LUCENE-10346: Specially treat SingletonSortedNumericDocValues in FastTaxonomyFacetCounts#countAll()

[gf2121]

CPU profile often tells SingletonSortedNumericDocValues#nextDoc() is using a high percentage of CPU when running luceneutil, but the nextDoc() of dense cases should be rather simple. So I suspect that it is too many layers of abstraction that cause the stress of JVM. Unwraping it to NumericDocvalues shows around 30% speed up.

                            TaskQPS baseline      StdDevQPS my_modified_version      StdDev                Pct diff p-value
            HighTermTitleBDVSort      132.24     (20.6%)      125.67      (9.9%)   -5.0% ( -29% -   32%) 0.330
                         LowTerm     1424.13      (3.2%)     1381.34      (4.4%)   -3.0% ( -10% -    4%) 0.014
                   OrHighNotHigh      707.82      (3.3%)      687.49      (6.0%)   -2.9% ( -11% -    6%) 0.062
                      TermDTSort      155.32     (10.9%)      151.02     (10.2%)   -2.8% ( -21% -   20%) 0.406
                    OrNotHighMed      618.46      (3.7%)      602.65      (4.4%)   -2.6% ( -10% -    5%) 0.047
                          Fuzzy1       76.22      (5.3%)       74.71      (6.6%)   -2.0% ( -13% -   10%) 0.293
               HighTermMonthSort      174.89     (10.4%)      171.45     (10.6%)   -2.0% ( -20% -   21%) 0.554
                    OrHighNotMed      776.08      (4.9%)      761.70      (7.8%)   -1.9% ( -13% -   11%) 0.367
           HighTermDayOfYearSort       56.23     (10.7%)       55.26     (10.9%)   -1.7% ( -21% -   22%) 0.615
                         MedTerm     1449.48      (3.7%)     1425.87      (5.1%)   -1.6% ( -10% -    7%) 0.250
                   OrNotHighHigh      687.92      (4.9%)      677.06      (5.5%)   -1.6% ( -11% -    9%) 0.339
                    OrHighNotLow      742.99      (4.7%)      732.23      (5.9%)   -1.4% ( -11% -    9%) 0.390
                    OrNotHighLow      789.37      (2.7%)      778.80      (4.7%)   -1.3% (  -8% -    6%) 0.270
                      HighPhrase       75.84      (2.2%)       75.14      (3.0%)   -0.9% (  -6% -    4%) 0.269
                HighSloppyPhrase       20.71      (5.9%)       20.56      (5.2%)   -0.7% ( -11% -   11%) 0.678
                          IntNRQ      106.38     (18.4%)      105.67     (18.2%)   -0.7% ( -31% -   44%) 0.908
                       OrHighMed       45.10      (1.5%)       44.83      (1.8%)   -0.6% (  -3% -    2%) 0.261
                     MedSpanNear      192.49      (2.5%)      191.51      (3.5%)   -0.5% (  -6% -    5%) 0.593
                       OrHighLow      489.82      (5.5%)      487.79      (5.7%)   -0.4% ( -11% -   11%) 0.815
                 MedSloppyPhrase       27.33      (2.9%)       27.22      (2.3%)   -0.4% (  -5% -    5%) 0.623
                       MedPhrase      208.94      (2.9%)      208.09      (3.7%)   -0.4% (  -6% -    6%) 0.696
                         Respell       71.84      (2.4%)       71.55      (2.4%)   -0.4% (  -5% -    4%) 0.600
                      OrHighHigh       36.26      (1.3%)       36.13      (1.1%)   -0.4% (  -2% -    2%) 0.344
           BrowseMonthSSDVFacets       15.95      (2.7%)       15.90      (2.5%)   -0.4% (  -5% -    5%) 0.672
                      AndHighMed       85.83      (2.2%)       85.53      (2.7%)   -0.3% (  -5% -    4%) 0.658
                         Prefix3      123.15      (2.6%)      122.74      (2.5%)   -0.3% (  -5% -    4%) 0.678
                          Fuzzy2       76.41      (4.7%)       76.23      (4.2%)   -0.2% (  -8% -    9%) 0.867
       BrowseDayOfYearSSDVFacets       14.52      (2.4%)       14.49      (2.2%)   -0.2% (  -4% -    4%) 0.747
             MedIntervalsOrdered       56.39      (4.2%)       56.27      (4.1%)   -0.2% (  -8% -    8%) 0.871
            HighIntervalsOrdered        9.29      (4.7%)        9.27      (4.4%)   -0.2% (  -8% -    9%) 0.896
         AndHighMedDayTaxoFacets      119.76      (2.5%)      119.53      (2.9%)   -0.2% (  -5% -    5%) 0.831
                    HighSpanNear       20.89      (2.0%)       20.85      (2.3%)   -0.2% (  -4% -    4%) 0.803
             LowIntervalsOrdered       45.51      (4.9%)       45.47      (4.8%)   -0.1% (  -9% -   10%) 0.952
                       LowPhrase       64.17      (2.6%)       64.14      (2.6%)   -0.1% (  -5% -    5%) 0.951
                     LowSpanNear      104.45      (2.2%)      104.41      (1.9%)   -0.0% (  -4% -    4%) 0.959
                        Wildcard      103.83      (2.8%)      103.80      (2.8%)   -0.0% (  -5% -    5%) 0.970
                     AndHighHigh       42.33      (2.6%)       42.33      (2.4%)   -0.0% (  -4% -    5%) 0.991
     BrowseRandomLabelSSDVFacets       10.62      (2.5%)       10.62      (1.8%)    0.0% (  -4% -    4%) 0.981
        AndHighHighDayTaxoFacets       29.75      (2.3%)       29.76      (2.7%)    0.1% (  -4% -    5%) 0.949
            MedTermDayTaxoFacets       26.56      (3.0%)       26.58      (2.5%)    0.1% (  -5% -    5%) 0.945
                      AndHighLow     1012.26      (4.5%)     1013.62      (4.3%)    0.1% (  -8% -    9%) 0.923
                 LowSloppyPhrase       78.82      (6.8%)       79.03      (6.0%)    0.3% ( -11% -   14%) 0.897
                        PKLookup      204.09      (3.0%)      204.82      (2.9%)    0.4% (  -5% -    6%) 0.703
          OrHighMedDayTaxoFacets       14.53      (3.4%)       14.59      (2.7%)    0.4% (  -5% -    6%) 0.694
                        HighTerm     1607.26      (5.2%)     1623.99      (5.6%)    1.0% (  -9% -   12%) 0.543
     BrowseRandomLabelTaxoFacets       11.93      (6.9%)       15.52      (2.5%)   30.1% (  19% -   42%) 0.000
            BrowseDateTaxoFacets       13.46      (9.0%)       18.28      (3.6%)   35.8% (  21% -   53%) 0.000
       BrowseDayOfYearTaxoFacets       13.59      (9.1%)       18.53      (3.6%)   36.3% (  21% -   53%) 0.000
           BrowseMonthTaxoFacets       13.93     (10.9%)       19.70     (14.9%)   41.4% (  14% -   75%) 0.000

Baseline

PERCENT       CPU SAMPLES   STACK
3.85%         12316         org.apache.lucene.facet.sortedset.SortedSetDocValuesFacetCounts#countOneSegment()
3.78%         12076         org.apache.lucene.util.packed.DirectReader$DirectPackedReader20#get()
3.72%         11905         org.apache.lucene.index.SingletonSortedNumericDocValues#nextDoc()
2.88%         9199          org.apache.lucene.queries.intervals.OrderedIntervalsSource$OrderedIntervalIterator#nextInterval()
2.31%         7380          org.apache.lucene.facet.taxonomy.FastTaxonomyFacetCounts#countAll()
2.27%         7270          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$20#ordValue()
2.25%         7211          org.apache.lucene.facet.taxonomy.IntTaxonomyFacets#increment()
2.23%         7139          org.apache.lucene.index.SingletonSortedNumericDocValues#nextValue()
1.88%         6006          java.nio.Buffer#checkIndex()
1.86%         5965          jdk.internal.misc.Unsafe#convEndian()
1.85%         5916          org.apache.lucene.util.packed.DirectReader$DirectPackedReader4#get()
1.72%         5491          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$EverythingEnum#nextPosition()
1.49%         4780          java.nio.DirectByteBuffer#ix()
1.42%         4548          java.nio.Buffer#scope()
1.40%         4465          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$4#longValue()
1.39%         4434          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$EverythingEnum#advance()
1.33%         4254          org.apache.lucene.store.ByteBufferGuard#ensureValid()
1.32%         4219          org.apache.lucene.util.packed.DirectReader$DirectPackedReader12#get()
1.28%         4109          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$20#nextDoc()
1.28%         4089          jdk.internal.misc.ScopedMemoryAccess#getByteInternal()
1.16%         3709          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$BlockImpactsPostingsEnum#advance()
1.10%         3517          org.apache.lucene.store.ByteBufferGuard#getInt()
1.07%         3427          org.apache.lucene.codecs.lucene90.Lucene90NormsProducer$3#longValue()
0.98%         3149          org.apache.lucene.search.ConjunctionDISI#doNext()
0.98%         3120          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader#findFirstGreater()
0.93%         2969          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$3#longValue()
0.92%         2927          org.apache.lucene.store.ByteBufferGuard#getByte()
0.88%         2828          com.carrotsearch.hppc.IntIntHashMap#indexOf()
0.82%         2635          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$BlockImpactsDocsEnum#advance()
0.82%         2633          org.apache.lucene.search.similarities.BM25Similarity$BM25Scorer#score()

Candidate

PERCENT       CPU SAMPLES   STACK
4.15%         12823         org.apache.lucene.util.packed.DirectReader$DirectPackedReader20#get()
3.94%         12186         org.apache.lucene.facet.sortedset.SortedSetDocValuesFacetCounts#countOneSegment()
3.32%         10266         org.apache.lucene.facet.taxonomy.FastTaxonomyFacetCounts#countAll()
2.98%         9208          org.apache.lucene.queries.intervals.OrderedIntervalsSource$OrderedIntervalIterator#nextInterval()
2.38%         7351          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$20#ordValue()
2.07%         6386          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$DenseNumericDocValues#nextDoc()
1.85%         5723          org.apache.lucene.facet.taxonomy.IntTaxonomyFacets#increment()
1.81%         5600          jdk.internal.misc.Unsafe#convEndian()
1.81%         5588          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$EverythingEnum#nextPosition()
1.75%         5409          java.nio.Buffer#checkIndex()
1.72%         5310          org.apache.lucene.util.packed.DirectReader$DirectPackedReader4#get()
1.50%         4631          java.nio.Buffer#scope()
1.44%         4437          jdk.internal.misc.ScopedMemoryAccess#getByteInternal()
1.43%         4408          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$EverythingEnum#advance()
1.39%         4297          java.nio.DirectByteBuffer#ix()
1.39%         4280          org.apache.lucene.util.packed.DirectReader$DirectPackedReader12#get()
1.33%         4111          org.apache.lucene.store.ByteBufferGuard#ensureValid()
1.31%         4052          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$20#nextDoc()
1.29%         3974          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$4#longValue()
1.22%         3761          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$BlockImpactsPostingsEnum#advance()
1.13%         3502          org.apache.lucene.codecs.lucene90.Lucene90NormsProducer$3#longValue()
1.04%         3219          org.apache.lucene.search.ConjunctionDISI#doNext()
1.00%         3099          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader#findFirstGreater()
0.99%         3067          org.apache.lucene.codecs.lucene90.Lucene90DocValuesProducer$3#longValue()
0.99%         3052          org.apache.lucene.store.ByteBufferGuard#getInt()
0.89%         2762          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$BlockImpactsDocsEnum#advance()
0.87%         2690          org.apache.lucene.search.similarities.BM25Similarity$BM25Scorer#score()
0.86%         2663          org.apache.lucene.store.ByteBufferGuard#getByte()
0.80%         2476          org.apache.lucene.codecs.lucene90.ForUtil#expand8()
0.78%         2420          org.apache.lucene.codecs.lucene90.Lucene90PostingsReader$EverythingEnum#skipPositions()

[rmuir]

very interesting (and simple contained) find. cc @gsmiller @mikemccand , I think this is an easy win? Thank you @gf2121 !

[rmuir]

This actually puts the taxo facets as running faster than SSDV facets? I wonder if the same optimization is missing in SSDV facets countall? Or perhaps there is a more complex explanation? Anyway, +1 to this change regardless, just wondering if we miss to optimize the single-valued situation for SSDV facets?

[gf2121]

Thanks @rmuir for so quick reply! Happy New Year :)

just wondering if we miss to optimize the single-valued situation for SSDV facets?

Thanks for remiding! I find we have already introduced the similar optimization for SSDV in #255

[gsmiller]

Great find! For what it's worth, this was overlooked when specializing SSDV in #255 because it was still using binary doc values at the time. When I switched over to numeric doc values, it looks like I overlooked adding this specialization. Thanks for the improvement!