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

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

Install the CData JDBC Driver for Todoist

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

Start a Spark Shell and Connect to Todoist Data

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

   Start by setting the Profile connection property to the location of the Todoist Profile on disk (e.g. C:\profiles\Todoist.apip). Next, set the ProfileSettings connection property to the connection string for Todoist (see below).

   Todoist API Profile Settings

   To authenticate to Todoist, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

   First, you will need to register an OAuth application with Todoist. To do so, go to App Management Console, create a new application and configure a valid OAuth redirect URL. Your Oauth application will be assigned a client id and a client secret.

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
   • OAuthClientId: Set this to the client_id that is specified in you app settings.
   • OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
   • CallbackURL: Set this to the Redirect URI that is specified in your app settings

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.api.jar

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

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Todoist.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;").option("dbtable","Tasks").option("driver","cdata.jdbc.api.APIDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Todoist data as a temporary table:

   scala> api_df.registerTable("tasks")

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

   scala> api_df.sqlContext.sql("SELECT Id, Priority FROM Tasks WHERE Completed = false").collect.foreach(println)

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

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