This matches our runbook for skewed keys.
Migrated stacks last quarter and this regression appeared. Stack trace and plan attached:
Context: SQL window function question, top 3 orders per customer
Happy to share schema snippets or metrics if useful.
This matches our runbook for skewed keys.
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.
Idempotent writes with merge keys saved us during backfills.
We saw the same issue, fixing the partition filter dropped runtime 60%.
Idempotent writes with merge keys saved us during backfills.
Careful with NULL in join keys, they'll drop rows in an inner join.
We saw the same issue, fixing the partition filter dropped runtime 60%.
Prefer a staging table plus validation gate before promoting to prod tables.
How do you handle backfill without duplicating rows?
How do you handle backfill without duplicating rows?
ELI5: think of it like a phone book. If it's sorted by last name and you search by last name, that's fast. Search by first name instead and you're flipping through every page.
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No cluster. No install. Just the tab.