Dynamic Source prosjection when using Data flow on Azure Data Factory

Question

I have an data flow that compares two similar tables( the original and the new one), the new rows from the new file are added (appended) on the original one.

It works fine. My issue is that this Dataflow will be reused by 10 different files using parameters that are in a json file.

It works almost fine.

My big issue is that metadata differs from each table and data factory doesnt adapt accordingly.

As an example. file1 : file projection is perfect.

When data factory iterates to the second table, data factory still have the same projection even though metadata differs. the result is : empty columns ....

I need to data factory to dynamically find out metadata from each table on the source of my dataflow and adapt accordingly.

How can I do that ? there is no option under "optimize" to set some dynamic parameters.

Answer 1

Hi @Nuno Trigo ,

Thankyou for using Microsoft Q&A platform and thanks for posting your question here.

As I understand your query, you are trying to create a dynamic dataflow that can be utilized to perform data transformation and data movement for multiple tables. Kindly let me know if that is not the ask.

You will need to use a parameterized dataset that uses a dataset parameters for the name of the table. Then, pass a string parameter from the Foreach activity that contains the table name into the dataset parameter for that data flow activity.

In dataflow, you need to use schema less datasets for your Source and Sink transformations and either use "automap" on the Sink or write a rule using rule-based mapping to map columns based on patterns.

This video helps explain how to do it: ADF Transform Multiple Tables in Single Pipeline

Hope this will help. Please let us know if any further queries.

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