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reweight the combined metric for lukewarm and inapplicable metrics
The Combined score is a weighted geomean of load (10%), data size (10%),
cold (20%) and hot (60%) ratios. That unfairly penalizes systems for
metrics that don't apply to them, and lets lukewarm "cold" numbers
(really warm queries) distort the cold component.
Unify the per-metric exclusion rules in a single metricExcludes()
helper (stateless from load, in-memory from cold/combined/load, lukewarm
from cold, missing data size from size) and reuse it everywhere:
- Cold Run metric: lukewarm systems are excluded from the ranking by
default.
- Combined per-query baseline: the cold-run minimum excludes lukewarm /
in-memory systems, so their warm "cold" numbers can't depress the
baseline and inflate every true-cold system's cold ratio. min load
time / min data size likewise exclude systems that don't qualify.
- Combined score: a metric that doesn't apply to a system is dropped and
the remaining weights are renormalized, instead of feeding a bogus
ratio. Lukewarm systems keep a cold component of 0 with its weight
folded into hot (load 10% / size 10% / hot 80%); a stateless engine
that still reports a load time (e.g. Polars (Parquet)) drops the load
component; etc. The cold term is guarded so an all-lukewarm selection
(empty cold baseline) can't poison the score with NaN.
The Combined view still shows only the single overall score; the
per-component breakdown is added in a follow-up commit.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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