How to work with SAP Data in Apache Spark using SQL

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

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

Getting Started

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Install the CData JDBC Driver for SAP

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

Start a Spark Shell and Connect to SAP Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for SAP JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for SAP/lib/cdata.jdbc.saperp.jar
   

2. With the shell running, you can connect to SAP with a JDBC URL and use the SQL Context load() function to read a table.

   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.

   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.

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

   Configure the connection to SAP, using the connection string generated above.

   scala> val saperp_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:saperp:Host=sap.mydomain.com;User=EXT90033;Password=xxx;Client=800;System Number=09;ConnectionType=Classic;Location=C:/mysapschemafolder;").option("dbtable","MARA").option("driver","cdata.jdbc.saperp.SAPERPDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the SAP data as a temporary table:

   scala> saperp_df.registerTable("mara")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> saperp_df.sqlContext.sql("SELECT MANDT, MBRSH FROM MARA WHERE ERNAM = BEHRMANN").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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