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https://issues.apache.org/jira/browse/LUCENE-10480?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17564611#comment-17564611
]
Zach Chen commented on LUCENE-10480:
------------------------------------
{quote}[AndMedOrHighHigh|https://home.apache.org/~mikemccand/lucenebench/AndMedOrHighHigh.html]
recovered fully but
[AndHighOrMedMed|https://home.apache.org/~mikemccand/lucenebench/AndHighOrMedMed.html]
only a bit. I'm unsure what explains there is still a slowdown compared to BMW.
{quote}
Hmm this is quite strange. Looks like
[AndHighOrMedMed|https://home.apache.org/~mikemccand/lucenebench/AndHighOrMedMed.html]
was still having about -13% (5 / 38) impact. I just ran the full suite of
wikinightly tasks a few times (by copying *wikinightly.tasks* into
*wikimedium.10M.nostopwords.tasks* and running *localrun.py* with source
*wikimedium10m,* and removing *VectorSearch* queries as they were causing
failure NPE for me) but couldn't reproduce the slow down (baseline is using
head before all BMM changes):
{code:java}
TaskQPS baseline StdDevQPS my_modified_version
StdDev Pct diff p-value
BrowseRandomLabelSSDVFacets 20.83 (3.8%) 20.09
(6.5%) -3.6% ( -13% - 6%) 0.034
BrowseMonthSSDVFacets 30.36 (10.6%) 29.56
(12.7%) -2.7% ( -23% - 23%) 0.473
Prefix3 402.70 (9.3%) 397.59
(9.9%) -1.3% ( -18% - 19%) 0.674
TermDayOfYearSort 183.55 (6.5%) 181.61
(6.9%) -1.1% ( -13% - 13%) 0.617
TermTitleSort 195.99 (7.2%) 194.25
(8.1%) -0.9% ( -15% - 15%) 0.713
PKLookup 293.80 (3.7%) 291.47
(4.8%) -0.8% ( -8% - 7%) 0.555
TermMonthSort 283.86 (7.1%) 281.74
(8.0%) -0.7% ( -14% - 15%) 0.755
Wildcard 227.26 (6.2%) 225.87
(6.4%) -0.6% ( -12% - 12%) 0.759
Term 2227.50 (3.7%) 2219.57
(3.3%) -0.4% ( -7% - 6%) 0.748
Fuzzy1 134.77 (2.8%) 134.37
(2.3%) -0.3% ( -5% - 4%) 0.712
TermGroup100 53.61 (3.7%) 53.47
(4.6%) -0.3% ( -8% - 8%) 0.846
TermDTSort 143.16 (3.2%) 142.89
(3.3%) -0.2% ( -6% - 6%) 0.857
TermBGroup1M1P 79.44 (5.5%) 79.29
(5.5%) -0.2% ( -10% - 11%) 0.917
AndHighHighDayTaxoFacets 45.01 (2.3%) 44.94
(2.1%) -0.1% ( -4% - 4%) 0.833
BrowseRandomLabelTaxoFacets 30.94 (50.0%) 30.92
(46.8%) -0.0% ( -64% - 193%) 0.998
AndHighMedDayTaxoFacets 78.11 (3.2%) 78.11
(3.0%) -0.0% ( -6% - 6%) 0.998
Phrase 202.17 (2.7%) 202.18
(2.0%) 0.0% ( -4% - 4%) 0.996
Fuzzy2 76.10 (2.6%) 76.15
(2.0%) 0.1% ( -4% - 4%) 0.933
TermGroup1M 22.65 (3.8%) 22.67
(3.2%) 0.1% ( -6% - 7%) 0.919
TermDateFacets 32.50 (5.3%) 32.60
(5.5%) 0.3% ( -9% - 11%) 0.861
BrowseDayOfYearSSDVFacets 26.31 (5.9%) 26.39
(8.5%) 0.3% ( -13% - 15%) 0.897
Respell 88.21 (2.2%) 88.49
(2.1%) 0.3% ( -3% - 4%) 0.642
SpanNear 16.14 (4.0%) 16.22
(4.2%) 0.5% ( -7% - 9%) 0.706
MedTermDayTaxoFacets 73.42 (4.8%) 73.85
(4.9%) 0.6% ( -8% - 10%) 0.708
TermBGroup1M 48.92 (4.2%) 49.23
(2.8%) 0.6% ( -6% - 8%) 0.581
IntervalsOrdered 22.42 (5.8%) 22.59
(4.2%) 0.7% ( -8% - 11%) 0.651
OrHighMedDayTaxoFacets 25.27 (6.1%) 25.46
(6.6%) 0.7% ( -11% - 14%) 0.711
TermGroup10K 30.26 (4.2%) 30.50
(2.9%) 0.8% ( -6% - 8%) 0.494
SloppyPhrase 91.40 (5.6%) 92.16
(6.3%) 0.8% ( -10% - 13%) 0.662
IntNRQ 152.74 (20.3%) 154.86
(17.1%) 1.4% ( -29% - 48%) 0.815
AndHighMed 88.55 (2.6%) 89.98
(3.1%) 1.6% ( -3% - 7%) 0.073
AndHighHigh 29.10 (2.7%) 29.68
(3.1%) 2.0% ( -3% - 8%) 0.032
BrowseDayOfYearTaxoFacets 31.29 (40.0%) 31.93
(38.0%) 2.0% ( -54% - 133%) 0.869
BrowseDateTaxoFacets 31.18 (40.3%) 31.87
(38.5%) 2.2% ( -54% - 135%) 0.859
BrowseDateSSDVFacets 3.79 (28.4%) 3.92
(27.9%) 3.4% ( -41% - 83%) 0.700
AndHighOrMedMed 63.04 (6.1%) 65.68
(5.5%) 4.2% ( -7% - 16%) 0.023
AndMedOrHighHigh 92.29 (4.6%) 99.20
(5.5%) 7.5% ( -2% - 18%) 0.000
BrowseMonthTaxoFacets 30.93 (39.4%) 34.36
(43.4%) 11.1% ( -51% - 154%) 0.397
OrHighHigh 20.09 (6.5%) 33.58
(8.7%) 67.2% ( 48% - 88%) 0.000
OrHighMed 78.61 (5.4%) 186.58
(10.7%) 137.4% ( 115% - 162%) 0.000 {code}
{code:java}
TaskQPS baseline StdDevQPS my_modified_version
StdDev Pct diff p-value
TermBGroup1M1P 81.36 (7.8%) 78.61
(5.5%) -3.4% ( -15% - 10%) 0.114
BrowseMonthSSDVFacets 29.39 (13.1%) 28.50
(13.3%) -3.0% ( -26% - 26%) 0.469
BrowseDateSSDVFacets 3.91 (27.0%) 3.81
(27.5%) -2.5% ( -44% - 71%) 0.768
AndHighOrMedMed 108.53 (6.6%) 106.50
(5.7%) -1.9% ( -13% - 11%) 0.336
OrHighMedDayTaxoFacets 23.14 (4.4%) 22.93
(6.5%) -0.9% ( -11% - 10%) 0.596
TermGroup100 64.69 (4.4%) 64.13
(3.4%) -0.9% ( -8% - 7%) 0.492
TermDayOfYearSort 142.82 (5.3%) 141.72
(2.7%) -0.8% ( -8% - 7%) 0.562
SloppyPhrase 3.10 (4.2%) 3.08
(4.6%) -0.7% ( -9% - 8%) 0.629
Phrase 35.56 (2.5%) 35.36
(2.4%) -0.6% ( -5% - 4%) 0.467
SpanNear 13.52 (3.7%) 13.45
(3.3%) -0.5% ( -7% - 6%) 0.667
Prefix3 395.12 (9.1%) 393.74
(10.6%) -0.3% ( -18% - 21%) 0.911
TermMonthSort 192.42 (9.5%) 191.95
(7.1%) -0.2% ( -15% - 18%) 0.926
Term 3216.34 (3.6%) 3208.51
(3.8%) -0.2% ( -7% - 7%) 0.833
TermTitleSort 278.44 (9.5%) 277.85
(7.1%) -0.2% ( -15% - 18%) 0.936
Respell 89.07 (2.1%) 88.98
(2.6%) -0.1% ( -4% - 4%) 0.885
Fuzzy1 127.07 (1.9%) 127.23
(2.8%) 0.1% ( -4% - 4%) 0.874
BrowseRandomLabelSSDVFacets 20.41 (9.5%) 20.44
(8.6%) 0.2% ( -16% - 20%) 0.954
Wildcard 366.66 (6.1%) 367.33
(6.1%) 0.2% ( -11% - 13%) 0.925
PKLookup 291.94 (4.4%) 292.59
(2.9%) 0.2% ( -6% - 7%) 0.849
IntNRQ 351.10 (1.2%) 351.89
(1.1%) 0.2% ( -2% - 2%) 0.540
TermGroup10K 22.73 (3.5%) 22.81
(3.5%) 0.4% ( -6% - 7%) 0.731
AndHighHigh 49.25 (4.1%) 49.45
(4.6%) 0.4% ( -7% - 9%) 0.770
Fuzzy2 136.67 (2.0%) 137.33
(2.5%) 0.5% ( -3% - 5%) 0.497
MedTermDayTaxoFacets 75.39 (3.4%) 75.79
(2.8%) 0.5% ( -5% - 7%) 0.591
AndHighMedDayTaxoFacets 135.26 (2.6%) 136.01
(2.1%) 0.6% ( -3% - 5%) 0.449
AndHighHighDayTaxoFacets 11.44 (2.4%) 11.50
(1.9%) 0.6% ( -3% - 4%) 0.386
IntervalsOrdered 13.19 (2.6%) 13.27
(2.8%) 0.6% ( -4% - 6%) 0.456
TermDateFacets 32.59 (3.8%) 32.81
(3.1%) 0.7% ( -5% - 7%) 0.526
AndHighMed 109.27 (4.6%) 110.09
(5.6%) 0.7% ( -9% - 11%) 0.648
AndMedOrHighHigh 67.43 (6.2%) 68.02
(6.2%) 0.9% ( -10% - 14%) 0.654
TermGroup1M 26.00 (2.9%) 26.26
(3.4%) 1.0% ( -5% - 7%) 0.310
BrowseDayOfYearSSDVFacets 27.08 (10.0%) 27.36
(14.4%) 1.0% ( -21% - 28%) 0.792
TermBGroup1M 37.57 (3.2%) 38.00
(4.0%) 1.1% ( -5% - 8%) 0.318
TermDTSort 141.09 (2.6%) 143.58
(6.5%) 1.8% ( -7% - 11%) 0.259
BrowseMonthTaxoFacets 28.19 (37.9%) 29.70
(40.8%) 5.3% ( -53% - 135%) 0.669
BrowseDayOfYearTaxoFacets 29.32 (37.6%) 31.00
(43.4%) 5.7% ( -54% - 138%) 0.656
BrowseDateTaxoFacets 29.18 (37.9%) 30.94
(43.8%) 6.0% ( -54% - 141%) 0.641
BrowseRandomLabelTaxoFacets 28.43 (47.1%) 30.67
(55.1%) 7.9% ( -64% - 207%) 0.627
OrHighHigh 19.75 (5.8%) 28.41
(6.0%) 43.9% ( 30% - 59%) 0.000
OrHighMed 78.52 (6.7%) 181.93
(10.9%) 131.7% ( 106% - 159%) 0.000 {code}
{code:java}
TaskQPS baseline StdDevQPS my_modified_version
StdDev Pct diff p-value
BrowseMonthSSDVFacets 28.38 (11.8%) 27.82
(10.5%) -2.0% ( -21% - 22%) 0.573
PKLookup 296.46 (2.0%) 290.88
(2.9%) -1.9% ( -6% - 3%) 0.016
TermDayOfYearSort 214.70 (7.4%) 210.70
(4.1%) -1.9% ( -12% - 10%) 0.323
TermBGroup1M 29.42 (4.0%) 28.91
(5.3%) -1.7% ( -10% - 7%) 0.236
TermGroup1M 23.08 (3.4%) 22.70
(4.3%) -1.7% ( -9% - 6%) 0.170
TermDTSort 345.43 (6.4%) 339.68
(4.9%) -1.7% ( -12% - 10%) 0.354
TermGroup10K 30.91 (3.3%) 30.44
(4.5%) -1.5% ( -9% - 6%) 0.220
TermDateFacets 47.40 (4.8%) 46.81
(3.8%) -1.3% ( -9% - 7%) 0.362
TermBGroup1M1P 81.44 (6.7%) 80.48
(7.5%) -1.2% ( -14% - 13%) 0.601
BrowseRandomLabelSSDVFacets 20.26 (7.9%) 20.02
(7.8%) -1.2% ( -15% - 15%) 0.637
MedTermDayTaxoFacets 75.68 (4.2%) 74.84
(3.4%) -1.1% ( -8% - 6%) 0.357
BrowseRandomLabelTaxoFacets 38.85 (44.7%) 38.42
(46.1%) -1.1% ( -63% - 162%) 0.940
TermGroup100 41.49 (3.7%) 41.05
(4.5%) -1.0% ( -8% - 7%) 0.419
BrowseDateTaxoFacets 37.84 (36.3%) 37.51
(38.4%) -0.9% ( -55% - 115%) 0.941
BrowseDayOfYearTaxoFacets 37.88 (36.2%) 37.60
(38.1%) -0.7% ( -55% - 115%) 0.950
AndHighHighDayTaxoFacets 7.05 (3.3%) 7.00
(3.8%) -0.7% ( -7% - 6%) 0.533
SloppyPhrase 93.42 (7.8%) 93.27
(6.9%) -0.2% ( -13% - 15%) 0.942
BrowseDateSSDVFacets 3.81 (28.9%) 3.80
(28.5%) -0.1% ( -44% - 80%) 0.993
Phrase 44.60 (2.9%) 44.68
(2.8%) 0.2% ( -5% - 6%) 0.840
SpanNear 27.76 (3.1%) 27.81
(2.8%) 0.2% ( -5% - 6%) 0.830
TermTitleSort 224.37 (7.2%) 225.08
(7.8%) 0.3% ( -13% - 16%) 0.895
TermMonthSort 277.86 (7.2%) 279.21
(7.9%) 0.5% ( -13% - 16%) 0.838
IntNRQ 1286.28 (3.0%) 1292.89
(2.0%) 0.5% ( -4% - 5%) 0.525
Term 2602.76 (3.0%) 2616.13
(3.7%) 0.5% ( -6% - 7%) 0.630
AndHighMedDayTaxoFacets 78.64 (3.2%) 79.12
(3.0%) 0.6% ( -5% - 7%) 0.540
Wildcard 375.54 (5.9%) 378.24
(3.9%) 0.7% ( -8% - 11%) 0.649
OrHighMedDayTaxoFacets 25.37 (7.9%) 25.56
(5.4%) 0.7% ( -11% - 15%) 0.728
AndHighOrMedMed 107.73 (5.2%) 108.60
(3.9%) 0.8% ( -7% - 10%) 0.572
Respell 108.71 (1.1%) 109.74
(2.2%) 0.9% ( -2% - 4%) 0.087
BrowseDayOfYearSSDVFacets 27.55 (10.9%) 27.82
(13.0%) 1.0% ( -20% - 27%) 0.797
AndHighMed 110.51 (4.3%) 111.60
(3.7%) 1.0% ( -6% - 9%) 0.441
Fuzzy1 133.81 (1.2%) 135.34
(1.9%) 1.1% ( -1% - 4%) 0.025
AndHighHigh 119.20 (3.7%) 120.59
(3.4%) 1.2% ( -5% - 8%) 0.302
Fuzzy2 78.92 (1.4%) 80.08
(2.0%) 1.5% ( -1% - 4%) 0.008
IntervalsOrdered 22.54 (4.5%) 22.90
(3.8%) 1.6% ( -6% - 10%) 0.226
BrowseMonthTaxoFacets 33.99 (38.5%) 35.09
(37.9%) 3.2% ( -52% - 129%) 0.788
Prefix3 410.98 (8.6%) 425.40
(5.9%) 3.5% ( -10% - 19%) 0.131
AndMedOrHighHigh 67.29 (3.7%) 69.77
(4.3%) 3.7% ( -4% - 12%) 0.003
OrHighHigh 19.57 (5.3%) 28.41
(5.6%) 45.2% ( 32% - 59%) 0.000
OrHighMed 95.08 (4.9%) 271.09
(10.1%) 185.1% ( 162% - 210%) 0.000 {code}
Also my *localconstants* file & java version for reference
{code:java}
BASE_DIR = '/Users/xichen/IdeaProjects/benchmarks'
BENCH_BASE_DIR = '/Users/xichen/IdeaProjects/benchmarks/util'
WIKI_BIG_DOCS_LINE_FILE = '%s/data/enwiki-20130102-lines.txt' % BASE_DIR
WIKI_BIG_DOCS_COUNT = 6647577
INDEX_NUM_THREADS = 10
# SEARCH_NUM_THREADS = 6
topN=100
{code}
{code:java}
xichen@MacBook-Pro util % java --version
java 17.0.2 2022-01-18 LTS
Java(TM) SE Runtime Environment (build 17.0.2+8-LTS-86)
Java HotSpot(TM) 64-Bit Server VM (build 17.0.2+8-LTS-86, mixed mode, sharing)
{code}
Maybe the nightly benchmark is using another suite of tests or the JVM setting
matters? I'll see if I can run the original nightly benchmark code / tests
from my machine to see if there's any difference.
> Specialize 2-clauses disjunctions
> ---------------------------------
>
> Key: LUCENE-10480
> URL: https://issues.apache.org/jira/browse/LUCENE-10480
> Project: Lucene - Core
> Issue Type: Task
> Reporter: Adrien Grand
> Priority: Minor
> Time Spent: 7h 20m
> Remaining Estimate: 0h
>
> WANDScorer is nice, but it also has lots of overhead to maintain its
> invariants: one linked list for the current candidates, one priority queue of
> scorers that are behind, another one for scorers that are ahead. All this
> could be simplified in the 2-clauses case, which feels worth specializing for
> as it's very common that end users enter queries that only have two terms?
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