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Work with Amazon Marketplace Data in Apache Spark Using SQL

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

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

Install the CData JDBC Driver for Amazon Marketplace

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

Start a Spark Shell and Connect to Amazon Marketplace Data

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

    To connect to the Amazon Marketplace Webservice (MWS), AWSAccessKeyId, MWSAuthToken, AWSSecretKey and SellerId are required. You can optionally set the Marketplace property. For more information on obtaining values for these properties, refer to the Help documentation.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.amazonmarketplace.jar

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

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

    scala> val amazonmarketplace_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:amazonmarketplace:AWS Access Key Id=myAWSAccessKeyId;AWS Secret Key=myAWSSecretKey;MWS Auth Token=myMWSAuthToken;Seller Id=mySellerId;Marketplace=United States;").option("dbtable","Orders").option("driver","cdata.jdbc.amazonmarketplace.AmazonMarketplaceDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Amazon Marketplace data as a temporary table:

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

    scala> amazonmarketplace_df.sqlContext.sql("SELECT AmazonOrderId, OrderStatus FROM Orders WHERE IsReplacementOrder = True").collect.foreach(println)

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

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