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

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

Install the CData JDBC Driver for Microsoft Planner

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

Start a Spark Shell and Connect to Microsoft Planner Data

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

   You can connect without setting any connection properties for your user credentials. Below are the minimum connection properties required to connect.

   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
   • Tenant (optional): Set this if you wish to authenticate to a different tenant than your default. This is required to work with an organization not on your default Tenant.

   When you connect the Driver opens the MS Planner OAuth endpoint in your default browser. Log in and grant permissions to the Driver. The Driver then completes the OAuth process.

   1. Extracts the access token from the callback URL and authenticates requests.
   2. Obtains a new access token when the old one expires.
   3. Saves OAuth values in OAuthSettingsLocation to be persisted across connections.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.microsoftplanner.jar

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

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

   scala> val microsoftplanner_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:microsoftplanner:OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;CallbackURL=http://localhost:33333;").option("dbtable","Tasks").option("driver","cdata.jdbc.microsoftplanner.MicrosoftPlannerDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

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

   scala> microsoftplanner_df.registerTable("tasks")

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

   scala> microsoftplanner_df.sqlContext.sql("SELECT TaskId, startDateTime FROM Tasks WHERE TaskId = BCrvyMoiLEafem-3RxIESmUAHbLK").collect.foreach(println)

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

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