read_blob_stream / read_blob_range_stream reassembled a CDC file by fetching
its chunks with `buffered(1)` — strictly sequential, so the next chunk's
backend fetch (a file `open` locally; a full request round-trip on S3/Azure)
only started after the current chunk was fully drained.
A benchmark of the exact pipeline (stream::iter(chunks).map(get).buffered(K)
.try_flatten()) showed a blind `buffered(4)` is the WRONG fix: on a local
disk it is neutral on a warm page cache and ~37% SLOWER cold, because
concurrent opens turn one sequential read into several competing random-I/O
streams over content-addressed (scattered) chunk files. The win is entirely
on remote backends, where per-chunk request latency dominates and overlapping
fetches hide it (≈ linear in K).
So the read-ahead depth is now a backend hint, not a constant:
- BlobStorageBackend::read_prefetch() default 1 (sequential; safe for local).
- S3 / Azure override to 8 (overlap GETs to hide TTFB).
- cached / encrypted / retry / migration delegate to the backend that serves
the bytes.
- Both CDC read paths use `self.backend.read_prefetch().max(1)`.
Net: local backend unchanged (no regression); remote reassembly ~4-8x faster.
Ordered `buffered` (not buffer_unordered) keeps chunks in sequence.
Bench (per-chunk fetch-latency model): buffered(1)->(4)/(8) = x3.9 / x7.8
@1ms, x4.0 / x8.1 @5ms, x4.0 / x8.0 @20ms. Local warm: 230ms@1 vs 227ms@4
(noise); local cold: 425ms@1 vs 585ms@4 (why local stays at 1).
https://claude.ai/code/session_01DCszkkU11LYxMEUWr4setK
Claude
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