How to work with Zoho Inventory 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 Zoho Inventory, Spark can work with live Zoho Inventory data. This article describes how to connect to and query Zoho Inventory data from a Spark shell.

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

Install the CData JDBC Driver for Zoho Inventory

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

Start a Spark Shell and Connect to Zoho Inventory Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Zoho Inventory/lib/cdata.jdbc.zohoinventory.jar
   

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

   In order to connect to Zoho Inventory, set the following connection properties:

   • OrganizationId: set this to the ID associated with your specific Zoho Inventory organization
   • InitiateOAuth: set the to "GETANDREFRESH"
   • AccountsServer (Optional): set this full Account Server URL (only when manually refreshing the OAuth token)

   The connectors use OAuth to authenticate with Zoho Inventory. For more information, refer to the Getting Started section of the Help documentation.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.zohoinventory.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 Zoho Inventory, using the connection string generated above.

   scala> val zohoinventory_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:zohoinventory:OrganizationId=YourOrganizationId;AccountsServer=YourAccountServerURL;InitiateOAuth=GETANDREFRESH;").option("dbtable","Contacts").option("driver","cdata.jdbc.zohoinventory.ZohoInventoryDriver").load()
   

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

4. Register the Zoho Inventory data as a temporary table:

   scala> zohoinventory_df.registerTable("contacts")

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

   scala> zohoinventory_df.sqlContext.sql("SELECT Id, CustomerName FROM Contacts WHERE FirstName = Katherine").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 Zoho Inventory in Apache Spark, you are able to perform fast and complex analytics on Zoho Inventory 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.