Ready to get started?

Learn more about the CData JDBC Driver for Magento or download a free trial:

Download Now

Process & Analyze Magento Data in Azure Databricks

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

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

Install the CData JDBC Driver in Azure

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

Connect to Salesforce from Databricks

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

Configure the Connection to Magento

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

driver = "cdata.jdbc.magento.MagentoDriver"
url = "jdbc:magento:OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://127.0.0.1:33333;Url=https://mymagentohost.com;InitiateOAuth=GETANDREFRESH"

Built-in Connection String Designer

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

java -jar cdata.jdbc.magento.jar

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

Magento uses the OAuth 1 authentication standard. To connect to the Magento REST API, you will need to obtain values for the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with your Magento system. See the "Getting Started" section in the help documentation for a guide to obtaining the OAuth values and connecting.

You will also need to provide the URL to your Magento system. The URL depends on whether you are using the Magento REST API as a customer or administrator.

  • Customer: To use Magento as a customer, make sure you have created a customer account in the Magento homepage. To do so, click Account -> Register. You can then set the URL connection property to the endpoint of your Magento system.

  • Administrator: To access Magento as an administrator, set CustomAdminPath instead. This value can be obtained in the Advanced settings in the Admin menu, which can be accessed by selecting System -> Configuration -> Advanced -> Admin -> Admin Base URL.

    If the Use Custom Admin Path setting on this page is set to YES, the value is inside the Custom Admin Path text box; otherwise, set the CustomAdminPath connection property to the default value, which is "admin".

Load Magento Data

Once the connection is configured, you can load Magento 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 Magento Data

Check the loaded Magento data by calling the display function.

display (remote_table.select ("Name"))

Analyze Magento 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 Magento data for analysis.

% sql

SELECT Name, Price FROM Products

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