0
Accepted answer
Start with the execution plan, numbers beat guesses.
Hitting a wall in prod and looking for patterns others have used. Minimal repro below but happy to share more context.
Context: Synapse dedicated vs serverless for ad-hoc analytics
Happy to share schema snippets or metrics if useful.
Accepted answer
Start with the execution plan, numbers beat guesses.
Start with the execution plan, numbers beat guesses.
Idempotent writes with merge keys saved us during backfills.
Agree on the staging table swap. Atomic promote prevented partial reads.
Small nit: the broadcast hint gets ignored once the table is over threshold, check the UI to confirm.
Worth measuring the serialized size before choosing broadcast.
+1, saw identical behaviour after upgrading Spark 3.4 to 3.5.
Sign in to reply.
© 2026 Lakebench, operated by Hunnurji Rao. Bengaluru, Karnataka, India.
No cluster. No install. Just the tab.