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Work with Salesforce Einstein Data in Apache Spark Using SQL

Access and process Salesforce Einstein Data in Apache Spark using the CData JDBC Driver.

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

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

Install the CData JDBC Driver for Salesforce Einstein

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

Start a Spark Shell and Connect to Salesforce Einstein Data

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

    Salesforce Einstein Analytics uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId and OAuthClientSecret by registering an app with Salesforce Einstein Analytics.

    See the Getting Started section of the CData data provider documentation for an authentication guide.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.sfeinsteinanalytics.jar

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

    Configure the connection to Salesforce Einstein, using the connection string generated above.

    scala> val sfeinsteinanalytics_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:sfeinsteinanalytics:OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://localhost:portNumber;").option("dbtable","Dataset_Opportunity").option("driver","cdata.jdbc.sfeinsteinanalytics.SFEinsteinAnalyticsDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Salesforce Einstein data as a temporary table:

    scala> sfeinsteinanalytics_df.registerTable("dataset_opportunity")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> sfeinsteinanalytics_df.sqlContext.sql("SELECT Name, CloseDate FROM Dataset_Opportunity WHERE StageName = Closed Won").collect.foreach(println)

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

Using the CData JDBC Driver for Salesforce Einstein in Apache Spark, you are able to perform fast and complex analytics on Salesforce Einstein 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.