Claude
7b26ff014c
Companion benches/*.md (matching the repo convention) capturing the before/after numbers and the honest interpretation behind the read_prefetch 1->2 tuning and the runtime pool sizing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01JG5yYZ9s868mJwqT2Qz7ez
54 lines
2.7 KiB
Markdown
54 lines
2.7 KiB
Markdown
# Blob download read-ahead benchmark
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Measures the local backend's chunk read-ahead depth — the `buffered(N)`
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read-ahead in `DedupService::stream_chunks` fed by
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`BlobStorageBackend::read_prefetch()`. Reproduces the exact production reassembly
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combinator (`stream::iter(hashes).map(get_blob_stream).buffered(N).try_flatten()`)
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over a real `LocalBlobBackend` whose chunk files are scattered across the 256
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hash-prefix dirs, then drains it and reports throughput. `N = 1` is the old
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production default ("antes"); higher N is the change ("después").
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## Reproduce
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```bash
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cargo run --release --features bench --example bench_blob_prefetch
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# tunables: BENCH_FILE_MB=192 BENCH_CHUNK_KB=256 BENCH_PREFETCH=1,2,4,8,16
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# BENCH_THROTTLE_MBPS=0,300,100 BENCH_REPS=5 BENCH_COLD=1
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```
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## Results (4-core box, SSD-class storage, 192 MiB in 768×256 KiB chunks)
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Median MB/s over 5 reps; `vs N=1` is the read-ahead gain over the old default.
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| scenario | N=1 | N=2 | N=4 | N=8 | N=16 |
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|-------------------------|----:|-----:|-----:|-----:|-----:|
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| warm / unthrottled |1306 | **1460** |1394 |1357 |1248 |
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| cold / unthrottled | 456 | **489** | 469 | 478 | 473 |
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| warm / throttled@300MB/s| 167 | 166 | 166 | 166 | 166 |
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| cold / throttled@300MB/s| 138 | 140 | 135 | 135 | 136 |
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| warm / throttled@100MB/s| 62 | 62 | 62 | 62 | 62 |
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| cold / throttled@100MB/s| 57 | 58 | 57 | 57 | 57 |
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(`vs N=1` for the best column N=2: warm/unthrottled **+11.8 %**, cold/unthrottled
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**+7.2 %**; throttled rows ≈ 0 %. N=16 regresses warm −4.4 %.)
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## Conclusions
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1. **N=2 is the sweet spot, not 8.** It wins or ties in 5 of 6 scenarios at the
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lowest fan-out: +11.8 % warm and +7.2 % cold on disk-bound reads, neutral when
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the consumer is the bottleneck. N=8 gives only +3.9 %/+4.8 %; N=16 regresses.
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So local now defaults to 2 (was 1); S3/Azure keep 8 (request-latency bound).
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2. **The win is disk-bound, not network-bound.** Throttled (network-bound) rows
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are flat because `buffered(N)` here overlaps the per-chunk `File::open`
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(cheap on local disk), **not** the data read (which `try_flatten` polls
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sequentially). The disk-bound rows cover localhost/LAN downloads *and* the
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internal blob reads that drain as fast as the disk delivers — thumbnail
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render, transcode, ZIP export, content extraction — all via `stream_chunks`.
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3. **No cold regression on SSD.** The trait doc's "slower cold" worry (concurrent
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opens → random I/O over scattered chunk files) is an HDD seek-thrash concern;
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on SSD-class storage cold reads *improved* at N=2. Operators on spinning disks
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can restore the old behaviour with `OXICLOUD_LOCAL_READ_PREFETCH=1`; NVMe
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arrays can raise it.
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