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

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

Install the CData JDBC Driver for Microsoft Project

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

Start a Spark Shell and Connect to Microsoft Project Data

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

   The User and Password properties, under the Authentication section, must be set to valid Microsoft Project user credentials. In addition, you will need to specify a URL to a valid Microsoft Project server organization root or Microsoft Project services file.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.microsoftproject.jar

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

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

   scala> val microsoftproject_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:microsoftproject:User=myuseraccount;Password=mypassword;URL=http://myserver/myOrgRoot;").option("dbtable","Projects").option("driver","cdata.jdbc.microsoftproject.MicrosoftProjectDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Microsoft Project data as a temporary table:

   scala> microsoftproject_df.registerTable("projects")

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

   scala> microsoftproject_df.sqlContext.sql("SELECT ProjectName, ProjectActualCost FROM Projects WHERE ProjectName = Tax Checker").collect.foreach(println)

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

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