## Problem
We've got several issues with the current `benchmarks` job setup:
- `benchmark_durations.json` file (that we generate in runtime to
split tests into several jobs[0]) is not consistent between these
jobs (and very not consistent with the file if we rerun the job). I.e.
test selection for each job can be different, which could end up in
missed tests in a test run.
- `scripts/benchmark_durations` doesn't fetch all tests from the
database (it doesn't expect any extra directories inside
`test_runner/performance`)
- For some reason, currently split into 4 groups ends up with the 4th
group has no tests to run, which fails the job[1]
- [0] https://github.com/neondatabase/neon/pull/4683
- [1] https://github.com/neondatabase/neon/issues/6629
## Summary of changes
- Generate `benchmark_durations.json` file once before we start
`benchmarks` jobs (this makes it consistent across the jobs) and pass
the file content through the GitHub Actions input (this makes it
consistent for reruns)
- `scripts/benchmark_durations` fix SQL query for getting all required
tests
- Split benchmarks into 5 jobs instead of 4 jobs.
## Problem
We started to store test results in a new format in
https://github.com/neondatabase/neon/pull/4549.
This PR switches scripts to query this db.
(we can completely remove old DB/ingestions scripts in a couple of
weeks after the PR merged)
## Summary of changes
- `scripts/benchmark_durations.py` query new database
- `scripts/flaky_tests.py` query new database
## Problem
Benchmarks run takes about an hour on main branch (in a single job),
which delays pipeline results. And it takes another hour if we want to
restart the job due to some failures.
## Summary of changes
- Use `pytest-split` plugin to run benchmarks on separate CI runners in
4 parallel jobs
- Add `scripts/benchmark_durations.py` for getting benchmark durations
from the database to help `pytest-split` schedule tests more evenly. It
uses p99 for the last 10 days' results (durations).
The current distribution could be better; each worker's durations vary
from 9m to 35m, but this could be improved in consequent PRs.
