Connect to Postmark Data in HULFT Integrate

HULFT Integrate is a modern data integration platform that provides a drag-and-drop user interface to create cooperation flows, data conversion, and processing so that complex data connections are easier than ever to execute. When paired with the CData API Driver for JDBC, HULFT Integrate can work with live Postmark data. This article explains how to connect to Postmark and move the data into a CSV file.

With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live Postmark data. When you issue complex SQL queries to Postmark, the driver pushes supported SQL operations, like filters and aggregations, directly to Postmark and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Postmark data using native data types.

Enable Access to Postmark

To enable access to Postmark data from HULFT Integrate projects:

1. Copy the CData JDBC Driver JAR file (and license file if it exists), cdata.jdbc.api.jar (and cdata.jdbc.api.lic), to the jdbc_adapter subfolder for the Integrate Server
2. Restart the HULFT Integrate Server and launch HULFT Integrate Studio

Build a Project with Access to Postmark Data

Once you copy the JAR files, you can create a project with access to Postmark data. Start by opening Integrate Studio and creating a new project.

1. Name the project
2. Ensure the "Create script" checkbox is checked
3. Click Next
4. Name the script (e.g.: APItoCSV)

Once you create the project, add components to the script to copy Postmark data to a CSV file.

Configure an Execute Select SQL Component

Drag an "Execute Select SQL" component from the Tool Palette (Database -> JDBC) into the Script workspace.

1. In the "Required settings" tab for the Destination, click "Add" to create a new connection for Postmark. Set the following properties:
   • Name: Postmark Connection Settings
   • Driver class name: cdata.jdbc.api.APIDriver
   • URL: jdbc:api:Profile=C:\profiles\Postmark.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your-server-api-token"
     
     

     Built-in Connection String Designer

     For assistance constructing the JDBC URL, use the connection string designer built into the Postmark 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 API Key Authentication

     Postmark uses server API tokens to authenticate requests. Each Postmark server has its own API token, which controls access to messages, bounces, templates, and statistics associated with that server.

     To obtain your Server API Token, log in to your Postmark account and navigate to the server you want to connect to. Go to API Tokens under the server settings and copy the token labeled Server API token.

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

     • AuthScheme: Set this to APIKey.
     • APIKey: Set this to your Postmark Server API Token. This value is sent as the X-Postmark-Server-Token header on every request.

     Example connection string:

     Profile=C:\profiles\Postmark.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your-server-api-token"
     

     Connecting to Postmark

     Once the authentication is configured, you can connect to Postmark and query data from any of the available tables such as OutboundMessages, Bounces, and Templates.

     
2. Write your SQL statement. For example:

   SELECT ,  FROM Bounces

3. Click "Extraction test" to ensure the connection and query are configured properly
4. Click "Execute SQL statement and set output schema"
5. Click "Finish"

Configure a Write CSV File Component

Drag a "Write CSV File" component from the Tool Palette (File -> CSV) onto the workspace.

1. Set a file to write the query results to (e.g. Bounces.csv)
2. Set "Input data" to the "Select SQL" component
3. Add columns for each field selected in the SQL query
4. In the "Write settings" tab, check the checkbox to "Insert column names into first row"
5. Click "Finish"

Map Postmark Fields to the CSV Columns

Map each column from the "Select" component to the corresponding column for the "CSV" component.

Finish the Script

Drag the "Start" component onto the "Select" component and the "CSV" component onto the "End" component. Build the script and run the script to move Postmark data into a CSV file.

Download a free, 30-day trial of the CData API Driver for JDBC and start working with your live Postmark data in HULFT Integrate. Reach out to our Support Team if you have any questions.