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

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

Install the CData JDBC Driver for Act CRM

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

Start a Spark Shell and Connect to Act CRM Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Act CRM/lib/cdata.jdbc.actcrm.jar
   

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

   The and properties, under the Authentication section, must be set to valid Act! user credentials. In addition to the authentication values, see the following:

   • Connecting to Act! Premium

     In addition to the authentication values, the to Act! is also required; for example https://eup1-iis-04.eu.hosted.act.com/.

     Additionally, you must specify the you will connect to. This is found by going to the About Act! Premium menu of your account, at the top right of the page, in the ? menu. Use the Database Name in the window that appears.

   • Connecting to Act! Premium Cloud

     To connect to your Act! Premium Cloud account, you also need to specify the property. This property is found in the URL address of the Cloud account; for example https://eup1-iis-04.eu.hosted.act.com/ActCloudName/.

   Note that retrieving ActCRM metadata can be expensive. It is advised that you set the property to store the metadata locally.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.actcrm.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 Act CRM, using the connection string generated above.

   scala> val actcrm_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:actcrm:URL=https://myActCRMserver.com;User=myUser;Password=myPassword;ActDatabase=MyDB;").option("dbtable","Activities").option("driver","cdata.jdbc.actcrm.ActCRMDriver").load()
   

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

4. Register the Act CRM data as a temporary table:

   scala> actcrm_df.registerTable("activities")

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

   scala> actcrm_df.sqlContext.sql("SELECT ActivityDisplayName, Subject FROM Activities WHERE Subject = Sample subject").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 Act CRM in Apache Spark, you are able to perform fast and complex analytics on Act CRM 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.