. When building the chart, you have access to the fields from Spark, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
7. When defining Dimensions, select City in the First Dimension menu.
8. When defining Expressions, click the summary function you want and select Balance in the menu.

9. Finish the wizard to generate the chart. The CData ODBC Driver for Spark connects to live Spark data, so the chart can be refreshed to see real-time changes. Live connections are possible and effective, thanks to the high-performance data processing native to CData ODBC Drivers.