Process & Analyze SQL Analysis Services 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 SQL Analysis Services data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live SQL Analysis Services data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live SQL Analysis Services 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.ssas.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access SQL Analysis Services Data in your Notebook: Python

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

Configure the Connection to SQL Analysis Services

Connect to SQL Analysis Services 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.ssas.SSASDriver"
url = "jdbc:ssas:RTK=5246...;User=myuseraccount;Password=mypassword;URL=http://localhost/OLAP/msmdpump.dll;"

Built-in Connection String Designer

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

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

To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

• HTTP Authentication

  Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

• Windows (NTLM)

  Set the Windows User and Password and set AuthScheme to "NTLM".

• Kerberos and Kerberos Delegation

  To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

• SSL/TLS:

  By default, the data provider 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.

You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

Load SQL Analysis Services Data

Once you configure the connection, you can load SQL Analysis Services 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" , "Adventure_Works") \
	.load ()

Display SQL Analysis Services Data

Check the loaded SQL Analysis Services data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Fiscal_Year"))

Analyze SQL Analysis Services 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 SQL Analysis Services data for reporting, visualization, and analysis.

% sql

SELECT Fiscal_Year, Sales_Amount FROM SAMPLE_VIEW ORDER BY Sales_Amount DESC LIMIT 5

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