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bench: measure list-shaped reads (instances/load_some) - #16
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…ces_sparse) The suite only covered single-entity operations, so the range-paging change in 0.12.0 (#14) was invisible to it. Add three cases: - load_page_50: cold load_some(1, 50) - instances_all: cold instances() with every id present - instances_sparse: cold instances() after deleting every other id Measured on a local replica with the Basilisk 0.15.0 template, v0.11.0 vs v0.12.0 (instructions, db=500 entity pairs): instances_all 700.6M -> 488.3M (-30%) instances_sparse 416.7M -> 246.1M (-41%) load_page_50 66.9M -> 47.4M (-29%) load 1.18M -> 1.04M (-12%) Remaining cost is ~0.95M instructions per hydrated entity (JSON decode + Entity construction), which is the next target. Co-authored-by: Cursor <cursoragent@cursor.com>
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Follow-up to #14 / #15. The benchmark suite only covered single-entity operations, so the range-paging change was invisible to it. Adds
load_page_50,instances_allandinstances_sparse(every other id deleted) totest_benchmark.pyand the orchestrator.Measured locally (same Basilisk 0.15.0 template, ic-python-db v0.11.0 vs v0.12.0), instructions:
instances_allinstances_sparse(50 % deleted)load_page_50loadDeleted ids now cost nothing (sparse ≈ half of dense). The remaining ~0.95 M instructions per hydrated entity are JSON decode +
Entityconstruction, i.e. the next optimisation target.Made with Cursor