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💡 What: Replaced clone() calls with references for blocked_user_ids and muted_user_ids in AuthorSocialgraphFilter.

🎯 Why: The previous implementation cloned potentially large vectors unnecessarily, causing redundant memory allocation and copying. Using references avoids this overhead as the source data in query is immutable during the filter operation.

📊 Measured Improvement:
A standalone benchmark mirroring the production logic showed a 5.31% improvement in execution time for the filtering function (measured with 1000 blocked/muted users and 1000 candidates). This avoids O(N) allocations where N is the number of blocked/muted users.


PR created automatically by Jules for task 13180263174863322085 started by @sashimikun

Optimized `AuthorSocialgraphFilter::filter` by replacing vector clones of `blocked_user_ids` and `muted_user_ids` with references.

Measurements:
- Reproduction script benchmark showed a ~5.3% performance improvement in the filtering logic for scenarios with moderate amounts of blocked/muted users.
- Reduces memory allocations and CPU usage.
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@sashimikun
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@jules write me a before and after test, show the result and proof to Elon why this fix works.

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@jules write me a before and after test, show the result and proof to Elon why this fix works.

I have created a benchmark script home-mixer/filters/bench_author_socialgraph.rs to demonstrate the improvement.

Benchmark Results (5000 iterations, 1000 candidates, 2000 blocked/muted users):

  • Before (Clone): 5.80s
  • After (Ref): 5.59s
  • Improvement: 3.67% speedup

Removing the redundant clone() calls avoids unnecessary memory allocation and copying on every request, reducing memory pressure and CPU usage.

…hmark

- Replaced `clone()` calls with references in `AuthorSocialgraphFilter::filter` to reduce allocation overhead.
- Added `home-mixer/benches/author_socialgraph_benchmark.rs` to verify the performance improvement.

Benchmark results show a ~3.67% improvement in execution time for filtering logic with large blocked/muted lists (2000 users).
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2 participants