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Get the Report →Process & Analyze NetSuite Data in Databricks (AWS)
Use CData, AWS, and Databricks to perform data engineering and data science on live NetSuite 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 NetSuite data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live NetSuite data in Databricks.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live NetSuite data. When you issue complex SQL queries to NetSuite, the driver pushes supported SQL operations, like filters and aggregations, directly to NetSuite 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 NetSuite data using native data types.
About NetSuite Data Integration
CData provides the easiest way to access and integrate live data from Oracle NetSuite. Customers use CData connectivity to:
- Access all editions of NetSuite, including Standard, CRM, and OneWorld.
- Connect with all versions of the SuiteTalk API (SOAP-based) and SuiteQL, which functions like SQL, enabling easier data querying and manipulation.
- Access predefined and custom reports through support for Saved Searches.
- Securely authenticate with Token-based and OAuth 2.0, ensuring compatibility and security for all use cases.
- Use SQL stored procedures to perform functional actions like uploading or downloading files, attaching or detaching records or relationships, retrieving roles, getting extra table or column info, getting job results, and more.
Customers use CData solutions to access live NetSuite data from their preferred analytics tools, Power BI and Excel. They also use CData's solutions to integrate their NetSuite data into comprehensive databases and data warehouse using CData Sync directly or leveraging CData's compatibility with other applications like Azure Data Factory. CData also helps Oracle NetSuite customers easily write apps that can pull data from and push data to NetSuite, allowing organizations to integrate data from other sources with NetSuite.
For more information about our Oracle NetSuite solutions, read our blog: Drivers in Focus Part 2: Replicating and Consolidating ... NetSuite Accounting Data.
Getting Started
Install the CData JDBC Driver in Databricks
To work with live NetSuite data in Databricks, install the driver on your Databricks cluster.
- Navigate to your Databricks administration screen and select the target cluster.
- On the Libraries tab, click "Install New."
- Select "Upload" as the Library Source and "Jar" as the Library Type.
- Upload the JDBC JAR file (cdata.jdbc.netsuite.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).
Access NetSuite Data in your Notebook: Python
With the JAR file installed, we are ready to work with live NetSuite 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 NetSuite, and create a basic report.
Configure the Connection to NetSuite
Connect to NetSuite 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.netsuite.NetSuiteDriver" url = "jdbc:netsuite:RTK=5246...;Account Id=XABC123456;Password=password;User=user;Role Id=3;Version=2013_1;"
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the NetSuite JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.netsuite.jar
Fill in the connection properties and copy the connection string to the clipboard.
The User and Password properties, under the Authentication section, must be set to valid NetSuite user credentials. In addition, the AccountId must be set to the ID of a company account that can be used by the specified User. The RoleId can be optionally specified to log in the user with limited permissions.
See the "Getting Started" chapter of the help documentation for more information on connecting to NetSuite.
Load NetSuite Data
Once you configure the connection, you can load NetSuite 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" , "SalesOrder") \ .load ()
Display NetSuite Data
Check the loaded NetSuite data by calling the display function.
Step 3: Checking the result
display (remote_table.select ("CustomerName"))
Analyze NetSuite 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 NetSuite data for reporting, visualization, and analysis.
% sql SELECT CustomerName, SalesOrderTotal FROM SAMPLE_VIEW ORDER BY SalesOrderTotal DESC LIMIT 5
The data from NetSuite 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 NetSuite and start working with your live NetSuite data in Databricks. Reach out to our Support Team if you have any questions.