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Solved! Go to Solution.
Hi @sunamitasantos ,
Thank you for reaching out to Microsoft Community.
The error [BigQuery] (310) Storage API Error: Stream removed typically occurs when the BigQuery read stream times out during a semantic model refresh. This usually happens when the query runs for too long or when transformations in Power Query prevent proper query folding, causing a full table scan.
To help prevent this issue:
Ensure query folding is enabled so that filters and transformations are pushed down to BigQuery instead of being processed in Power Query.
Filter data at the source to avoid scanning the entire table during refresh.
Minimize heavy transformations in Power Query by moving them to BigQuery (for example, using views or SQL logic).
Reduce refresh parallelism to avoid opening too many read streams simultaneously.
Retrieve only the required columns rather than using SELECT *, which helps reduce the volume of data streamed.
Applying these adjustments can shorten the data read duration and prevent the Storage API stream from expiring, allowing the refresh to complete successfully.
Hope this helps.
Thank you.
Hi @sunamitasantos ,
May I ask if you have resolved this issue? Please let us know if you have any further issues, we are happy to help.
Thank you.
Hi @sunamitasantos ,
We’d like to follow up regarding the recent concern. Kindly confirm whether the issue has been resolved, or if further assistance is still required. We are available to support you and are committed to helping you reach a resolution.
Thank you.
Hi @sunamitasantos ,
Thank you for reaching out to Microsoft Community.
The error [BigQuery] (310) Storage API Error: Stream removed typically occurs when the BigQuery read stream times out during a semantic model refresh. This usually happens when the query runs for too long or when transformations in Power Query prevent proper query folding, causing a full table scan.
To help prevent this issue:
Ensure query folding is enabled so that filters and transformations are pushed down to BigQuery instead of being processed in Power Query.
Filter data at the source to avoid scanning the entire table during refresh.
Minimize heavy transformations in Power Query by moving them to BigQuery (for example, using views or SQL logic).
Reduce refresh parallelism to avoid opening too many read streams simultaneously.
Retrieve only the required columns rather than using SELECT *, which helps reduce the volume of data streamed.
Applying these adjustments can shorten the data read duration and prevent the Storage API stream from expiring, allowing the refresh to complete successfully.
Hope this helps.
Thank you.
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