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Preserve contiguous index ranges in BitPacked take - #10520

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joseph-isaacs merged 7 commits into
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db/sparse-vector-selection
Oct 16, 2026
Merged

joseph-isaacs merged 7 commits into
developfrom
db/sparse-vector-selection

Merge develop for BitPacked benchmark baseline

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CodSpeed / CodSpeed Performance Analysis failed Oct 16, 2026

2 benchmarks regressed

⚠️ Unknown Walltime execution environment detected

Using the Walltime instrument on standard Hosted Runners will lead to inconsistent data.

For the most accurate results, we recommend using CodSpeed Macro Runners: bare-metal machines fine-tuned for performance measurement consistency.

⚠️ 2 benchmarks measured no execution time

Nothing ran under measurement, usually because the compiler removed the code under test. These results are not comparable, so they count as unchanged.

Preventing compiler optimizations

⚠️ 18 benchmarks spent significant time in system calls

System calls cannot be consistently instrumented, so they are not included in the measure, which understates the real cost. Please switch to the Walltime instrument to accurately measure system calls.

Measurement and system calls

ℹ️ 40 benchmarks have no flame graph

The flamegraph could not be generated because we failed to resolve the symbols in the profiling trace. This happens when we fail to harvest information about language frames.

⚠️ Different runtime environments detected

Some benchmarks with significant performance changes were compared across different runtime environments,
which may affect the accuracy of the results.

Open the report in CodSpeed to investigate

⚡ 50 improved benchmarks
❌ 2 regressed benchmarks
✅ 2335 untouched benchmarks
⏩ 12 skipped benchmarks1

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

Mode Benchmark BASE HEAD Efficiency
❌ WallTime filter_neon[8] 876 ns 1,469 ns -40.37%
❌ WallTime threshold_neon[8] 1.4 µs 1.5 µs -10.62%
⚡ Simulation embedding_code_runs[4096] 1,940.1 µs 160 µs ×12
⚡ Simulation embedding_code_runs[2048] 997.1 µs 108.2 µs ×9.2
⚡ Simulation embedding_code_runs[1024] 534.9 µs 82.7 µs ×6.5
⚡ Simulation embedding_code_runs[512] 306 µs 74.1 µs ×4.1
⚡ Simulation isolated_runs[u8, (512, 0)] 304.7 µs 74.2 µs ×4.1
⚡ Simulation embedding_runs[1536] 890.8 µs 236 µs ×3.8
⚡ Simulation embedding_runs[1024] 605.3 µs 168.2 µs ×3.6
⚡ Simulation fragmented_runs[1024] 605.2 µs 168.6 µs ×3.6
⚡ Simulation isolated_runs[u16, (512, 0)] 322.1 µs 95 µs ×3.4
⚡ Simulation embedding_runs[768] 498.2 µs 170.3 µs ×2.9
⚡ Simulation isolated_runs[u8, (256, 0)] 190.5 µs 70.7 µs ×2.7
⚡ Simulation isolated_runs[u8, (256, 1020)] 193.9 µs 73.3 µs ×2.6
⚡ Simulation isolated_runs[u32, (512, 0)] 353.5 µs 135.8 µs ×2.6
⚡ Simulation fragmented_runs[512] 354 µs 136.5 µs ×2.6
⚡ Simulation isolated_runs[u8, (256, 896)] 199.5 µs 80.5 µs ×2.5
⚡ Simulation isolated_runs[u16, (256, 0)] 204 µs 86.2 µs ×2.4
⚡ Simulation isolated_runs[u16, (256, 1020)] 207.6 µs 90.2 µs ×2.3
⚡ Simulation isolated_runs[u8, (161, 0)] 145.3 µs 69.1 µs ×2.1
... ... ... ... ... ...

ℹ️ Only the first 20 benchmarks are displayed. Go to the app to view all benchmarks.

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.


Comparing db/sparse-vector-selection (826b627) with develop (e8167ae)

Open in CodSpeed

Footnotes

  1. 12 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩