Hey, so when we use anomaly checks which compares DataFrame metrics to previous DataFrame.
Lets say we have batch jobs with pydeequ checks, and one of the checks failed from anomaly check. I go back repair it, but then when i rerun batch job again, it would compare it to failed metric and fail again.
How can i avoid this, or is there option to compare only to baseline DataFrame?
to sum it up:
I have monthly jobs with anomaly checks with lets say relative changes of +-20%, if it fails, job fails, i repair, but then it would compare new run to failed metric and it would fail again.
Hey, so when we use anomaly checks which compares DataFrame metrics to previous DataFrame. Lets say we have batch jobs with pydeequ checks, and one of the checks failed from anomaly check. I go back repair it, but then when i rerun batch job again, it would compare it to failed metric and fail again.
How can i avoid this, or is there option to compare only to baseline DataFrame?
to sum it up:
I have monthly jobs with anomaly checks with lets say relative changes of +-20%, if it fails, job fails, i repair, but then it would compare new run to failed metric and it would fail again.