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Accepted answer
Check whether AQE is disabled in your Spark conf, skew join handling helped us a lot here.
Interview follow-up got me thinking, how do you actually implement this in production?
Context: Dataflow streaming with BigQuery sink, duplicate rows on retry
Happy to share schema snippets or metrics if useful.
Accepted answer
Check whether AQE is disabled in your Spark conf, skew join handling helped us a lot here.
Prefer a staging table plus validation gate before promoting to prod tables.
Start with the execution plan, numbers beat guesses.
Tried that, partial improvement but lag still spikes on redeploy.
Prefer a staging table plus validation gate before promoting to prod tables.
Prefer a staging table plus validation gate before promoting to prod tables.
Simple way to think about it: caching is a bet that you'll ask the same question again soon. If you don't, you're just paying rent on memory for nothing.
Prefer a staging table plus validation gate before promoting to prod tables.
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No cluster. No install. Just the tab.