Accepted answer
We saw the same issue, fixing the partition filter dropped runtime 60%.
Migrated stacks last quarter and this regression appeared. Stack trace and plan attached:
Context: How many files per partition is too many for Parquet?
Happy to share schema snippets or metrics if useful.
Accepted answer
We saw the same issue, fixing the partition filter dropped runtime 60%.
Tried that, partial improvement but lag still spikes on redeploy.
Check whether AQE is disabled in your Spark conf, skew join handling helped us a lot here.
This matches our runbook for skewed keys.
Plain English: the system prefers to guess a good-enough plan than the perfect plan, because figuring out the perfect plan would take longer than just running the good-enough one.
Note that merge on Delta still needs unique keys defined correctly.
Start with the execution plan, numbers beat guesses.
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No cluster. No install. Just the tab.