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

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

Install the CData JDBC Driver for Elorus

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

Start a Spark Shell and Connect to Elorus Data

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

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

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

   Start by setting the Profile connection property to the location of the Elorus Profile on disk (e.g. C:\profiles\Elorus.apip). Next, set the ProfileSettings connection property to the connection string for Elorus (see below).

   Elorus API Profile Settings

   Obtain your API Key from your User Profile in the top-right corner of Elorus. Find your Organization ID under Settings > Organization.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Elorus 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 Elorus, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Elorus.apip;ProfileSettings='APIKey=your_api_key;OrganizationId=your_org_id';").option("dbtable","BillAttachments").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 Elorus data as a temporary table:

   scala> api_df.registerTable("billattachments")

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

   scala> api_df.sqlContext.sql("SELECT BillId, Id FROM BillAttachments WHERE BillId = 1").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 Elorus in Apache Spark, you are able to perform fast and complex analytics on Elorus 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.