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

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

Install the CData JDBC Driver for Workable

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

Start a Spark Shell and Connect to Workable Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Workable/lib/cdata.jdbc.api.jar
   

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

   Using API Key Authentication

   Workable uses API key authentication to control access to the API. To obtain an API Key:

   1. Log in to your Workable account.
   2. Navigate to Settings > Integrations > API Access Tokens.
   3. Click "Generate API Token".
   4. Copy the generated token.

   After obtaining your API Key, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   Set the following in the ProfileSettings connection property:
   • APIKey: Set this to your Workable API Key.
   • Subdomain: Set this to your Workable account subdomain. For example, if your Workable URL is acmeinc.workable.com, then the Subdomain is 'acmeinc'.

   Example Connection String

   Profile=C:\profiles\Workable.apip;ProfileSettings='AuthScheme=APIKey;APIKey=my_api_key;Subdomain=acmeinc';
   

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.api.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 Workable, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Workable.apip;ProfileSettings='AuthScheme=APIKey;APIKey=my_api_key;Subdomain=acmeinc';").option("dbtable","Accounts").option("driver","cdata.jdbc.api.APIDriver").load()
   

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

4. Register the Workable data as a temporary table:

   scala> api_df.registerTable("accounts")

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

   scala> api_df.sqlContext.sql("SELECT , FROM Accounts WHERE = ").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 Workable in Apache Spark, you are able to perform fast and complex analytics on Workable 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.