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Work with Data in Apache Spark Using SQL

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

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

Install the CData JDBC Driver for

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

Start a Spark Shell and Connect to Data

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

    The primary method for performing basic authentication is to provide your login credentials, as follows:

    • User: Set this to your username.
    • Password: Set this to your password.

    Optionally, if you are making use of a sandbox environment, set the following:

    • UseSandbox: Set this to true if you are authenticating with a sandbox account.

    Authenticating Using Account Number and License Key

    Alternatively, you can authenticate using your account number and license key. Connect to data using the following:

    • AccountId: Set this to your Account Id. The Account Id is listed in the upper right hand corner of the admin console.
    • LicenseKey: Set this to your Avalara Avatax license key. You can generate a license key by logging into Avalara Avatax as an account adminstrator and navigating to Settings -> Reset License Key.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.avalaraavatax.jar

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

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

    scala> val avalaraavatax_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:avalaraavatax:User=MyUser;Password=MyPassword;").option("dbtable","Transactions").option("driver","cdata.jdbc.avalaraavatax.AvalaraAvataxDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the data as a temporary table:

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

    scala> avalaraavatax_df.sqlContext.sql("SELECT Id, TotalTax FROM Transactions WHERE Code = 051349").collect.foreach(println)

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

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