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

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

Install the CData JDBC Driver for Mode

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

Start a Spark Shell and Connect to Mode Data

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

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

2. With the shell running, you can connect to Mode 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 Mode Profile on disk (e.g. C:\profiles\Mode.apip). Next, set the ProfileSettings connection property to the connection string for Mode (see below).

   Mode API Profile Settings

   In Mode, go to My Account > API Tokens to generate an access token and access secret, which serve as the User and Password credentials respectively.

   Built-in Connection String Designer

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Mode.apip;ProfileSettings='User=your_api_access_token;Password=your_access_secret';").option("dbtable","DataSources").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 Mode data as a temporary table:

   scala> api_df.registerTable("datasources")

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

   scala> api_df.sqlContext.sql("SELECT Organization, Token FROM DataSources WHERE Public = true").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 Mode in Apache Spark, you are able to perform fast and complex analytics on Mode 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.