zhongshanhao opened a new pull request, #13343:
URL: https://github.com/apache/lucene/pull/13343
Sometime, due to the need to decode impact and calculate the maximum score,
`ImpactsDISI` typically adds more overhead than it enables skipping.
Let's talk the query:
```
+title:a +title:b +title:c +title:d
```
These term(a, b, c, d) has a large doc frequency.
Maybe the query result set is small, not even a minimum competition score is
produced, `BlockMaxConjunctionBulkScorer` and `BlockMaxConjunctionScorer`
still try to get max score at the beginning of the `advance`.
This PR is designed to solve this problem, to advoid the use of
`ImpactsDISI` when no minimum competitive score has been set.
Here are the benchmark of this PR on wikimediumall.
iter 4:
```
TaskQPS baseline StdDevQPS
my_modified_version StdDev Pct diff p-value
AndHighHigh 13.42 (6.3%) 12.65
(5.5%) -5.7% ( -16% - 6%) 0.131
OrHighHigh 11.19 (12.1%) 10.59
(10.1%) -5.4% ( -24% - 19%) 0.441
HighTermMonthSort 1940.04 (2.8%) 1884.34
(6.9%) -2.9% ( -12% - 7%) 0.390
AndHighMed 72.28 (4.5%) 70.47
(4.2%) -2.5% ( -10% - 6%) 0.358
HighSloppyPhrase 4.89 (4.9%) 4.77
(4.9%) -2.5% ( -11% - 7%) 0.428
BrowseMonthSSDVFacets 3.17 (2.3%) 3.11
(1.7%) -1.8% ( -5% - 2%) 0.145
OrNotHighHigh 151.65 (3.2%) 148.99
(3.2%) -1.8% ( -7% - 4%) 0.385
OrHighNotMed 272.56 (6.0%) 267.90
(4.6%) -1.7% ( -11% - 9%) 0.613
HighTerm 283.60 (5.9%) 278.93
(5.4%) -1.6% ( -12% - 10%) 0.647
MedTermDayTaxoFacets 6.97 (7.4%) 6.85
(6.6%) -1.6% ( -14% - 13%) 0.713
OrHighNotLow 277.16 (4.9%) 272.79
(4.6%) -1.6% ( -10% - 8%) 0.597
OrHighNotHigh 172.23 (4.6%) 169.55
(3.6%) -1.6% ( -9% - 6%) 0.552
HighIntervalsOrdered 2.69 (2.3%) 2.65
(2.2%) -1.5% ( -5% - 3%) 0.299
OrHighMed 73.52 (4.8%) 72.66
(3.4%) -1.2% ( -8% - 7%) 0.657
OrNotHighMed 264.98 (3.3%) 262.00
(4.2%) -1.1% ( -8% - 6%) 0.639
OrHighLow 184.70 (5.4%) 182.84
(5.1%) -1.0% ( -10% - 10%) 0.762
TermDTSort 102.46 (2.4%) 101.69
(3.6%) -0.8% ( -6% - 5%) 0.700
MedSloppyPhrase 3.36 (11.1%) 3.34
(11.0%) -0.5% ( -20% - 24%) 0.946
MedTerm 446.96 (6.0%) 445.14
(5.7%) -0.4% ( -11% - 11%) 0.912
BrowseRandomLabelSSDVFacets 2.13 (4.9%) 2.12
(5.0%) -0.4% ( -9% - 10%) 0.904
Wildcard 72.04 (1.9%) 71.89
(1.8%) -0.2% ( -3% - 3%) 0.859
Respell 33.84 (0.7%) 33.78
(0.9%) -0.2% ( -1% - 1%) 0.730
LowTerm 348.43 (4.9%) 348.30
(3.2%) -0.0% ( -7% - 8%) 0.988
LowSloppyPhrase 13.10 (2.9%) 13.10
(3.4%) 0.0% ( -6% - 6%) 0.999
HighTermTitleBDVSort 4.63 (2.8%) 4.63
(2.0%) 0.0% ( -4% - 5%) 0.986
AndHighMedDayTaxoFacets 32.99 (0.5%) 33.00
(1.3%) 0.0% ( -1% - 1%) 0.942
OrNotHighLow 323.13 (0.7%) 323.29
(1.7%) 0.1% ( -2% - 2%) 0.951
LowSpanNear 43.88 (0.7%) 43.95
(1.4%) 0.2% ( -1% - 2%) 0.823
Prefix3 263.17 (0.6%) 263.60
(1.7%) 0.2% ( -2% - 2%) 0.839
AndHighHighDayTaxoFacets 7.51 (1.4%) 7.53
(1.5%) 0.2% ( -2% - 3%) 0.850
Fuzzy1 56.47 (1.2%) 56.58
(1.1%) 0.2% ( -2% - 2%) 0.802
MedIntervalsOrdered 6.49 (3.0%) 6.52
(3.1%) 0.3% ( -5% - 6%) 0.865
PKLookup 122.42 (2.6%) 123.00
(2.5%) 0.5% ( -4% - 5%) 0.774
LowIntervalsOrdered 17.71 (3.3%) 17.79
(3.3%) 0.5% ( -5% - 7%) 0.820
MedPhrase 73.52 (3.2%) 74.02
(4.4%) 0.7% ( -6% - 8%) 0.781
OrHighMedDayTaxoFacets 3.17 (4.7%) 3.19
(5.8%) 0.7% ( -9% - 11%) 0.836
HighSpanNear 3.00 (0.8%) 3.02
(2.5%) 0.7% ( -2% - 4%) 0.539
HighTermDayOfYearSort 196.79 (1.1%) 198.64
(0.9%) 0.9% ( -1% - 2%) 0.132
AndHighLow 256.98 (3.6%) 259.46
(2.4%) 1.0% ( -4% - 7%) 0.617
HighPhrase 24.61 (4.0%) 24.89
(4.3%) 1.1% ( -6% - 9%) 0.667
MedSpanNear 11.10 (1.5%) 11.23
(3.6%) 1.1% ( -3% - 6%) 0.516
BrowseDateSSDVFacets 0.73 (3.7%) 0.74
(4.6%) 1.1% ( -6% - 9%) 0.665
Fuzzy2 55.52 (1.8%) 56.47
(1.3%) 1.7% ( -1% - 4%) 0.077
HighTermTitleSort 53.70 (2.8%) 54.69
(4.1%) 1.9% ( -4% - 8%) 0.402
LowPhrase 8.64 (5.1%) 8.89
(5.0%) 2.9% ( -6% - 13%) 0.363
BrowseDayOfYearSSDVFacets 2.77 (3.0%) 2.91
(11.6%) 5.0% ( -9% - 20%) 0.346
IntNRQ 39.03 (6.5%) 41.43
(7.8%) 6.2% ( -7% - 21%) 0.175
BrowseRandomLabelTaxoFacets 2.60 (3.0%) 3.09
(34.7%) 18.6% ( -18% - 58%) 0.234
BrowseDateTaxoFacets 3.15 (2.7%) 3.83
(38.6%) 21.6% ( -19% - 64%) 0.211
BrowseDayOfYearTaxoFacets 3.15 (2.7%) 3.85
(38.6%) 22.0% ( -18% - 65%) 0.204
BrowseMonthTaxoFacets 3.24 (1.6%) 4.83
(58.6%) 49.3% ( -10% - 111%) 0.060
```
The result of benchmark does not seem to add some optimization. 🤔
Should I add relevant test cases？
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