January 2, 2019 at 2:02 pm
Hi Team,
Is there a way to combine data from two flat file destinations from two different data flow tasks into one flat file?
Let me know if I am not clear on my question.
Happy New year!!
January 2, 2019 at 2:23 pm
I'm assuming what you mean is you want to be ale to 'append' the data from the second data flow task to the data from another data flow task.
In your second 'Flat File Destination Editor' there is a check box for 'Overwrite data in the file'., just remove the check in the box.
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we travel not to escape life but for life not to escape us
Don't fear failure, fear regret.
January 2, 2019 at 2:26 pm
If you are wanting to be able to write out 2 different formats to the same file, you will need to create 2 different 'layout' connections in your connection manager.
I have a process that writes a 'header' row to a flat file, kind of a summary, then another data flow tasks add the 'detail' records, both are different formats.
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we travel not to escape life but for life not to escape us
Don't fear failure, fear regret.
January 2, 2019 at 2:33 pm
There are several ways to do that, is the format of the data the same? One option is to use a union in the same data flow and join the two data sets that way. Another way is to have both data flows write to the same file but only have the first data flow overwrite the file.
January 2, 2019 at 2:33 pm
Sorry - not clear...are you trying to pull data from a single source flat file and split it into two destination files? Or do you have 2 source files that you want to put into a single destination file?
If you are looking to take two source files into a single destination - you have several options depending on how that needs to be done. You can UNION the data - which means each source file has the same (or similar) structure and the destination will end up with separate rows. That is - if source one has 10 rows and source two has 10 rows - you would end up with 20 rows in the destination file.
If you need to join the data and have a value in both sources that matches - you can merge/join the rows from each source.
Jeffrey Williams
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