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Hi,
I have a pipeline reads an excel file with a table with around 20 rows. each row has parameters to use on a post request.
excel looks like:
pipeline should send this requests ang save json file that get in response.
This works fine when using Azure Data Factory, completing in about a minute or two. However, when running the same flow on Microsoft Fabric, it keeps running indefinitely.
some of the tasks show following error:
-> ErrorCode=FlattenFailedInHierarchicalFlattenStage,'Type=Microsoft.DataTransfer.Common.Shared.HybridDeliveryException,Message=Failed to flatten data, error message: Exception of type 'System.OutOfMemoryException' was thrown.,Source=Microsoft.DataTransfer.ClientLibrary,''Type=System.OutOfMemoryException,Message=Exception of type 'System.OutOfMemoryException' was thrown.,Source=mscorlib,'
it seems the system runs out of memory, what should i do to prevent that ? when running on azure data fabrick i do use default runtime.
Solved! Go to Solution.
ForEach activity is used to iterate over a collection and executes specified activities in a loop.
You can try breaking the data into smaller batches to reduce memory usage.
ForEach activity - Microsoft Fabric | Microsoft Learn
Check if you can allocate more memory for the pipe in Microsoft Fabric.
Scale your Fabric capacity - Microsoft Fabric | Microsoft Learn
Regards,
Nono Chen
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
ForEach activity is used to iterate over a collection and executes specified activities in a loop.
You can try breaking the data into smaller batches to reduce memory usage.
ForEach activity - Microsoft Fabric | Microsoft Learn
Check if you can allocate more memory for the pipe in Microsoft Fabric.
Scale your Fabric capacity - Microsoft Fabric | Microsoft Learn
Regards,
Nono Chen
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount!
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