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

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

Install the CData JDBC Driver for Zoho Projects

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

Start a Spark Shell and Connect to Zoho Projects Data

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

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

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

   The connector uses OAuth to authenticate with Zoho Projects. CData Software has already registered an OAuth application with Zoho Project which is embedded and used to authenticate.

   If you use the embedded credentials, set the InitiateOAuth connection property to "GETANDREFRESH".

   If you would prefer to use your own custom OAuth app, see the Help documentation.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.zohoprojects.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 Projects, using the connection string generated above.

   scala> val zohoprojects_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:zohoprojects:InitiateOAuth=GETANDREFRESH;").option("dbtable","Portals").option("driver","cdata.jdbc.zohoprojects.ZohoProjectsDriver").load()
   

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

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

   scala> zohoprojects_df.registerTable("portals")

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

   scala> zohoprojects_df.sqlContext.sql("SELECT Id, Name FROM Portals WHERE CrmPartner = true").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 Projects in Apache Spark, you are able to perform fast and complex analytics on Zoho Projects 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.