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

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

Install the CData JDBC Driver for MailerSend

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

Start a Spark Shell and Connect to MailerSend Data

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

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

2. With the shell running, you can connect to MailerSend with a JDBC URL and use the SQL Context load() function to read a table.

   The MailerSend API uses API Key authentication via a Bearer token in the Authorization request header.

   Using API Key Authentication

   Your MailerSend API token is required to create a connection. To obtain your API token:

   1. Log into your MailerSend account at app.mailersend.com.
   2. Navigate to Settings > API Tokens in your account dashboard.
   3. Click Generate new token, provide a name and select the appropriate permissions.
   4. Copy the generated API token.

   After obtaining your API token, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your MailerSend API token.

   Example connection string:

   Profile=C:\profiles\Mailersend.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_token';
   

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the MailerSend 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.

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Mailersend.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_token';").option("dbtable","Activity").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 MailerSend data as a temporary table:

   scala> api_df.registerTable("activity")

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

   scala> api_df.sqlContext.sql("SELECT , FROM Activity WHERE DomainId = domain123").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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