Forum Discussion
Dataflow Gen2 error in Fabric
- Anonymous1 year ago
Hi Anonymous,
Thanks for sharing the update. The error you are seeing "Lakehouse036: conflicting metadata change" is happening because multiple Dataflow Gen2 jobs are writing to the same Lakehouse table in parallel. When this happens, each dataflow tries to commit changes to the table metadata, which leads to conflicts, and some of them fail.
To resolve your issue try avoiding parallel writes to the same table. Instead of 5 Dataflows writing into the same final table at the same time, run them sequentially. This will ensure there are no metadata conflicts when committing changes.
Or you can use staging tables. Point each yearly Dataflow to its own staging table in the Lakehouse (e.g., Table_2019, Table_2020, etc.). After that, you can either use a notebook or Pipeline activity to merge these staging tables into your final table, or create a lakehouse shortcut or union query on top of them.
If you prefer keeping the Dataflows, orchestrate them using a Fabric Data Pipeline to run one after another (or write to staging first, then merge).
This approach removes the metadata conflict and will make your loads more stable.
Best Regards,
Hammad.
Hi Anonymous,
Thanks for reaching out to the Microsoft fabric community forum and yes, Fabric Dataflow Gen2 currently has a affective execution time limit of 4 hours per run, even with higher SKUs like F128. Since your job ran for exactly 4:00:43 and then failed, it’s very likely that it hit this hard timeout limit.
Given your scenario (18GB, 120M+ rows, 160+ columns, full load), even without transformations, this volume can push Dataflow Gen2 close to or beyond the timeout window, especially when moving from external sources like Databricks.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Best Regards,
Hammad.