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

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

Install the CData JDBC Driver for SharePoint Excel Services

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

Start a Spark Shell and Connect to SharePoint Excel Services Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for SharePoint Excel Services/lib/cdata.jdbc.excelservices.jar
   

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

   The URL, User, and Password properties, under the Authentication section, must be set to valid credentials for SharePoint Online, SharePoint 2010, or SharePoint 2013. Additionally, the Library property must be set to a valid SharePoint Document Library and the File property must be set to a valid .xlsx file in the indicated Library.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.excelservices.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 SharePoint Excel Services, using the connection string generated above.

   scala> val excelservices_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:excelservices:URL=https://myorg.sharepoint.com;[email protected];Password=password;File=Book1.xlsx;").option("dbtable","Account").option("driver","cdata.jdbc.excelservices.ExcelServicesDriver").load()
   

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

4. Register the SharePoint Excel Services data as a temporary table:

   scala> excelservices_df.registerTable("account")

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

   scala> excelservices_df.sqlContext.sql("SELECT Name, AnnualRevenue FROM Account WHERE Industry = Floppy Disks").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 SharePoint Excel Services in Apache Spark, you are able to perform fast and complex analytics on SharePoint Excel Services 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.