Explore Geographical Relationships in Spark Data with Power Map



Create data visualizations with Spark data in Power Map.

The CData ODBC Driver for Spark is easy to set up and use with self-service analytics solutions like Power BI: Microsoft Excel provides built-in support for the ODBC standard. This article shows how to load the current Spark data into Excel and start generating location-based insights on Spark data in Power Map.

Create an ODBC Data Source for Spark

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.

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.

Import Spark Data into Excel

You can import data into Power Map either from an Excel spreadsheet or from Power Pivot. For a step-by-step guide to use either method to import Spark data, see the "Using the ODBC Driver" section in the help documentation.

Geocode Spark Data

After importing the Spark data into an Excel spreadsheet or into PowerPivot, you can drag and drop Spark entities in Power Map. To open Power Map, click any cell in the spreadsheet and click Insert -> Map.

In the Choose Geography menu, Power Map detects the columns that have geographic information. In the Geography and Map Level menu in the Layer Pane, you can select the columns you want to work with. Power Map then plots the data. A dot represents a record that has this value. When you have selected the geographic columns you want, click Next.

Select Measures and Categories

You can then simply select columns: Measures and categories are automatically detected. The available chart types are Stacked Column, Clustered Column, Bubble, Heat Map, and Region.

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Apache Spark Icon Apache Spark ODBC Driver

The Spark ODBC Driver is a powerful tool that allows you to connect with Apache Spark, directly from any applications that support ODBC connectivity.

The Driver maps SQL to Spark SQL, enabling direct standard SQL-92 access to Apache Spark.