After the previous changeset, some numbers stood out:
- HighlightsRanking.extractFeatures: 44.9%
- HighlightCandidate.getFeatureValue: 19.4%
- Collections.secondaryHash: 17.3%
- HashMap.get: 11.7%
My hypothesis was that our HighlightCandidate.features implementation was slow:
it was mapping FeatureNames -> values in a HashMap but HashMap look-ups are
slower than a direct memory access.
I replaced the implementation with a direct access from an array - about as
fast as we can get. This encouraged me to make some changes with the following
benefits:
- Rewrote HighlightsRanking.normalize to save iterations and allocations.
- Rm code from HighlightsRanking.scoreEntries: we no longer need to iterate to
construct the filtered items, we just index directly into the list
- Rewrote HighlightsRanking.decay(), which I think is a little clearer now.
- Saved a few iterator/object allocations inside inner loops in places.
The tests pass and we have coverage for the normalize changes but not for
scoreEntries.
---
For perf, my changes affected multiple methods so the percentages are no longer
reliable but I can verify absolute runtime changes. I ran three tests, the best
of which showed an overall 33% runtime compared to the previous changeset and
the other two profiles showed a 66% overall runtime. In particular, for the
middle run, the changes for affected methods go from X microseconds to Y
microseconds:
- Features.get: 3,554,796 -> 322,145
- secondaryHash: 3,165,785 -> 35,253
- HighlightsRanking.normalize: 6,578,481 -> 1,734,078
- HighlightsRanking.scoreEntries: 3,017,272 -> 448,300
As far as I know, my changes should not have introduced any new inefficiencies
to the code.
MozReview-Commit-ID: 9THXe8KqBbB
--HG--
extra : rebase_source : 2358fe83acebaf04a61d912e88f8cf420b7df3d7
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