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Pipe PayPal Data in Google Data Fusion

Load the CData JDBC Driver into Google Data Fusion and pipe live PayPal data to any supported data platform.

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for PayPal enables users to access live PayPal data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping PayPal data to any data source natively supported in Google Data Fusion, this article walks through piping data from PayPal to Google BigQuery,

Upload the CData JDBC Driver for PayPal to Google Data Fusion

Upload the CData JDBC Driver for PayPal to your Google Data Fusion instance to work with live PayPal data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format -.jar. For example: cdata.jdbc.paypal-2019.jar

  1. Open your Google Data Fusion instance
  2. Click the to add an entity and upload a driver
  3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
  4. On the "Driver configuration" tab:
    • Name: Create a name for the driver (cdata.jdbc.paypal) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.paypal.PayPalDriver)
  5. Click "Finish"

Pipe PayPal Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live PayPal data in Google Data Fusion Pipelines.

  1. Navigate to the Pipeline Studio to create a new Pipeline
  2. From the "Source" options, click "Database" to add a source for the JDBC Driver
  3. Click "Properties" on the Database source to edit the properties
    • Set the Label
    • Set Reference Name to a value for any future references (i.e.: cdata-paypal)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for PayPal. For example:

      jdbc:paypal:RTK=5246...;Schema=SOAP;Username=sandbox-facilitator_api1.test.com;Password=xyz123;Signature=zx2127;InitiateOAuth=GETANDREFRESH;

      The provider surfaces tables from two PayPal APIs. The APIs use different authentication methods.

      • The REST API uses the OAuth standard. To authenticate to the REST API, you will need to set the OAuthClientId, OAuthClientSecret, and CallbackURL properties.
      • The Classic API requires Signature API credentials. To authenticate to the Classic API, you will need to obtain an API username, password, and signature.

      See the "Getting Started" chapter of the help documentation for a guide to obtaining the necessary API credentials.

      To select the API you want to work with, you can set the Schema property to REST or SOAP. By default the SOAP schema will be used.

      For testing purposes you can set UseSandbox to true and use sandbox credentials.

      To use the JDBC Driver in Google Data Fusion, you will need to set the RTK property in the JDBC URL. You can view the licensing file included in the installation for information on how to set this property.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.paypal.jar

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

    • Set Import Query to a SQL query that will extract the data you want from PayPal, i.e.:
      SELECT * FROM Transactions
  4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
  5. Click "Properties" on the BigQuery sink to edit the properties
    • Set the Label
    • Set Reference Name to a value like paypal-bigquery
    • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
    • Set Dataset to a specific Google BigQuery dataset
    • Set Table to the name of the table you wish to insert PayPal data into

With the Source and Sink configured, you are ready to pipe PayPal data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from PayPal and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex PayPal pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for PayPal and start working with your live PayPal data in Google Data Fusion today.