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Process & Analyze Sybase Data in Azure Databricks

Host the CData JDBC Driver for Sybase in Azure and use Databricks to perform data engineering and data science on live Sybase 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 Sybase data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Sybase data in Databricks.

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

Install the CData JDBC Driver in Azure

To work with live Sybase 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.sybase.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Sybase\lib).

Connect to Salesforce from Databricks

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

Configure the Connection to Sybase

Connect to Sybase by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL.

driver = "cdata.jdbc.sybase.SybaseDriver"
url = "jdbc:sybase:User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.sybase.jar

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

To authenticate with Sybase, set User and Password. Additionally, set IntegratedSecurity; to true to use Windows authentication otherwise, Sybase authentication is used. Set the Server and Database properties. To secure connections with TLS/SSL, set Encrypt to true.

Load Sybase Data

Once the connection is configured, you can load Sybase 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" , "Products") \
	.load ()

Display Sybase Data

Check the loaded Sybase data by calling the display function.

display (remote_table.select ("Id"))

Analyze Sybase 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 Sybase data for analysis.

% sql

SELECT Id, ProductName FROM Products WHERE ProductName = Konbu

The data from Sybase 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 Sybase and start working with your live Sybase data in Apache NiFi. Reach out to our Support Team if you have any questions.