Process & Analyze Neo4J 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 Neo4J data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live Neo4J data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Neo4J data. When you issue complex SQL queries to Neo4J, the driver pushes supported SQL operations, like filters and aggregations, directly to Neo4J 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 Neo4J data using native data types.

Install the CData JDBC Driver in Databricks

To work with live Neo4J 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.neo4j.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Neo4J Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Neo4J 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 Neo4J, and create a basic report.

Configure the Connection to Neo4J

Connect to Neo4J 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.neo4j.Neo4jDriver"
url = "jdbc:neo4j:RTK=5246...;Server=localhost;Port=7474;User=my_user;Password=my_password;"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Neo4J 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.

To connect to Neo4j, set the following connection properties:

• Server: The server hosting the Neo4j instance.
• Port: The port on which the Neo4j service is running. The provider connects to port 7474 by default.
• User: The username of the user using the Neo4j instance.
• Password: The password of the user using the Neo4j instance.

Load Neo4J Data

Once you configure the connection, you can load Neo4J 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" , "ProductCategory") \
	.load ()

Display Neo4J Data

Check the loaded Neo4J data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("CategoryId"))

Analyze Neo4J 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 Neo4J data for reporting, visualization, and analysis.

% sql

SELECT CategoryId, CategoryName FROM SAMPLE_VIEW ORDER BY CategoryName DESC LIMIT 5

The data from Neo4J 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 Neo4J and start working with your live Neo4J data in Databricks. Reach out to our Support Team if you have any questions.