How to work with NetSuite Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for NetSuite, Spark can work with live NetSuite data. This article describes how to connect to and query NetSuite data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live NetSuite data due to optimized data processing built into the driver. 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 (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze NetSuite data using native data types.

Getting Started

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Install the CData JDBC Driver for NetSuite

Download the CData JDBC Driver for NetSuite installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to NetSuite Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for NetSuite JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for NetSuite/lib/cdata.jdbc.netsuite.jar
   

2. With the shell running, you can connect to NetSuite with a JDBC URL and use the SQL Context load() function to read a table.

   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.

   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.

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

   Configure the connection to NetSuite, using the connection string generated above.

   scala> val netsuite_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:netsuite:Account Id=XABC123456;Password=password;User=user;Role Id=3;Version=2013_1;").option("dbtable","SalesOrder").option("driver","cdata.jdbc.netsuite.NetSuiteDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the NetSuite data as a temporary table:

   scala> netsuite_df.registerTable("salesorder")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> netsuite_df.sqlContext.sql("SELECT CustomerName, SalesOrderTotal FROM SalesOrder WHERE Class_Name = Furniture : Office").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for NetSuite in Apache Spark, you are able to perform fast and complex analytics on NetSuite data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.