Process & Analyze EnterpriseDB 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 EnterpriseDB data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live EnterpriseDB data in Databricks.

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

Install the CData JDBC Driver in Databricks

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

👁 Loading the JDBC JAR File into AWS

Access EnterpriseDB Data in your Notebook: Python

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

Configure the Connection to EnterpriseDB

Connect to EnterpriseDB by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the 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.enterprisedb.EnterpriseDBDriver"
url = "jdbc:enterprisedb:RTK=5246...;User=postgres;Password=admin;Database=postgres;Server=127.0.0.1;Port=5444"

Built-in Connection String Designer

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

java -jar cdata.jdbc.enterprisedb.jar

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

The following connection properties are required in order to connect to data.

• Server: The host name or IP of the server hosting the EnterpriseDB database.
• Port: The port of the server hosting the EnterpriseDB database.

You can also optionally set the following:

• Database: The default database to connect to when connecting to the EnterpriseDB Server. If this is not set, the user's default database will be used.

Connect Using Standard Authentication

To authenticate using standard authentication, set the following:

• User: The user which will be used to authenticate with the EnterpriseDB server.
• Password: The password which will be used to authenticate with the EnterpriseDB server.

Connect Using SSL Authentication

You can leverage SSL authentication to connect to EnterpriseDB data via a secure session. Configure the following connection properties to connect to data:

• SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
• SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
• SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
• SSLClientCertType: The certificate type of the client store.
• SSLServerCert: The certificate to be accepted from the server.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load EnterpriseDB Data

Once you configure the connection, you can load EnterpriseDB 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 EnterpriseDB Data

Check the loaded EnterpriseDB data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("ShipName"))

👁 Displaying EnterpriseDB Data

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

% sql

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

👁 Displaying EnterpriseDB Data

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