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

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

Install the CData JDBC Driver for ApprovalMax

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

Start a Spark Shell and Connect to ApprovalMax Data

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

   
   $ spark-shell --jars /CData/CData JDBC Driver for ApprovalMax/lib/cdata.jdbc.api.jar
   

2. With the shell running, you can connect to ApprovalMax 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 ApprovalMax Profile on disk (e.g. C:\profiles\ApprovalMax.apip). Next, set the ProfileSettings connection property to the connection string for ApprovalMax (see below).

   ApprovalMax API Profile Settings

   To authenticate to ApprovalMax and connect to your own data or to allow other users to connect to their data, the ApprovalMax Public API requires the OAuth 2.0 authorization code flow.

   First, you will need to register an OAuth application with ApprovalMax. Sign in to the ApprovalMax Developer Portal (https://developer.approvalmax.com/applications) and create a new application. Your OAuth application will be assigned a Client ID and a Client Secret, and you must register at least one Redirect URI (Callback URL).

   A Premium ApprovalMax subscription (or active trial) is required to use the Public API.

   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 shown in your application settings on the ApprovalMax Developer Portal.
   • OAuthClientSecret: Set this to the Client Secret that is shown in your application settings on the ApprovalMax Developer Portal.
   • CallbackURL: Set this to the Redirect URI that is registered in your application settings.
   • Scope: (Optional) Override the default OAuth scopes. The default value openid offline_access https://www.approvalmax.com/scopes/public_api/read grants read-only access to all tables in this profile and enables refresh tokens. Use the principle of least privilege when narrowing this scope.

   The OAuth Authorization URL is https://identity.approvalmax.com/connect/authorize and the Token URL is https://identity.approvalmax.com/connect/token. Both authorization_code and refresh_token grant types are supported.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the ApprovalMax 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 ApprovalMax, using the connection string generated above.

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\ApprovalMax.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=your_callback_url;").option("dbtable","UserProfiles").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 ApprovalMax data as a temporary table:

   scala> api_df.registerTable("userprofiles")

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

   scala> api_df.sqlContext.sql("SELECT UserId, Email FROM UserProfiles WHERE CompanyId = 00000000-0000-0000-0000-000000000000").collect.foreach(println)

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

   

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