Run top-level conjunctions of term queries with a specialized BulkScorer. #12382

jpountz · 2023-06-22T16:49:53Z

This implements a specialized BlockMaxConjunctionBulkScorer, which is similar to BlockMaxConjunctionScorer with the following differences:

Implemented as a BulkScorer instead of a Scorer (ie. for top-level conjunctions only).
Only used for clauses that have simple iterators (not two-phase iterators).
Checks if a competitive score is still possible before advancing the next clause. This helps because it's often less costly to do this check than advancing the next clause, which might in-turn require decoding an entire block of postings.

…rer. This implements a specialized `BlockMaxConjunctionBulkScorer`, which is really the same as `BlockMaxConjunctionScorer`, but as a `BulkScorer` instead of a `Scorer`. Also it doesn't support two-phase iterators in order to focus on the common case when queries, such as term queries, do not have two-phase iterators. If a clause has a two-phase iterator, it will keep running as a `BlockMaxConjunctionScorer` wrapped in a `DefaultBulkScorer`.

jpountz · 2023-06-23T09:42:46Z

The speedup is not as high as I had hoped, so I'm leaning towards not merging this PR. Maybe someone figures out how to make this code run faster!

                            TaskQPS baseline      StdDevQPS my_modified_version      StdDev                Pct diff p-value
                      TermDTSort      183.14      (1.6%)      179.82      (5.1%)   -1.8% (  -8% -    5%) 0.133
                          IntNRQ      105.92     (15.4%)      104.00     (13.4%)   -1.8% ( -26% -   32%) 0.693
           HighTermDayOfYearSort      436.32      (1.8%)      428.70      (5.8%)   -1.7% (  -9% -    6%) 0.203
               HighTermTitleSort      151.24      (6.0%)      148.87      (8.8%)   -1.6% ( -15% -   14%) 0.512
                      AndHighLow     1692.56      (3.7%)     1666.70      (2.8%)   -1.5% (  -7% -    5%) 0.140
     BrowseRandomLabelSSDVFacets       14.89      (8.3%)       14.75      (6.4%)   -0.9% ( -14% -   14%) 0.685
           BrowseMonthTaxoFacets       30.24      (6.9%)       29.95      (8.3%)   -0.9% ( -15% -   15%) 0.698
                      OrHighHigh       47.35      (6.6%)       46.96      (4.2%)   -0.8% ( -10% -   10%) 0.630
                        Wildcard      220.59      (4.7%)      218.79      (4.4%)   -0.8% (  -9% -    8%) 0.570
       BrowseDayOfYearTaxoFacets       45.10      (3.5%)       44.82      (2.7%)   -0.6% (  -6% -    5%) 0.525
                       OrHighLow      650.91      (4.4%)      647.28      (3.1%)   -0.6% (  -7% -    7%) 0.646
            HighTermTitleBDVSort       25.83      (1.7%)       25.70      (3.6%)   -0.5% (  -5% -    4%) 0.575
                       OrHighMed      167.05      (5.0%)      166.32      (3.6%)   -0.4% (  -8% -    8%) 0.752
             MedIntervalsOrdered       17.59      (3.5%)       17.53      (4.1%)   -0.4% (  -7% -    7%) 0.758
                      AndHighMed      391.35      (4.4%)      390.02      (3.7%)   -0.3% (  -8% -    8%) 0.789
                    OrNotHighLow     1442.98      (3.7%)     1438.18      (3.3%)   -0.3% (  -7% -    7%) 0.767
            BrowseDateTaxoFacets       44.30      (3.0%)       44.19      (3.0%)   -0.2% (  -6% -    5%) 0.795
                          Fuzzy1      139.23      (1.1%)      138.94      (1.0%)   -0.2% (  -2% -    1%) 0.539
                          Fuzzy2      112.21      (0.8%)      112.00      (0.9%)   -0.2% (  -1% -    1%) 0.502
                 MedSloppyPhrase       35.95      (2.2%)       35.90      (2.1%)   -0.1% (  -4% -    4%) 0.836
                         Respell       95.08      (1.5%)       94.97      (1.4%)   -0.1% (  -2% -    2%) 0.795
                     MedSpanNear      100.90      (5.9%)      100.89      (7.0%)   -0.0% ( -12% -   13%) 0.997
                        PKLookup      242.29      (5.0%)      242.27      (4.2%)   -0.0% (  -8% -    9%) 0.995
                HighSloppyPhrase       24.75      (3.2%)       24.75      (4.6%)   -0.0% (  -7% -    8%) 0.997
             LowIntervalsOrdered       13.76      (4.3%)       13.77      (4.2%)    0.0% (  -8% -    8%) 0.976
          OrHighMedDayTaxoFacets       17.13      (4.5%)       17.14      (3.6%)    0.1% (  -7% -    8%) 0.937
       BrowseDayOfYearSSDVFacets       20.81     (13.8%)       20.83     (13.5%)    0.1% ( -23% -   31%) 0.980
                         Prefix3      249.54      (5.3%)      250.06      (2.6%)    0.2% (  -7% -    8%) 0.875
                     LowSpanNear       51.89      (2.1%)       52.03      (2.7%)    0.3% (  -4% -    5%) 0.740
                    HighSpanNear       30.44      (4.2%)       30.54      (5.2%)    0.3% (  -8% -   10%) 0.841
                    OrNotHighMed      435.83      (6.3%)      437.24      (5.3%)    0.3% ( -10% -   12%) 0.860
            BrowseDateSSDVFacets        5.52      (7.9%)        5.54     (10.2%)    0.4% ( -16% -   20%) 0.894
                   OrHighNotHigh      332.17      (7.0%)      333.72      (6.0%)    0.5% ( -11% -   14%) 0.821
                         LowTerm      852.62      (6.5%)      856.98      (5.7%)    0.5% ( -10% -   13%) 0.791
                 LowSloppyPhrase       34.09      (4.2%)       34.28      (3.8%)    0.6% (  -7% -    8%) 0.654
                    OrHighNotMed      389.58      (7.0%)      392.08      (6.6%)    0.6% ( -12% -   15%) 0.765
            HighIntervalsOrdered       16.82      (5.4%)       16.93      (7.3%)    0.6% ( -11% -   14%) 0.750
                    OrHighNotLow      503.57      (7.5%)      507.57      (6.6%)    0.8% ( -12% -   16%) 0.721
                         MedTerm      954.20      (8.0%)      962.60      (6.3%)    0.9% ( -12% -   16%) 0.699
                   OrNotHighHigh      483.09      (6.5%)      487.85      (5.4%)    1.0% ( -10% -   13%) 0.601
           BrowseMonthSSDVFacets       21.00      (9.5%)       21.25     (10.3%)    1.2% ( -16% -   23%) 0.697
         AndHighMedDayTaxoFacets       20.84      (2.6%)       21.18      (2.9%)    1.6% (  -3% -    7%) 0.060
        AndHighHighDayTaxoFacets       28.62      (2.1%)       29.09      (2.3%)    1.6% (  -2% -    6%) 0.018
                      HighPhrase      211.10      (4.2%)      214.68      (3.3%)    1.7% (  -5% -    9%) 0.154
                        HighTerm      380.81      (8.8%)      387.70      (6.9%)    1.8% ( -12% -   19%) 0.472
                       MedPhrase       22.08      (4.8%)       22.48      (3.8%)    1.8% (  -6% -   10%) 0.180
            MedTermDayTaxoFacets       80.33      (3.1%)       81.88      (2.7%)    1.9% (  -3% -    7%) 0.036
                       LowPhrase      348.19      (3.5%)      355.21      (2.9%)    2.0% (  -4% -    8%) 0.048
               HighTermMonthSort     3789.19      (4.2%)     3879.83      (3.0%)    2.4% (  -4% -   10%) 0.039
     BrowseRandomLabelTaxoFacets       35.61      (6.2%)       36.77      (2.3%)    3.3% (  -4% -   12%) 0.028
                     AndHighHigh       51.92      (5.9%)       54.91      (5.0%)    5.7% (  -4% -   17%) 0.001

jpountz · 2023-09-21T13:45:09Z

Reopening as I'm now seeing speedups. It's possible it's related to other changes that happened since last time I looked, or to the specific tasks that get picked by luceneutil. Here's the output of a run on wikibigall:

                            TaskQPS baseline      StdDevQPS my_modified_version      StdDev                Pct diff p-value
               HighTermMonthSort     2585.95      (5.2%)     2525.81      (7.8%)   -2.3% ( -14% -   11%) 0.268
                         LowTerm      910.97      (5.9%)      890.32      (5.8%)   -2.3% ( -13% -    9%) 0.218
                        HighTerm      520.07      (5.2%)      510.12      (5.2%)   -1.9% ( -11% -    8%) 0.245
                         MedTerm      456.03      (5.5%)      448.52      (5.2%)   -1.6% ( -11% -    9%) 0.329
                       OrHighMed      190.06      (2.9%)      187.85      (3.6%)   -1.2% (  -7% -    5%) 0.263
           HighTermDayOfYearSort      268.40      (3.2%)      265.61      (2.6%)   -1.0% (  -6% -    4%) 0.261
                     MedSpanNear       43.74      (2.9%)       43.33      (2.8%)   -0.9% (  -6% -    4%) 0.297
                    HighSpanNear        4.33      (2.7%)        4.31      (3.0%)   -0.5% (  -6% -    5%) 0.571
                          Fuzzy2       58.11      (2.0%)       57.83      (2.3%)   -0.5% (  -4% -    3%) 0.482
                       MedPhrase       78.83      (2.3%)       78.47      (3.0%)   -0.5% (  -5% -    4%) 0.579
                     LowSpanNear       11.19      (1.6%)       11.15      (2.1%)   -0.4% (  -3% -    3%) 0.546
                       OrHighLow      625.94      (3.1%)      624.02      (3.4%)   -0.3% (  -6% -    6%) 0.768
                CountAndHighHigh       45.07      (3.5%)       44.94      (4.3%)   -0.3% (  -7% -    7%) 0.813
                      OrHighHigh       41.35      (5.5%)       41.23      (5.9%)   -0.3% ( -11% -   11%) 0.881
                 CountAndHighMed      149.52      (3.2%)      149.33      (3.3%)   -0.1% (  -6% -    6%) 0.903
                 LowSloppyPhrase       52.33      (1.7%)       52.28      (2.5%)   -0.1% (  -4% -    4%) 0.892
                         Prefix3      271.79      (3.4%)      271.62      (3.8%)   -0.1% (  -7% -    7%) 0.955
                        PKLookup      211.98      (3.4%)      211.93      (2.6%)   -0.0% (  -5% -    6%) 0.981
                       LowPhrase       53.95      (2.1%)       53.96      (2.4%)    0.0% (  -4% -    4%) 0.975
                     CountPhrase        2.78      (4.3%)        2.79      (2.0%)    0.1% (  -5% -    6%) 0.950
                          Fuzzy1      138.29      (2.1%)      138.39      (2.6%)    0.1% (  -4% -    4%) 0.918
                      HighPhrase       28.83      (3.2%)       28.86      (4.7%)    0.1% (  -7% -    8%) 0.932
                HighSloppyPhrase        7.74      (1.8%)        7.75      (2.6%)    0.2% (  -4% -    4%) 0.764
                  CountOrHighMed      138.64     (15.8%)      138.99     (15.0%)    0.2% ( -26% -   36%) 0.959
                         Respell       56.79      (1.8%)       56.95      (2.3%)    0.3% (  -3% -    4%) 0.664
                 CountOrHighHigh       40.89     (17.1%)       41.02     (15.9%)    0.3% ( -27% -   40%) 0.951
                      AndHighLow     1009.08      (3.2%)     1013.60      (4.4%)    0.4% (  -6% -    8%) 0.713
                       CountTerm     8120.00      (7.4%)     8193.70     (11.2%)    0.9% ( -16% -   21%) 0.763
                          IntNRQ      302.71      (6.2%)      305.63      (6.7%)    1.0% ( -11% -   14%) 0.634
                 MedSloppyPhrase       19.03      (4.7%)       19.28      (4.9%)    1.3% (  -7% -   11%) 0.387
                        Wildcard       25.15      (4.7%)       25.59      (4.3%)    1.7% (  -6% -   11%) 0.223
                      AndHighMed      171.18      (2.9%)      230.86      (4.4%)   34.9% (  26% -   43%) 0.000
                     AndHighHigh       46.05      (4.4%)       78.03      (5.6%)   69.4% (  56% -   82%) 0.000

benwtrent

The numbers are impressive. I have some code design/flow comments.

lucene/CHANGES.txt

lucene/core/src/java/org/apache/lucene/search/BlockMaxConjunctionBulkScorer.java

lucene/core/src/java/org/apache/lucene/search/BooleanWeight.java

jpountz · 2023-09-21T14:32:51Z

The numbers are impressive

I agree... it makes me suspicous. I'll verify my localrun.py and run with higher taskCountPerCat and taskRepeatCount to see if I'm still getting such good results.

benwtrent · 2023-09-21T14:44:07Z

I agree... it makes me suspicous. I'll verify my localrun.py and run with higher taskCountPerCat and taskRepeatCount to see if I'm still getting such good results.

I doubt this is your problem, but I have made the mistake in the past of benchmarking the incorrect commit because either:

I had merged in the wrong things and didn't double check
Forgot to point to the correct directory and use ./gradlew clean && ./gradlew jar to ensure everything built ONLY with my changes.

jpountz · 2023-09-21T15:06:34Z

Running with taskCountPerCat=5 and taskRepeatCount=50 gave very similar results:

                            TaskQPS baseline      StdDevQPS my_modified_version      StdDev                Pct diff p-value
                        HighTerm      472.68      (4.7%)      464.58      (3.8%)   -1.7% (  -9% -    7%) 0.392
                         MedTerm      585.82      (3.6%)      580.49      (3.7%)   -0.9% (  -7% -    6%) 0.598
           HighTermDayOfYearSort      286.30      (1.2%)      284.36      (1.9%)   -0.7% (  -3% -    2%) 0.362
                      OrHighHigh       51.81      (6.7%)       51.54      (4.5%)   -0.5% ( -10% -   11%) 0.842
                        Wildcard      225.50      (3.3%)      224.32      (3.3%)   -0.5% (  -6% -    6%) 0.734
                       OrHighLow      611.45      (2.6%)      608.55      (3.0%)   -0.5% (  -5% -    5%) 0.723
                       OrHighMed      118.00      (5.0%)      117.46      (3.6%)   -0.5% (  -8% -    8%) 0.823
                         LowTerm     1000.83      (3.3%)      996.92      (3.5%)   -0.4% (  -7% -    6%) 0.809
                        PKLookup      222.91      (1.0%)      222.27      (3.2%)   -0.3% (  -4% -    4%) 0.800
                          IntNRQ      106.47     (20.2%)      106.19     (19.5%)   -0.3% ( -33% -   49%) 0.977
                       LowPhrase       26.20      (1.9%)       26.20      (1.5%)   -0.0% (  -3% -    3%) 0.990
                         Respell       73.45      (1.1%)       73.50      (1.5%)    0.1% (  -2% -    2%) 0.914
                          Fuzzy2      119.32      (0.4%)      119.64      (0.5%)    0.3% (   0% -    1%) 0.182
               HighTermMonthSort     5878.05      (1.9%)     5897.37      (2.7%)    0.3% (  -4% -    5%) 0.764
                 CountAndHighMed      121.92      (2.9%)      122.35      (3.2%)    0.4% (  -5% -    6%) 0.809
                      HighPhrase       46.45      (3.4%)       46.62      (2.1%)    0.4% (  -4% -    6%) 0.776
                          Fuzzy1      104.63      (0.7%)      105.18      (0.6%)    0.5% (   0% -    1%) 0.105
                       MedPhrase       27.38      (4.0%)       27.55      (2.2%)    0.6% (  -5% -    7%) 0.692
                         Prefix3      227.82      (3.7%)      229.47      (2.7%)    0.7% (  -5% -    7%) 0.633
                       CountTerm    20661.05      (2.5%)    20826.02      (2.3%)    0.8% (  -3% -    5%) 0.476
                CountAndHighHigh       40.20      (2.6%)       40.78      (3.4%)    1.4% (  -4% -    7%) 0.313
                  CountOrHighMed       86.48     (14.9%)       88.87     (17.9%)    2.8% ( -26% -   41%) 0.721
                 CountOrHighHigh       55.70     (15.0%)       57.27     (18.0%)    2.8% ( -26% -   42%) 0.719
                     CountPhrase        3.32      (7.6%)        3.45     (10.2%)    3.9% ( -12% -   23%) 0.356
                      AndHighLow      567.28      (3.7%)      742.59      (4.6%)   30.9% (  21% -   40%) 0.000
                      AndHighMed      115.23      (2.8%)      161.49      (4.9%)   40.1% (  31% -   49%) 0.000
                     AndHighHigh       32.62      (4.8%)       47.72      (4.8%)   46.3% (  34% -   58%) 0.000

I did a diff -r between my baseline and candidate and saw the code changes from this PR as expected.

benwtrent

++

jpountz · 2023-09-25T11:36:21Z

FWIW I ran the benchmark from https://tantivy-search.github.io/bench/ and also observed a speedup on conjunctions, so I think that the speedup is indeed real.

…rer. (#12382) This implements a specialized `BlockMaxConjunctionBulkScorer`, which is really the same as `BlockMaxConjunctionScorer`, but as a `BulkScorer` instead of a `Scorer`. Also it doesn't support two-phase iterators in order to focus on the common case when queries, such as term queries, do not have two-phase iterators. If a clause has a two-phase iterator, it will keep running as a `BlockMaxConjunctionScorer` wrapped in a `DefaultBulkScorer`.

jpountz · 2023-09-29T08:04:26Z

This gave a good speedup to AndHighHigh on nightlies: +15%, but AndHighMed had a small drop: -1.5%. It still looks positive overall as it's making the slow query (AndHighHigh, 22 QPS) faster and the fast query (AndHighMed, 51 QPS) slightly slower but I'm still a bit puzzled why I'm seeing such different numbers on my local benchmark and on nightlies.

hossman · 2023-10-03T01:39:09Z

git bisect has identified f2bd0bbcdd38cd3c681a9d302bdb856f1a62208d as the cause of a recent jenkins failure in TestBlockMaxConjunction.testRandom that reproduces reliably for me locally on main

Example of failure...

org.apache.lucene.search.TestBlockMaxConjunction > testRandom FAILED
    java.lang.AssertionError: Hit 0 docnumbers don't match
    Hits length1=1      length2=1
    hit=0: doc4=9.615059 shardIndex=-1,  doc1215=9.615059 shardIndex=-1
    for query:+foo:9 +foo:10 +foo:11 +foo:12 +foo:13
        at __randomizedtesting.SeedInfo.seed([C738B747E3320853:B57492485252BE20]:0)
        at org.junit.Assert.fail(Assert.java:89)
        at org.apache.lucene.tests.search.CheckHits.checkEqual(CheckHits.java:229)
        at org.apache.lucene.tests.search.CheckHits.doCheckTopScores(CheckHits.java:709)
        at org.apache.lucene.tests.search.CheckHits.checkTopScores(CheckHits.java:694)
        at org.apache.lucene.search.TestBlockMaxConjunction.testRandom(TestBlockMaxConjunction.java:81)
...
  2> NOTE: reproduce with: gradlew test --tests TestBlockMaxConjunction.testRandom -Dtests.seed=C738B747E3320853 -Dtests.multiplier=2 -Dtests.locale=or -Dtests.timezone=Australia/Tasmania -Dtests.asserts=true -Dtests.file.encoding=UTF-8

git bisect log...

$ git bisect log
# bad: [1dd05c89b0836531d367d2692ea5eae7d54b78fd] Add missing create github release step to release wizard (#12607)
# good: [d62ca4a01f3693e0c6043a48080b33d03fdee8b4] add missing changelog entry for #12498
git bisect start '1dd05c89b0836531d367d2692ea5eae7d54b78fd' 'd62ca4a01f3693e0c6043a48080b33d03fdee8b4'
# good: [51ade888f3274ea42ed4beb2bf000d7f922de4c7] Update wrong PR number in CHANGES.txt
git bisect good 51ade888f3274ea42ed4beb2bf000d7f922de4c7
# bad: [ce464c7d6d20f49c2fe29126fcf400ee1cfeb112] Fix test failure.
git bisect bad ce464c7d6d20f49c2fe29126fcf400ee1cfeb112
# good: [3deead0ed32494d7159c0023dcc86c218c43f4eb] Remove deprecated IndexSearcher#getExecutor method (#12580)
git bisect good 3deead0ed32494d7159c0023dcc86c218c43f4eb
# good: [d48913a957392e2746b489fe5aef77a21250e4b4] Allow reading / writing binary stored fields as DataInput (#12581)
git bisect good d48913a957392e2746b489fe5aef77a21250e4b4
# bad: [483d28853a03aa57e727f0639032918e725a7032] Move CHANGES entry to correct version.
git bisect bad 483d28853a03aa57e727f0639032918e725a7032
# bad: [f2bd0bbcdd38cd3c681a9d302bdb856f1a62208d] Run top-level conjunctions of term queries with a specialized BulkScorer. (#12382)
git bisect bad f2bd0bbcdd38cd3c681a9d302bdb856f1a62208d
# first bad commit: [f2bd0bbcdd38cd3c681a9d302bdb856f1a62208d] Run top-level conjunctions of term queries with a specialized BulkScorer. (#12382)

The week ending on 2023-09-15, TestBlockMaxConjunction.testRandom had a roughly ~2% jenkins failure rate per week -- i believe the first known failures of this test? In the past 7 days (rolling window) 17 of 746 jenkins runs have failed. I have not looked into the failures of the other jenkins builds to confirm if the tes failure messages are identical.

EDIT: Updated misleading final paragraph because i realized i had misread the calendar

jpountz · 2023-10-03T06:54:57Z

Thanks Hoss! I had missed this failure, it looks like a real one. I'm looking.

jpountz · 2023-10-03T09:38:00Z

I just pushed a fix: 3f81f2f.

PR apache#12382 added a bulk scorer for top-k hits on conjunctions that yielded a significant speedup (annotation [FP](http://people.apache.org/~mikemccand/lucenebench/AndHighHigh.html)). This change proposes a similar change for exhaustive collection of conjunctive queries, e.g. for counting, faceting, etc.

PR #12382 added a bulk scorer for top-k hits on conjunctions that yielded a significant speedup (annotation [FP](http://people.apache.org/~mikemccand/lucenebench/AndHighHigh.html)). This change proposes a similar change for exhaustive collection of conjunctive queries, e.g. for counting, faceting, etc.

jpountz added this to the 9.8.0 milestone Jun 22, 2023

jpountz added 2 commits June 22, 2023 18:50

CHANGES

ef80886

Fix.

da9968f

jpountz marked this pull request as draft June 22, 2023 17:17

Compute scores on the fly.

70b5f61

jpountz closed this Jul 8, 2023

jpountz added 4 commits September 18, 2023 14:53

Merge branch 'main' into specialized_conjunction_bulk_scorer

e93ffa3

fix compilation

6a2fd38

fixes

8e44bb4

Merge branch 'main' into specialized_conjunction_bulk_scorer

ab89bf4

jpountz reopened this Sep 21, 2023

jpountz marked this pull request as ready for review September 21, 2023 13:25

jpountz mentioned this pull request Sep 21, 2023

Window-at-a-time scoring for conjunctions. #12564

Closed

jpountz modified the milestones: 9.8.0, 9.9.0 Sep 21, 2023

Move CHANGES to 9.9.

68401ce

tidy

b6f61ac

benwtrent reviewed Sep 21, 2023

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jpountz added 2 commits September 21, 2023 16:19

Propertly propagate top-level scoring clause.

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@benwtrent's feedback

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benwtrent approved these changes Sep 21, 2023

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jpountz merged commit f2bd0bb into apache:main Sep 25, 2023
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jpountz deleted the specialized_conjunction_bulk_scorer branch September 25, 2023 11:36

jpountz mentioned this pull request Oct 24, 2023

Add a specialized bulk scorer for regular conjunctions. #12719

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Run top-level conjunctions of term queries with a specialized BulkScorer. #12382

Run top-level conjunctions of term queries with a specialized BulkScorer. #12382

jpountz commented Jun 22, 2023 •

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jpountz commented Oct 3, 2023

jpountz commented Oct 3, 2023

Run top-level conjunctions of term queries with a specialized BulkScorer. #12382

Run top-level conjunctions of term queries with a specialized BulkScorer. #12382

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