## 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
We still need to rerun some builds manually because flaky tests weren't
detected automatically.
I found two reasons for it:
- If a test is flaky on a particular build type, on a particular
Postgres version, there's a high chance that this test is flaky on all
configurations, but we don't automatically detect such cases.
- We detect flaky tests only on the main branch, which requires manual
retrigger runs for freshly made flaky tests.
Both of them are fixed in the PR.
## Summary of changes
- Spread flakiness of a single test to all configurations
- Detect flaky tests in all branches (not only in the main)
- Look back only at 7 days of test history (instead of 10)
- Increase `connect_timeout` to 30s, which should be enough for
most of the cases
- If the script cannot connect to the DB (or any other
`psycopg2.OperationalError` occur) — do not fail the script, log
the error and proceed. Problems with fetching flaky tests shouldn't
block the PR
This PR adds a plugin that automatically reruns (up to 3 times) flaky
tests. Internally, it uses data from `TEST_RESULT_CONNSTR` database and
`pytest-rerunfailures` plugin.
As the first approximation we consider the test flaky if it has failed on
the main branch in the last 10 days.
Flaky tests are fetched by `scripts/flaky_tests.py` script (it's
possible to use it in a standalone mode to learn which tests are flaky),
stored to a JSON file, and then the file is passed to the pytest plugin.
