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

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

Install the CData JDBC Driver in Databricks

To work with live AlloyDB 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.alloydb.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access AlloyDB Data in your Notebook: Python

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

Configure the Connection to AlloyDB

Connect to AlloyDB 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.alloydb.AlloyDBDriver"
url = "jdbc:alloydb:RTK=5246...;User=alloydb;Password=admin;Database=alloydb;Server=127.0.0.1;Port=5432"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the AlloyDB 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.

The following connection properties are usually required in order to connect to AlloyDB.

• Server: The host name or IP of the server hosting the AlloyDB database.
• User: The user which will be used to authenticate with the AlloyDB server.
• Password: The password which will be used to authenticate with the AlloyDB server.

You can also optionally set the following:

• Database: The database to connect to when connecting to the AlloyDB Server. If this is not set, the user's default database will be used.
• Port: The port of the server hosting the AlloyDB database. This property is set to 5432 by default.

Authenticating with Standard Authentication

Standard authentication (using the user/password combination supplied earlier) is the default form of authentication.

No further action is required to leverage Standard Authentication to connect.

Authenticating with pg_hba.conf Auth Schemes

There are additional methods of authentication available which must be enabled in the pg_hba.conf file on the AlloyDB server.

Find instructions about authentication setup on the AlloyDB Server here.

Authenticating with MD5 Authentication

This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to md5.

Authenticating with SASL Authentication

This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to scram-sha-256.

Authenticating with Kerberos

The authentication with Kerberos is initiated by AlloyDB Server when the ∏ is trying to connect to it. You should set up Kerberos on the AlloyDB Server to activate this authentication method. Once you have Kerberos authentication set up on the AlloyDB Server, see the Kerberos section of the help documentation for details on how to authenticate with Kerberos.

Load AlloyDB Data

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

Display AlloyDB Data

Check the loaded AlloyDB data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("ShipName"))

Analyze AlloyDB 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 AlloyDB data for reporting, visualization, and analysis.

% sql

SELECT ShipName, ShipCity FROM SAMPLE_VIEW ORDER BY ShipCity DESC LIMIT 5

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