Process & Analyze OData Services in Databricks (AWS)

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OData JDBC Driver

Easy-to-use OData client (consumer) enables developers to build Java applications that easily communicate with OData services.



Host the CData JDBC Driver for OData in AWS and use Databricks to perform data engineering and data science on live OData services.

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 OData services. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live OData services in Databricks.

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

Install the CData JDBC Driver in Databricks

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

Access OData Services in your Notebook: Python

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

Configure the Connection to OData

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

Step 1: Connection Information

driver = "cdata.jdbc.odata.ODataDriver"
url = "jdbc:odata:URL=http://services.odata.org/V4/Northwind/Northwind.svc;UseIdUrl=True;OData Version=4.0;Data Format=ATOM;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.odata.jar

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

The User and Password properties, under the Authentication section, must be set to valid OData user credentials. In addition, you will need to specify a URL to a valid OData server organization root or OData services file.

Load OData Services

Once you configure the connection, you can load OData services 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" , "Orders") \
	.load ()

Display OData Services

Check the loaded OData services by calling the display function.

Step 3: Checking the result

display (remote_table.select ("OrderName"))

Analyze OData Services 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 OData services for reporting, visualization, and analysis.

% sql

SELECT OrderName, Freight FROM SAMPLE_VIEW ORDER BY Freight DESC LIMIT 5

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