feat(nimbus): split retention results into fixed weekly metrics

[moibra05]

Because

• The existing retention metric only represented Week 2 preventing users from viewing retention for other weeks

This commit

• Splits retention into fixed weekly metrics, gives each metric the correct displayed window, and hides unrelated breakdowns

Fixes #16421

[jaredlockhart]

Okay one small labeling change but otherwise I think looks good thanks @moibra05 🙏 🎉

[mikewilli]

Left a few comments, but looks close. Do we need to do a data migration here as well or is this backwards compatible?

[RJAK11]

@mikewilli I don't have the full context so let me know if I misunderstood anything but I just made the changes you mentioned.
Since we rename the key, I think existing results data won’t find the old value anymore. So current experiments would not have the data for Week 2 and completed experiments wouldn’t automatically recover since they don’t re-fetch.
The migration I added fixes that by clearing analysis_start_time once so the normal results task re-fetches from Jetstream and after that the real timestamp gets written back so it only happens once but it seems like a huge task. The other option I could think of would be to rewrite the stored keys directly which avoids the re-fetch, but it edits the existing data in place and seems a bit risky. What do you think?

[mikewilli]

Thanks for picking this up! Changes look good, left one small question about a possible tiny refactor.

As for the migration, I think the approach you chose is probably our best option. The results fetches are quick (couple seconds at most), so a one-time re-fetch of everything shouldn't be a big deal. We're also fetching everything automatically anyway, so there's no concern about accidentally overwriting results. I'd be interested in @jaredlockhart 's input in case he has a different opinion, but in lieu of that I'd say go ahead with your chosen approach.

[mikewilli]

Would it make more sense to put this under if data and window == AnalysisWindow.WEEKLY?