perf(btreemap): batch the per-field node reads and writes - #441
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Loading a node performed one memory read per field: every child address, key size, key, and value size separately — dozens of reads per node. A memory access costs a fixed amount per call plus a fee per byte, so the load now fetches the front of the initial page in one read and parses the fields out of the buffer, with any field beyond the read falling back to an individual read as before. The read is sized so that it only ever buys bytes the load will use. For key types bounded by at most 64 bytes the header pins down the extent of the children and key areas, and that estimate is all that is fetched. For larger or unbounded key bounds the interleaved layout offers no extent worth prefetching — the sizes the walk needs sit between payloads it skips — so those types read exactly as before; an earlier draft that read a fixed 1 KiB for them regressed the large-value benchmarks by up to 8%. Saving mirrors this: fields are serialized into a buffer flushed in as few writes as possible, except that slices of 48 bytes or more are written directly, uncopied, flushing whatever is buffered around them. The threshold is measured, and lower than intuition suggests: copying into the buffer costs a few instructions per byte while a separate write costs a fixed amount for the call and its page mapping, which puts the crossover around forty bytes — earlier drafts with a 128- and 512-byte threshold both measured thousands of instructions per save slower on nodes with ~128-byte keys and values. The `NodeWriter` keeps sole ownership of the overflow-address field at bytes [7, 15): it updates the chain pointer in place as overflow pages are allocated and released, so the save skips over it rather than risk clobbering a pointer the writer just installed. The writer's unused field helpers are gone. Full canbench sweep: 147 improved / 0 regressed / 105 unchanged of 252, median -3.9%, best -23.5%; the largest positive movement is +1.8% on a benchmark whose code path is untouched (noise). Memory-manager maps gain the most (-16 to -23%), followed by maps with small keys and values (-10 to -19%). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Loading a node performed one memory read per field — every child address, key size, key, and value size separately — dozens of reads per node, and saving mirrored that with one write per field. A memory access costs a fixed amount per call plus a fee per byte, so this PR batches both directions while keeping every path that can't be batched profitably on its existing per-field behavior.
Load
The load now fetches the front of the initial page in one read and parses the fields out of the buffer, with any field beyond the read falling back to an individual read. The read is sized so that it only ever buys bytes the load will use:
The previous
CHILDREN_BATCH_READ_THRESHOLD = 4heuristic ("individual reads are faster for ≤ 4 children") is gone: re-measured under the new read pattern, it no longer paid for itself — the sweep below shows no regression on any internal-node-heavy benchmark.Save
Fields are serialized into a buffer flushed in as few writes as possible, except that slices of ≥ 48 bytes are written directly, uncopied, flushing whatever is buffered around them. The threshold is measured, and lower than intuition suggests: copying into the buffer costs a few instructions per byte, while a separate write costs a fixed amount for the call and its page mapping, putting the crossover around forty bytes. (Drafts with 128- and 512-byte thresholds both measured thousands of instructions per save slower on nodes with ~128-byte keys and values.)
The save no longer writes the overflow-address field at bytes [7, 15): the
NodeWriterowns it, updating the chain pointer in place as overflow pages are allocated and released, andfinish()writes theNULLterminator into it whenever the node ends up with no overflow pages — so even a fresh node at a reused address cannot retain a stale pointer. (The old explicit write was redundant with that terminator.)A new test covers the one newly reachable trap: a node placed so close to the end of memory that the batched-read estimate extends past the last byte ever written; the read clamps rather than traps.
Benchmarks
Full
canbenchsweep againstmain(canbench 0.2.0, all 252 benchmarks):Zero regressions. The single largest positive movement (+1.84%,
remove_vec_64_128) is on a code path this PR does not touch (unbounded keys take the unchanged per-field route) and is within canbench's noise threshold.Top improvements:
mem_manager_remove_u64_u64mem_manager_insert_u64_u64mem_manager_get_u64_u64get_blob8_u64get_zipf_100k_u64_u64_nocacheinsert_blob8_u64remove_blob8_u64mem_manager_get_u64_blob512pop_last_blob_32_0scan_iter_rev_1k_0bcontains_blob_8_128get_blob_4_128remove_100k_u64_u64_nocacheMemory-manager maps gain the most (−16 to −23%), followed by maps with small keys and values (−10 to −19%); sparse-node scans and range queries land around −14 to −16%. One footnote:
insert_vec_8_128shows a one-time +1 page (64 KiB) heap high-water increase from the save buffer — a peak-allocation effect, not a per-operation cost.🤖 Generated with Claude Code