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Add facilitator and workshop rollups #29518
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499a06d
Add facilitator and workshop rollups
hacodeorg 15eed06
Typo fixes
hacodeorg 3530f39
Fix unit test
hacodeorg 7310e34
Merge branch 'staging' into ha/sp-rollup-3
hacodeorg 8ac0420
Merge branch 'staging' into ha/sp-rollup-3
hacodeorg e6cf00f
Stop using raw SQL. Fix variable names
hacodeorg f28cd01
Fix naming conflict between module Pd::SurveyPipeline::Helper and mod…
hacodeorg 01a54cf
Merge branch 'staging' into ha/sp-rollup-3
hacodeorg 0cc77cc
Merge branch 'staging' into ha/sp-rollup-3
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Not blocking on this PR, but I'm interested in a discussion about how specific we can usefully get with this (and similar)
rescue
blocks. I know we want to be resilient against failures, but I wonder if we can define useful boundaries of that resilience that will help us notice very unexpected scenarios faster.Related: Rescue StandardError, Not Exception - ThoughtBot (especially the "Best-case Scenario" example)
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My train of thought when dealing with errors (StandardError) is
a) Interrupt the current code flow, throw error up 1 layer and let the upper layer deal with it.
b) Swallow the error and continue with the current code flow.
c) Swallow the error but report it via Honeybadger (externally) or record it and bubble the info up to upper layers.
In this particular case, the rescued block executes one reducer function on one group of data, which is a part of applying multiple reducers to multiple groups. I chose option (c) here, swallow all errors, record and bubble them up. This is best-effort approach, getting usable results but still notify higher layers about caught errors.