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Work with SAP Fieldglass Data in Apache Spark Using SQL

Access and process SAP Fieldglass Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for SAP Fieldglass, Spark can work with live SAP Fieldglass data. This article describes how to connect to and query SAP Fieldglass data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live SAP Fieldglass data due to optimized data processing built into the driver. When you issue complex SQL queries to SAP Fieldglass, the driver pushes supported SQL operations, like filters and aggregations, directly to SAP Fieldglass 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 work with and analyze SAP Fieldglass data using native data types.

Install the CData JDBC Driver for SAP Fieldglass

Download the CData JDBC Driver for SAP Fieldglass installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to SAP Fieldglass Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for SAP Fieldglass JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for SAP Fieldglass/lib/cdata.jdbc.sapfieldglass.jar
  2. With the shell running, you can connect to SAP Fieldglass with a JDBC URL and use the SQL Context load() function to read a table.

    To authenticate, you will need to specify the Username, Password, APIKey, and EnvironmentURL connection properties.

    To obtain an APIKey, log in to the SAP API Business Hub and click on Get API Key.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.sapfieldglass.jar

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

    scala> val sapfieldglass_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:sapfieldglass:EnvironmentURL='https://myinstance.com';Username=myuser;Password=mypassword;APIKey=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx;").option("dbtable","AuditTrails").option("driver","cdata.jdbc.sapfieldglass.SAPFieldglassDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the SAP Fieldglass data as a temporary table:

    scala> sapfieldglass_df.registerTable("audittrails")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> sapfieldglass_df.sqlContext.sql("SELECT Id, Category FROM AuditTrails WHERE Company = CData").collect.foreach(println)

    You will see the results displayed in the console, similar to the following:

Using the CData JDBC Driver for SAP Fieldglass in Apache Spark, you are able to perform fast and complex analytics on SAP Fieldglass data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 160+ CData JDBC Drivers and get started today.