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

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

Install the CData JDBC Driver in Databricks

To work with live Google Cloud Storage 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.googlecloudstorage.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Google Cloud Storage Data in your Notebook: Python

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

Configure the Connection to Google Cloud Storage

Connect to Google Cloud Storage 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.googlecloudstorage.GoogleCloudStorageDriver"
url = "jdbc:googlecloudstorage:RTK=5246...;ProjectId='project1';InitiateOAuth=GETANDREFRESH"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Google Cloud Storage 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.

Authenticate with a User Account

You can connect without setting any connection properties for your user credentials. After setting InitiateOAuth to GETANDREFRESH, you are ready to connect.

When you connect, the Google Cloud Storage OAuth endpoint opens in your default browser. Log in and grant permissions, then the OAuth process completes

Authenticate with a Service Account

Service accounts have silent authentication, without user authentication in the browser. You can also use a service account to delegate enterprise-wide access scopes.

You need to create an OAuth application in this flow. See the Help documentation for more information. After setting the following connection properties, you are ready to connect:

• InitiateOAuth: Set this to GETANDREFRESH.
• OAuthJWTCertType: Set this to "PFXFILE".
• OAuthJWTCert: Set this to the path to the .p12 file you generated.
• OAuthJWTCertPassword: Set this to the password of the .p12 file.
• OAuthJWTCertSubject: Set this to "*" to pick the first certificate in the certificate store.
• OAuthJWTIssuer: In the service accounts section, click Manage Service Accounts and set this field to the email address displayed in the service account Id field.
• OAuthJWTSubject: Set this to your enterprise Id if your subject type is set to "enterprise" or your app user Id if your subject type is set to "user".
• ProjectId: Set this to the Id of the project you want to connect to.

The OAuth flow for a service account then completes.

Load Google Cloud Storage Data

Once you configure the connection, you can load Google Cloud Storage 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" , "Buckets") \
	.load ()

Display Google Cloud Storage Data

Check the loaded Google Cloud Storage data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Name"))

Analyze Google Cloud Storage 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 Google Cloud Storage data for reporting, visualization, and analysis.

% sql

SELECT Name, OwnerId FROM SAMPLE_VIEW ORDER BY OwnerId DESC LIMIT 5

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