Add mergeable streaming latency percentile digest#281
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stats.percentile needs the full sorted list in memory; for long-running or sharded load/soak runs add a HdrHistogram-style LatencyDigest with O(1) record, bounded memory (significant-figure buckets) and merge for cross-shard aggregation, plus exact_percentiles for small sets. Wired through the facade, AC_percentiles executor command, MCP tool and the Script Builder.
Up to standards ✅🟢 Issues
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| Metric | Results |
|---|---|
| Complexity | 47 |
| Duplication | 0 |
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Summary
stats.percentileis exact but needs the full sorted sample list in memory; for a long-running or sharded load/soak run you want an O(1)-per-record, bounded-memory, mergeable structure. This adds it.LatencyDigest(sig_figs=3)—record(O(1), buckets to significant figures),percentile/quantiles/summary, andmergefor cross-shard aggregation (correct aggregate p99 from per-worker results).exact_percentiles(samples, qs)— exact percentiles for the small-set case (delegates tostats.percentile).Pure stdlib (
math).Five-layer wiring
je_auto_control/utils/percentiles/__init__.py+__all__AC_percentiles(arbitrary quantiles, complementsAC_describe_stats' fixed set)ac_percentilesTests & docs
test/unit_test/headless/test_percentiles_batch.py(9 tests: exact, digest accuracy, summary, merge, empty, quantiles)Lint clean: ruff / pylint (same-class merge protected-access justified) / bandit / radon.