Process & Analyze SAP Data in Databricks (AWS)

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 data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live SAP data in Databricks.

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

Getting Started

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Install the CData JDBC Driver in Databricks

To work with live SAP data in Databricks, install the driver on your Databricks 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.saperp.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

👁 Loading the JDBC JAR File into AWS

Access SAP Data in your Notebook: Python

With the JAR file installed, we are ready to work with live SAP 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, and create a basic report.

Configure the Connection to SAP

Connect to SAP by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the 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.

Step 1: Connection Information

driver = "cdata.jdbc.saperp.SAPERPDriver"
url = "jdbc:saperp:RTK=5246...;Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;Location=C:/mysapschemafolder;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.saperp.jar

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

The driver supports connecting to an SAP system using the SAP Java Connector (SAP JCo). Install the files (sapjco3.jar and sapjco3.dll) to the appropriate directory for the hosting application or platform. See the "Getting Started" chapter in the help documentation for information on using the SAP JCo files.

In addition, you can connect to an SAP system using Web services (SOAP). To use Web services, you must enable SOAP access to your SAP system and set the Client, RFCUrl, User, and Password properties, under the Authentication section.

For more information, see this guide on obtaining the connection properties needed to connect to any SAP system.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load SAP Data

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

Step 2: Reading the data

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

Display SAP Data

Check the loaded SAP data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("MANDT"))

👁 Displaying SAP Data

Analyze SAP Data in Databricks

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

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the SAP data for reporting, visualization, and analysis.

% sql

SELECT MANDT, MBRSH FROM SAMPLE_VIEW ORDER BY MBRSH DESC LIMIT 5

👁 Displaying SAP Data

The data from SAP 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 ERP and start working with your live SAP data in Databricks. Reach out to our Support Team if you have any questions.