Azure Data Factory (ADFv1) JSON Example for Salesforce Incremental Load of RelationalSource Pipeline

What I am sharing in this blob post isn't rocket science, but when I first began working with ADF, I would have had genuine feelings of gratitude if I could have found a JSON script example for incremental loads.  Consequently, this blog post is here in hopes that it finds someone who just needs a quick pick-me-up with ADF.

You will want to first reference my blog post on initial data loads with ADF because I will build here on the same resources and linked services.  What is different is the pipeline JSON script.  Follow the instructions for initial data load for everything else.

Using the Account table from Salesforce as an example, here is  what I call an incremental load pipeline:
{
  "name": "InboundPipeline-SalesforceIncrementalLoad",
  "properties": {
    "activities": [
      {
        "type": "Copy",
        "typeProperties": {
          "source": {
            "type": "RelationalSource",
            "query": "$$Text.Format('select * from Account where LastModifiedDate >= {{ts\\'{0:yyyy-MM-dd HH:mm:ss}\\'}} AND LastModifiedDate < {{ts\\'{1:yyyy-MM-dd HH:mm:ss}\\'}}', WindowStart, WindowEnd)"
          },
          "sink": {
            "type": "AzureDataLakeStoreSink",
            "writeBatchSize": 0,
            "writeBatchTimeout": "00:00:00"
          }
        },
        "inputs": [
          {
            "name": "InputDataset-Account"
          }
        ],
        "outputs": [
          {
            "name": "OutputDataset-Account"
          }
        ],
        "policy": {
          "timeout": "1.00:00:00",
          "concurrency": 1,
          "executionPriorityOrder": "NewestFirst",
          "style": "StartOfInterval",
          "retry": 3,
          "longRetry": 0,
          "longRetryInterval": "00:00:00"
        },
        "scheduler": {
          "frequency": "Day",
          "interval": 1
        },
        "name": "Activity-Account"
      }
    ],
    "start": "2017-04-17T19:48:55.667Z",
    "end": "2099-12-31T05:00:00Z",
    "isPaused": false,
    "pipelineMode": "Scheduled"
  },
}

Unfortunately at this time, the "query" property isn't that flexible.  I have been told by Microsoft that the next version of ADF scheduled for release fall 2017 will include input parameters.  I have tested and was able to use a REPLACE() function in the above SELECT but that is because under the covers, Microsoft is using the Simba ODBC driver for their Salesforce connection.  Each data source will have different capabilities within their "SELECT..."  Having identified several challenges with the current version of ADF, I was just happy to be able to use a WHERE clause.