Mapping columns from JSON in an Azure SQL Data Flow task

Question

I am attempting a simple SELECT action on a Source JSON dataset in an Azure Data Factory data flow, but I am getting an error message that none of the columns from my source are valid. I use the exact configuration as the video, except instead of a CSV file, I use a JSON file.

In the video, at 1:12, you can see that after configuring the source dataset, the source projection shows all of the columns from the source schema. Below is a screen shot from the tutorial video: image.png

And below is a screen shot from my attempt: (I blurred the column names because they match column names from a vendor app)

Note in my projection, I am unable to modify the data types or the format. I'm not sure why not, but I don't need to modify either so I moved on. I did try with a CSV and I was able to modify the data types. I'm assuming this is a JSON thing, but I'm noting here just in case there is some configuration that I should take a look at.

At 6:48 in the video, you'll see the user add a select task, exactly as I have done. Below is a screen shot of the select task in the tutorial immediately following adding the task:

Notice the source columns all appear. Below is a screen shot of my select task:

I'm curious why the column names are missing? If I type them in manually, I get an error: "Column not found"

For reference, below are screen shots of my Data Source setup. I'm using a Data Lake Storage Gen2 Linked Service connected via Managed Identity and the AutoResolvingIntegrationRuntime. Note that I tried to do this with a CSV as well. I was able to edit the datatype and format on a CSV, but I get the same column not found error on the next step.

Answer 1

Try doing this in a different browser or clear your browser cache. It may just be a formatting thing in the auto-generated JSON. This has happened to me before.