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branch-4.0: [codex] fix ANN OpenMP build budget and add concurrency test #61313#62838

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branch-4.0: [codex] fix ANN OpenMP build budget and add concurrency test #61313#62838
zhiqiang-hhhh wants to merge 1 commit intoapache:branch-4.0from
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@zhiqiang-hhhh
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cherry pick from #61313

…61313)

This PR fixes ANN index build OpenMP thread budgeting and adds a BE unit
test for the concurrency cap.
`ScopedOmpThreadBudget` computed available budget from
`config::omp_threads_limit` directly. With the default
`omp_threads_limit = -1`, each builder effectively reserved 1 thread and
did not follow the documented auto behavior (80% of CPU cores). In
addition, concurrent builders could overrun the intended global limit
because there was no wait/coordination when the budget was exhausted.
In `faiss_ann_index.cpp`:
- The constructor used `config::omp_threads_limit` directly instead of
the auto-resolved limit from `get_omp_threads_limit()`.
- No blocking mechanism existed when all OpenMP budget was already in
use.
- Use `get_omp_threads_limit()` as the actual global limit for
budgeting.
- Add a condition variable to block builders until at least one OpenMP
slot is available.
- Keep the existing policy of reserving up to half of remaining budget
(minimum 1).
- Add concise comments to explain wait/wakeup behavior.
- Added `VectorSearchTest.OmpThreadBudgetNeverExceedsLimit` in
`be/test/storage/index/ann/faiss_vector_index_test.cpp`.
- The test sets `config::omp_threads_limit = 1`, runs multiple
concurrent ANN `add()` builds, samples `ann_index_build_index_threads`,
and asserts peak usage never exceeds 1 and finally returns to 0.
- Local compilation/test run was intentionally skipped per request.
@zhiqiang-hhhh
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run buildall

@Thearas
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Thearas commented Apr 25, 2026

Thank you for your contribution to Apache Doris.
Don't know what should be done next? See How to process your PR.

Please clearly describe your PR:

  1. What problem was fixed (it's best to include specific error reporting information). How it was fixed.
  2. Which behaviors were modified. What was the previous behavior, what is it now, why was it modified, and what possible impacts might there be.
  3. What features were added. Why was this function added?
  4. Which code was refactored and why was this part of the code refactored?
  5. Which functions were optimized and what is the difference before and after the optimization?

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