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

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

Install the CData JDBC Driver for XML

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

Start a Spark Shell and Connect to XML Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for XML/lib/cdata.jdbc.xml.jar
   

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

   Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) XML Files

   CData Drivers let you work with XML files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

   Setting connection properties for local files

   Set the URI property to local folder path.

   Setting connection properties for files stored in Amazon S3

   To connect to XML file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended XML files exist. In addition, at least set these properties:

   • AWSAccessKey: AWS Access Key (username)
   • AWSSecretKey: AWS Secret Key

   Setting connection properties for files stored in Box

   To connect to XML file(s) within Box, set the URI property to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect to Box.

   Dropbox

   To connect to XML file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

   SharePoint Online (SOAP)

   To connect to XML file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended XML file. Set User, Password, and StorageBaseURL.

   SharePoint Online REST

   To connect to XML file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended XML file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

   Google Drive

   To connect to XML file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

   The property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your XML data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling XML Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.xml.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 XML, using the connection string generated above.

   scala> val xml_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:xml:URI=C:/people.xml;DataModel=Relational;").option("dbtable","people").option("driver","cdata.jdbc.xml.XMLDriver").load()
   

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

4. Register the XML data as a temporary table:

   scala> xml_df.registerTable("people")

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

   scala> xml_df.sqlContext.sql("SELECT [ personal.name.first ], [ personal.name.last ] FROM people WHERE [ personal.name.last ] = Roberts").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 XML in Apache Spark, you are able to perform fast and complex analytics on XML 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.