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

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

Install the CData JDBC Driver for Asana

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

Start a Spark Shell and Connect to Asana Data

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

   You can optionally set the following to refine the data returned from Asana.

   • WorkspaceId: Set this to the globally unique identifier (gid) associated with your Asana Workspace to only return projects from the specified workspace. To get your workspace id, navigate to https://app.asana.com/api/1.0/workspaces while logged into Asana. This displays a JSON object containing your workspace name and Id.
   • ProjectId: Set this to the globally unique identifier (gid) associated with your Asana Project to only return data mapped under the specified project. Project IDs can be found in the URL of your project's Overview page. This will be the numbers directly after /0/.

   Connect Using OAuth Authentication

   You must use OAuth to authenticate with Asana. OAuth requires the authenticating user to interact with Asana using the browser. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.asana.jar

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

   Configure the connection to Asana, using the connection string generated above.

   scala> val asana_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:asana:OAuthClientId=YourClientId;OAuthClientSecret=YourClientSecret;CallbackURL='http://localhost:33333';").option("dbtable","projects").option("driver","cdata.jdbc.asana.AsanaDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Asana data as a temporary table:

   scala> asana_df.registerTable("projects")

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

   scala> asana_df.sqlContext.sql("SELECT Id, WorkspaceId FROM projects WHERE Archived = true").collect.foreach(println)

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

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