prudhvigodithi commented on PR #15446:
URL: https://github.com/apache/lucene/pull/15446#issuecomment-3576074285
> No need, now I understand the results you are providing. I think you
should provide the comparison with main for completeness (e.g is this solution
competitive with the current status quo).
Thanks! Below are the results without enabling intra-segment search (on both
`lucene_candidate` and `lucene_baseline`), which reflects the current behavior
on `main`.
```
TaskQPS baseline StdDevQPS
my_modified_version StdDev Pct diff p-value
BrowseDateSSDVFacets 0.56 (16.1%) 0.50
(1.1%) -11.0% ( -24% - 7%) 0.337
OrHighNotLow 221.92 (9.6%) 198.50
(10.8%) -10.6% ( -28% - 10%) 0.301
OrHighNotHigh 99.49 (8.9%) 90.42
(3.9%) -9.1% ( -20% - 4%) 0.186
AndHighMedDayTaxoFacets 27.38 (3.2%) 25.24
(2.4%) -7.8% ( -13% - -2%) 0.006
MedTerm 352.99 (3.0%) 331.70
(2.7%) -6.0% ( -11% - 0%) 0.036
HighTermTitleSort 20.00 (2.1%) 19.13
(2.7%) -4.3% ( -8% - 0%) 0.076
OrHighLow 354.88 (14.1%) 341.84
(7.3%) -3.7% ( -22% - 20%) 0.744
range 1531.41 (3.8%) 1478.39
(5.7%) -3.5% ( -12% - 6%) 0.476
HighSloppyPhrase 9.15 (1.0%) 8.88
(1.3%) -3.0% ( -5% - 0%) 0.009
MedTermDayTaxoFacets 7.75 (13.9%) 7.58
(9.0%) -2.2% ( -22% - 24%) 0.852
BrowseDayOfYearSSDVFacets 2.88 (34.4%) 2.83
(15.4%) -1.8% ( -38% - 73%) 0.945
AndHighLow 532.13 (1.7%) 526.10
(3.4%) -1.1% ( -6% - 4%) 0.674
AndHighHigh 39.57 (6.2%) 39.20
(1.3%) -0.9% ( -7% - 7%) 0.834
OrHighHigh 63.20 (2.8%) 62.78
(2.9%) -0.7% ( -6% - 5%) 0.814
PKLookup 152.77 (2.4%) 152.01
(0.3%) -0.5% ( -3% - 2%) 0.770
HighTermDayOfYearSort 70.31 (0.4%) 70.05
(6.7%) -0.4% ( -7% - 6%) 0.939
LowSpanNear 12.96 (2.6%) 12.94
(0.7%) -0.1% ( -3% - 3%) 0.944
LowPhrase 23.84 (1.2%) 23.82
(1.1%) -0.1% ( -2% - 2%) 0.945
LowSloppyPhrase 7.93 (5.2%) 7.94
(0.2%) 0.2% ( -4% - 5%) 0.966
HighTermTitleBDVSort 9.53 (10.7%) 9.55
(9.3%) 0.2% ( -17% - 22%) 0.985
OrHighNotMed 162.09 (4.9%) 162.41
(1.2%) 0.2% ( -5% - 6%) 0.957
IntNRQ 48.11 (5.4%) 48.34
(5.0%) 0.5% ( -9% - 11%) 0.928
Wildcard 18.14 (0.5%) 18.25
(1.7%) 0.6% ( -1% - 2%) 0.654
BrowseMonthTaxoFacets 2.28 (0.3%) 2.30
(4.4%) 0.7% ( -3% - 5%) 0.829
HighSpanNear 5.88 (3.4%) 5.94
(5.2%) 1.1% ( -7% - 10%) 0.799
HighPhrase 11.88 (2.3%) 12.05
(3.8%) 1.5% ( -4% - 7%) 0.638
Fuzzy2 42.79 (0.7%) 43.45
(15.6%) 1.6% ( -14% - 17%) 0.888
LowTerm 462.46 (2.5%) 471.91
(5.4%) 2.0% ( -5% - 10%) 0.628
Prefix3 201.07 (4.2%) 205.62
(0.7%) 2.3% ( -2% - 7%) 0.454
OrNotHighHigh 192.75 (1.4%) 197.39
(3.8%) 2.4% ( -2% - 7%) 0.396
LowIntervalsOrdered 20.77 (3.2%) 21.28
(4.0%) 2.5% ( -4% - 9%) 0.499
AndHighMed 125.26 (6.8%) 128.38
(7.2%) 2.5% ( -10% - 17%) 0.722
OrHighMedDayTaxoFacets 5.56 (3.2%) 5.70
(1.1%) 2.5% ( -1% - 7%) 0.293
MedSpanNear 41.21 (2.4%) 42.62
(3.3%) 3.4% ( -2% - 9%) 0.239
AndHighHighDayTaxoFacets 3.89 (3.3%) 4.03
(0.8%) 3.4% ( 0% - 7%) 0.150
HighIntervalsOrdered 6.43 (0.4%) 6.69
(0.3%) 3.9% ( 3% - 4%) 0.000
BrowseRandomLabelTaxoFacets 1.72 (4.0%) 1.79
(1.9%) 4.1% ( -1% - 10%) 0.192
TermDTSort 76.67 (2.1%) 79.95
(3.8%) 4.3% ( -1% - 10%) 0.165
MedPhrase 37.46 (4.2%) 39.26
(0.9%) 4.8% ( 0% - 10%) 0.112
OrHighMed 170.61 (3.8%) 180.07
(8.8%) 5.5% ( -6% - 18%) 0.413
OrNotHighLow 406.32 (4.2%) 429.70
(0.8%) 5.8% ( 0% - 11%) 0.058
HighTerm 277.15 (1.1%) 293.83
(5.3%) 6.0% ( 0% - 12%) 0.118
HighTermMonthSort 440.76 (6.9%) 474.15
(1.8%) 7.6% ( -1% - 17%) 0.131
Fuzzy1 30.28 (8.7%) 32.72
(20.1%) 8.0% ( -19% - 40%) 0.604
MedSloppyPhrase 48.44 (5.4%) 52.45
(0.4%) 8.3% ( 2% - 14%) 0.030
BrowseDateTaxoFacets 2.14 (14.9%) 2.32
(9.4%) 8.5% ( -13% - 38%) 0.495
BrowseDayOfYearTaxoFacets 1.98 (2.2%) 2.15
(13.6%) 8.7% ( -6% - 24%) 0.375
MedIntervalsOrdered 1.63 (2.2%) 1.79
(2.1%) 9.8% ( 5% - 14%) 0.000
Respell 27.76 (8.9%) 30.85
(6.1%) 11.1% ( -3% - 28%) 0.144
IntSet 262.93 (6.0%) 292.36
(0.3%) 11.2% ( 4% - 18%) 0.009
OrNotHighMed 134.43 (20.1%) 149.87
(9.4%) 11.5% ( -15% - 51%) 0.465
BrowseRandomLabelSSDVFacets 1.84 (12.0%) 2.07
(0.2%) 12.4% ( 0% - 28%) 0.144
BrowseMonthSSDVFacets 3.06 (21.2%) 3.98
(71.7%) 30.0% ( -51% - 155%) 0.570
```
This approach aims to improve PointRangeQuery performance when intra-segment
search is enabled, as part of stabilizing the intra-segment work and eliminate
per-segment work across segment partitions
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