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Build FedEx-Connected ETL Processes in Google Data Fusion

Load the CData JDBC Driver into Google Data Fusion and create ETL processes with access live FedEx data.

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

Upload the CData JDBC Driver for FedEx to Google Data Fusion

Upload the CData JDBC Driver for FedEx to your Google Data Fusion instance to work with live FedEx 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.fedex-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.fedex) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.fedex.FedExDriver)
  5. Click "Finish"

Connect to FedEx Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live FedEx 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-fedex)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for FedEx. For example:

      jdbc:fedex:RTK=5246...;Server='https://gatewaybeta.fedex.com:443/xml';DeveloperKey='alsdkfjpqoewiru';Password='zxczxqqtyiuowkdlkn';AccountNumber='110371337';MeterNumber='240134349'; PrintLabelLocation='C:\users\username\documents\mylabels';CacheProvider='org.sqlite.JDBC';CacheConnection='jdbc:sqlite:C:\users\username\documents\fedexcache.db';

      There are five pieces of information needed in order to authenticate its actions with the FedEx service. This information is below.

      • Server: This controls the URL where the requests should be sent. Common testing options for this are: "https://gatewaybeta.fedex.com:443/xml", "https://wsbeta.fedex.com:443/xml", "https://gatewaybeta.fedex.com:443/web-service", and "https://wsbeta.fedex.com:443/web-service"
      • DeveloperKey: This is the identifier part of the authentication key for the sender's identity. This value will be provided to you by FedEx after registration.
      • Password: This is the secret part of the authentication key for the sender's identity. This value will be provided to you by FedEx after registration.
      • AccountNumber: This valid 9-digit FedEx account number is used for logging into the FedEx server.
      • MeterNumber: This value is used for submitting requests to FedEx. This value will be provided to you by FedEx after registration.
      • PrintLabelLocation: This property is required if one intends to use the GenerateLabels or GenerateReturnLabels stored procedures. This should be set to the folder location where generated labels should be stored.

      The Cache Database

      Many of the useful tasks available from FedEx require a lot of data. To ensure this data is easy to input and recall later, utilizes a cache database to make these requests. You must set the cache connection properties:

      • CacheProvider: The specific database you are using to cache with. For example, org.sqlite.JDBC.
      • CacheConnection: The connection string to be passed to the cache provider. For example, jdbc:sqlite:C:\users\username\documents\fedexcache.db

      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 FedEx JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.fedex.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 FedEx, i.e.:
      SELECT * FROM Senders
  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 fedex-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 FedEx data into

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

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