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

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

Install the CData JDBC Driver for SuiteCRM

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

Start a Spark Shell and Connect to SuiteCRM Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for SuiteCRM JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for SuiteCRM/lib/cdata.jdbc.suitecrm.jar
2. With the shell running, you can connect to SuiteCRM with a JDBC URL and use the SQL Context load() function to read a table.

   The User and Password properties must be set to valid SuiteCRM user credentials. Additionally, specify the URL to the SuiteCRM application, for example http://suite.crm.com.

   Note that retrieving SuiteCRM metadata can be expensive. It is advised that you store the metadata locally as described in the Caching Metadata section of the data provider help documentation.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.suitecrm.jar

   Fill in the connection properties and copy the connection string to the clipboard.

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

   scala> val suitecrm_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:suitecrm:URL=http://mySuiteCRM.com;User=myUser;Password=myPassword;").option("dbtable","Accounts").option("driver","cdata.jdbc.suitecrm.SuiteCRMDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the SuiteCRM data as a temporary table:

   scala> suitecrm_df.registerTable("accounts")

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

   scala> suitecrm_df.sqlContext.sql("SELECT Name, Industry FROM Accounts WHERE Industry = Manufacturing").collect.foreach(println)

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

Using the CData JDBC Driver for SuiteCRM in Apache Spark, you are able to perform fast and complex analytics on SuiteCRM data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.