Process & Analyze SAP Fieldglass Data in Azure Databricks

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SAP Fieldglass JDBC Driver

Provides Java developers with the power to easily connect their Web, Desktop, and Mobile applications to data in SAP Fieldglass Approvals, Audit Trails, Analytics, and more!



Host the CData JDBC Driver for SAP Fieldglass in Azure and use Databricks to perform data engineering and data science on live SAP Fieldglass data.

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live SAP Fieldglass data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live SAP Fieldglass data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live SAP Fieldglass data. 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 client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze SAP Fieldglass data using native data types.

Install the CData JDBC Driver in Azure

To work with live SAP Fieldglass data in Databricks, install the driver on your Azure cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "Upload" as the Library Source and "Jar" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.sapfieldglass.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for SAP Fieldglass\lib).

Connect to SAP Fieldglass from Databricks

With the JAR file installed, we are ready to work with live SAP Fieldglass data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query SAP Fieldglass, and create a basic report.

Configure the Connection to SAP Fieldglass

Connect to SAP Fieldglass by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.sapfieldglass.SAPFieldglassDriver"
url = "jdbc:sapfieldglass:RTK=5246...;EnvironmentURL='https://myinstance.com';Username=myuser;Password=mypassword;APIKey=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx;InitiateOAuth=GETANDREFRESH"

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.

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.

Load SAP Fieldglass Data

Once the connection is configured, you can load SAP Fieldglass data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "AuditTrails") \
	.load ()

Display SAP Fieldglass Data

Check the loaded SAP Fieldglass data by calling the display function.

display (remote_table.select ("Id"))

Analyze SAP Fieldglass Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the SAP Fieldglass data for analysis.

% sql

SELECT Id, Category FROM AuditTrails WHERE Company = 'CData'

The data from SAP Fieldglass is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for SAP Fieldglass and start working with your live SAP Fieldglass data in Apache NiFi. Reach out to our Support Team if you have any questions.