Process & Analyze SAP Business Warehouse 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 Business Warehouse data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live SAP Business Warehouse data in Databricks.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live SAP Business Warehouse data. When you issue complex SQL queries to SAP Business Warehouse, the driver pushes supported SQL operations, like filters and aggregations, directly to SAP Business Warehouse 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 Business Warehouse data using native data types.
Install the CData JDBC Driver in Databricks
To work with live SAP Business Warehouse data in Databricks, install the driver on your Databricks cluster.
- Navigate to your Databricks administration screen and select the target cluster.
- On the Libraries tab, click "Install New."
- Select "Upload" as the Library Source and "Jar" as the Library Type.
- Upload the JDBC JAR file (cdata.jdbc.sapbusinesswarehouse.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).
Access SAP Business Warehouse Data in your Notebook: Python
With the JAR file installed, we are ready to work with live SAP Business Warehouse 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 Business Warehouse, and create a basic report.
Configure the Connection to SAP Business Warehouse
Connect to SAP Business Warehouse by referencing the JDBC Driver class 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.
Step 1: Connection Information
driver = "cdata.jdbc.sapbusinesswarehouse.SAPBusinessWarehouseDriver" url = "jdbc:sapbusinesswarehouse:RTK=5246...;URL=https://mysapserver:8000;AuthScheme=Basic;User=username;Password=password;"
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the SAP Business Warehouse JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.sapbusinesswarehouse.jar
Fill in the connection properties and copy the connection string to the clipboard.
To connect to SAP Business Warehouse, set the URL property to a valid SAP Business Warehouse server base URL. The driver must connect to SAP Business Warehouse instances hosted over HTTP with XMLA access.
The driver supports the following authentication schemes via the AuthScheme property:
- None: Anonymous authentication, if available on the server.
- Basic: Set User and Password and set AuthScheme to Basic.
- Kerberos: See the Using Kerberos section of the help documentation for the required Kerberos properties.
By default, the driver attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.
Load SAP Business Warehouse Data
Once you configure the connection, you can load SAP Business Warehouse 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" , "Sales") \ .load ()
Display SAP Business Warehouse Data
Check the loaded SAP Business Warehouse data by calling the display function.
Step 3: Checking the result
display (remote_table.select ("CustomerCount"))
Analyze SAP Business Warehouse 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 Business Warehouse data for reporting, visualization, and analysis.
% sql SELECT CustomerCount, City FROM SAMPLE_VIEW ORDER BY City DESC LIMIT 5
The data from SAP Business Warehouse 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 Business Warehouse and start working with your live SAP Business Warehouse data in Databricks. Reach out to our Support Team if you have any questions.