Forum Discussion
DataflowsError
Hello all,
Getting the error when running Dataflow , it seems because of data size , how to resolve the error?
Error: PipelineException: The uncompressed data size specified in a packet header exceeds max limit: GatewayDecompressor - Header.UncompressedDataSize (211517212) of a compressed packet exceeds the maximum allowed uncompressed payload of 157286421..Param1 = PipelineException: The uncompressed data size specified in a packet header exceeds max limit: GatewayDecompressor - Header.UncompressedDataSize (211517212) of a compressed packet exceeds the maximum allowed uncompressed payload of 157286421
27 Replies
Hi ArvindJha - These errors are common when there is a data packet being processed in your Power BI Dataflow exceeds the maximum allowed size
Try limiting the number of rows or columns processed in your Dataflow:
Try reducing columns, filtering data, and enabling Incremental Refresh first. If the issue persists, check gateway memory and consider partitioning your data.
option 2: If possible, split large tables into smaller tables and process them separately
ref: link:
Troubleshooting Dataflows in Power BI | Power Query Tutorial Ep8 | Power BI | BI Consulting Pro | 4K
Thanks for the response all of this is already taken care of still the issue persists , for incremental load to happen it has to do full load first time right ? colums are reduced to what is required , it works absoultely fine in QlikSense
Hi ArvindJha,
Thanks for reaching out to the Microsoft fabric community forum.
You're right about Power BI requiring a full load initially when Incremental Refresh is enabled, and it sounds like you've already optimized the dataset thoughtfully.
One thing to consider is how the query steps are structured within the dataflow. If a particular transformation (like a merge, append, or expand) results in a very large in-memory object even briefly it can cause a single packet to exceed the allowed uncompressed size, leading to this error. Unlike QlikSense, Power BI doesn’t stream all data step-by-step during transformation and might materialize intermediate results in memory depending on how the query is built.
If possible, try reviewing the query steps to see if a specific operation may be generating a large intermediate dataset. Breaking that transformation into smaller steps, perhaps by materializing earlier steps into a staging Dataflow or applying filters earlier in the chain can help distribute the load more evenly.
I would also take a moment to thank rajendraongole1, for actively participating in the community forum and for the solutions you’ve been sharing in the community forum. Your contributions make a real difference.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Best Regards,
Hammad.
Community Support TeamIf this post helps then please mark it as a solution, so that other members find it more quickly.
Thank you.
Hi ArvindJha,
Thanks for reaching out to the Microsoft fabric community forum.
It looks like you are facing issue whike running your dataflow and you suggest it might be because of data size. As rajendraongole1 already responded to your query, please go through his response and mark it as solution if it solves your issue.
I would also take a moment to thank rajendraongole1, for actively participating in the community forum and for the solutions you’ve been sharing in the community forum. Your contributions make a real difference.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Best Regards,
Hammad.
Community Support TeamIf this post helps then please mark it as a solution, so that other members find it more quickly.
Thank you.
Hi ArvindJha,
As we haven’t heard back from you, so just following up to our previous message. I'd like to confirm if you've successfully resolved this issue or if you need further help.
If yes, you are welcome to share your workaround and mark it as a solution so that other users can benefit as well. If you find a reply particularly helpful to you, you can also mark it as a solution.
If you still have any questions or need more support, please feel free to let us know. We are more than happy to continue to help you.
Thank you for your patience and look forward to hearing from you.Hi ArvindJha,
I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions. If my response has addressed your query, please accept it as a solution so that other community members can find it easily.
Thank you.
thanks for response , actually for extraction i give say 9 am , the power automate flow runs when extraction is successful but the trigger point for final report is when transformation is complete but both transformation and report starts running parallely even in if else condition
Hi ArvindJha,
What you're running into is a common behavior in Power Automate, actions placed after each other don't automatically wait for the previous ones to complete unless explicitly configured to do so.
Even if you're using if/else conditions, if both branches or steps aren’t nested properly or controlled with "Configure Run After", Power Automate may still attempt to run them in parallel, especially if the actions don’t have a true dependency link.
Best Regards,
Hammad.
Community Support TeamThanks for the response but i dont find a way for dependency , transformation runs when extraction is successful but final dataset starts running in parallel
