Tony-X commented on PR #12688:
URL: https://github.com/apache/lucene/pull/12688#issuecomment-1825228925
After some tweaking and tinkering I was finally able to get the bench
running the way I wanted in luceneutil! @mikemccand
Unfortunately luceneutil out of the box doesn't work for my case...
```
TaskQPS baseline StdDevQPS
my_modified_version StdDev Pct diff p-value
[19/1802]
Wildcard 56.20 (2.0%) 7.30
(0.2%) -87.0% ( -87% - -86%) 0.000
Respell 44.00 (1.7%) 14.46
(0.6%) -67.1% ( -68% - -65%) 0.000
Fuzzy1 54.11 (1.2%) 20.86
(0.8%) -61.4% ( -62% - -60%) 0.000
Prefix3 103.61 (0.8%) 41.37
(0.5%) -60.1% ( -60% - -59%) 0.000
Fuzzy2 42.43 (1.2%) 20.26
(0.9%) -52.3% ( -53% - -50%) 0.000
HighTermTitleSort 127.60 (1.7%) 114.65
(1.6%) -10.1% ( -13% - -6%) 0.000
HighTermMonthSort 2549.22 (2.8%) 2435.74
(3.8%) -4.5% ( -10% - 2%) 0.037
AndHighLow 708.99 (2.3%) 678.15
(2.1%) -4.4% ( -8% - 0%) 0.001
LowTerm 369.16 (5.5%) 358.15
(3.1%) -3.0% ( -10% - 5%) 0.287
OrNotHighLow 258.51 (1.8%) 252.11
(2.2%) -2.5% ( -6% - 1%) 0.054
OrHighLow 348.58 (1.1%) 340.11
(2.5%) -2.4% ( -5% - 1%) 0.046
OrNotHighHigh 141.31 (6.7%) 138.54
(3.2%) -2.0% ( -11% - 8%) 0.554
IntNRQ 17.93 (1.8%) 17.62
(3.7%) -1.7% ( -7% - 3%) 0.349
MedSloppyPhrase 26.73 (0.8%) 26.28
(1.3%) -1.7% ( -3% - 0%) 0.017
HighIntervalsOrdered 3.88 (2.6%) 3.82
(2.3%) -1.6% ( -6% - 3%) 0.314
HighTerm 290.77 (7.3%) 286.20
(6.9%) -1.6% ( -14% - 13%) 0.727
OrHighNotHigh 296.51 (6.9%) 291.90
(4.9%) -1.6% ( -12% - 11%) 0.682
LowIntervalsOrdered 15.48 (1.1%) 15.26
(1.3%) -1.4% ( -3% - 0%) 0.057
MedTerm 405.54 (6.3%) 399.77
(5.9%) -1.4% ( -12% - 11%) 0.713
LowSloppyPhrase 44.64 (0.5%) 44.04
(2.1%) -1.3% ( -3% - 1%) 0.171
HighTermDayOfYearSort 177.36 (1.6%) 175.08
(1.8%) -1.3% ( -4% - 2%) 0.234
OrHighMed 79.44 (3.7%) 78.48
(3.0%) -1.2% ( -7% - 5%) 0.572
OrNotHighMed 268.82 (4.3%) 265.74
(3.1%) -1.1% ( -8% - 6%) 0.632
BrowseMonthTaxoFacets 3.89 (0.4%) 3.85
(1.2%) -0.9% ( -2% - 0%) 0.134
AndHighMedDayTaxoFacets 44.33 (0.7%) 43.96
(1.1%) -0.8% ( -2% - 0%) 0.145
MedSpanNear 30.67 (1.1%) 30.42
(2.3%) -0.8% ( -4% - 2%) 0.481
LowSpanNear 4.56 (0.8%) 4.53
(2.1%) -0.6% ( -3% - 2%) 0.576
HighSpanNear 8.52 (1.4%) 8.47
(2.1%) -0.5% ( -3% - 2%) 0.636
OrHighNotLow 236.32 (6.6%) 235.28
(4.4%) -0.4% ( -10% - 11%) 0.901
AndHighHighDayTaxoFacets 4.31 (0.6%) 4.29
(0.8%) -0.4% ( -1% - 1%) 0.446
LowPhrase 69.90 (1.2%) 69.67
(2.7%) -0.3% ( -4% - 3%) 0.807
AndHighMed 41.87 (0.6%) 41.75
(2.7%) -0.3% ( -3% - 3%) 0.828
OrHighHigh 45.86 (7.4%) 45.77
(7.9%) -0.2% ( -14% - 16%) 0.969
TermDTSort 101.90 (2.3%) 101.84
(2.0%) -0.1% ( -4% - 4%) 0.966
HighSloppyPhrase 0.48 (2.2%) 0.48
(2.6%) -0.0% ( -4% - 4%) 0.995
BrowseDateSSDVFacets 1.00 (3.7%) 1.00
(5.3%) -0.0% ( -8% - 9%) 1.000
HighTermTitleBDVSort 4.48 (5.4%) 4.49
(4.4%) 0.0% ( -9% - 10%) 0.990
BrowseDayOfYearSSDVFacets 3.51 (13.4%) 3.52
(13.3%) 0.1% ( -23% - 30%) 0.990
BrowseMonthSSDVFacets 3.38 (0.7%) 3.39
(0.6%) 0.1% ( -1% - 1%) 0.740
BrowseDayOfYearTaxoFacets 3.85 (0.3%) 3.85
(0.5%) 0.2% ( 0% - 0%) 0.469
MedIntervalsOrdered 1.65 (1.5%) 1.65
(1.5%) 0.2% ( -2% - 3%) 0.802
BrowseDateTaxoFacets 3.82 (0.3%) 3.83
(0.4%) 0.3% ( 0% - 0%) 0.264
BrowseRandomLabelSSDVFacets 2.34 (1.0%) 2.35
(0.5%) 0.3% ( -1% - 1%) 0.494
OrHighNotMed 296.34 (7.6%) 297.38
(4.6%) 0.4% ( -11% - 13%) 0.930
BrowseRandomLabelTaxoFacets 3.29 (0.6%) 3.31
(0.7%) 0.5% ( 0% - 1%) 0.275
MedPhrase 9.84 (2.1%) 9.90
(4.1%) 0.6% ( -5% - 6%) 0.787
AndHighHigh 33.50 (1.2%) 33.73
(3.4%) 0.7% ( -3% - 5%) 0.669
HighPhrase 15.15 (2.3%) 15.28
(4.1%) 0.9% ( -5% - 7%) 0.679
MedTermDayTaxoFacets 13.36 (1.8%) 13.55
(2.0%) 1.4% ( -2% - 5%) 0.240
OrHighMedDayTaxoFacets 3.73 (1.4%) 3.83
(2.2%) 2.6% ( 0% - 6%) 0.026
PKLookup 147.84 (1.6%) 157.37
(1.5%) 6.4% ( 3% - 9%) 0.000
```
### Observations:
#### PKLookup has improvement
This is reasonable as the terms index (FST) holds all the terms.
#### Fuzzy/Wildcard/Prefix queries got *much slower*
This is also expected because currently I used the default implementation
provided by `TermsEnum` which does not take advantage of the FST. With an
optimized implementation I expect it to at least be on-par and slightly better
because the FST holds information about all terms, whereas the current
BlockTreeTerms only holds prefixes.
#### `HighTermTitleSort` and `HighTermMonthSort` got about 4.5% ~ 10% less
throughput
I don't quite understand why term lookup could
#### `AndHighLow` got slower
Am i missing some optimization opportunity for low freq terms?
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