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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,4 +1,4 @@ | ||
| BWC_VERSION: | ||
| - "7.17.20" | ||
| - "8.13.2" | ||
| - "7.17.21" | ||
| - "8.13.3" | ||
| - "8.14.0" |
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188 changes: 188 additions & 0 deletions
188
benchmarks/src/main/java/org/elasticsearch/benchmark/vector/VectorScorerBenchmark.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,188 @@ | ||
| /* | ||
| * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one | ||
| * or more contributor license agreements. Licensed under the Elastic License | ||
| * 2.0 and the Server Side Public License, v 1; you may not use this file except | ||
| * in compliance with, at your election, the Elastic License 2.0 or the Server | ||
| * Side Public License, v 1. | ||
| */ | ||
|
|
||
| package org.elasticsearch.benchmark.vector; | ||
|
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||
| import org.apache.lucene.index.VectorSimilarityFunction; | ||
| import org.apache.lucene.store.Directory; | ||
| import org.apache.lucene.store.IOContext; | ||
| import org.apache.lucene.store.IndexInput; | ||
| import org.apache.lucene.store.IndexOutput; | ||
| import org.apache.lucene.store.MMapDirectory; | ||
| import org.apache.lucene.util.quantization.ScalarQuantizedVectorSimilarity; | ||
| import org.elasticsearch.common.logging.LogConfigurator; | ||
| import org.elasticsearch.core.IOUtils; | ||
| import org.elasticsearch.vec.VectorScorer; | ||
| import org.elasticsearch.vec.VectorScorerFactory; | ||
| import org.openjdk.jmh.annotations.Benchmark; | ||
| import org.openjdk.jmh.annotations.BenchmarkMode; | ||
| import org.openjdk.jmh.annotations.Fork; | ||
| import org.openjdk.jmh.annotations.Measurement; | ||
| import org.openjdk.jmh.annotations.Mode; | ||
| import org.openjdk.jmh.annotations.OutputTimeUnit; | ||
| import org.openjdk.jmh.annotations.Param; | ||
| import org.openjdk.jmh.annotations.Scope; | ||
| import org.openjdk.jmh.annotations.Setup; | ||
| import org.openjdk.jmh.annotations.State; | ||
| import org.openjdk.jmh.annotations.TearDown; | ||
| import org.openjdk.jmh.annotations.Warmup; | ||
|
|
||
| import java.io.IOException; | ||
| import java.nio.file.Files; | ||
| import java.util.concurrent.ThreadLocalRandom; | ||
| import java.util.concurrent.TimeUnit; | ||
|
|
||
| import static org.elasticsearch.vec.VectorSimilarityType.DOT_PRODUCT; | ||
| import static org.elasticsearch.vec.VectorSimilarityType.EUCLIDEAN; | ||
|
|
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| @Fork(value = 1, jvmArgsPrepend = { "--add-modules=jdk.incubator.vector" }) | ||
| @Warmup(iterations = 3, time = 3) | ||
| @Measurement(iterations = 5, time = 3) | ||
| @BenchmarkMode(Mode.Throughput) | ||
| @OutputTimeUnit(TimeUnit.MICROSECONDS) | ||
| @State(Scope.Thread) | ||
| /** | ||
| * Benchmark that compares various scalar quantized vector similarity function | ||
| * implementations;: scalar, lucene's panama-ized, and Elasticsearch's native. | ||
| * Run with ./gradlew -p benchmarks run --args 'VectorScorerBenchmark' | ||
| */ | ||
| public class VectorScorerBenchmark { | ||
|
|
||
| static { | ||
| LogConfigurator.configureESLogging(); // native access requires logging to be initialized | ||
| } | ||
|
|
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| @Param({ "96", "768", "1024" }) | ||
| int dims; | ||
| int size = 2; // there are only two vectors to compare | ||
|
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| Directory dir; | ||
| IndexInput in; | ||
| VectorScorerFactory factory; | ||
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| byte[] vec1; | ||
| byte[] vec2; | ||
| float vec1Offset; | ||
| float vec2Offset; | ||
| float scoreCorrectionConstant; | ||
|
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| ScalarQuantizedVectorSimilarity luceneDotScorer; | ||
| ScalarQuantizedVectorSimilarity luceneSqrScorer; | ||
| VectorScorer nativeDotScorer; | ||
| VectorScorer nativeSqrScorer; | ||
|
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||
| @Setup | ||
| public void setup() throws IOException { | ||
| var optionalVectorScorerFactory = VectorScorerFactory.instance(); | ||
| if (optionalVectorScorerFactory.isEmpty()) { | ||
| String msg = "JDK=[" | ||
| + Runtime.version() | ||
| + "], os.name=[" | ||
| + System.getProperty("os.name") | ||
| + "], os.arch=[" | ||
| + System.getProperty("os.arch") | ||
| + "]"; | ||
| throw new AssertionError("Vector scorer factory not present. Cannot run the benchmark. " + msg); | ||
| } | ||
| factory = optionalVectorScorerFactory.get(); | ||
| scoreCorrectionConstant = 1f; | ||
| vec1 = new byte[dims]; | ||
| vec2 = new byte[dims]; | ||
|
|
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| ThreadLocalRandom.current().nextBytes(vec1); | ||
| ThreadLocalRandom.current().nextBytes(vec2); | ||
| vec1Offset = ThreadLocalRandom.current().nextFloat(); | ||
| vec2Offset = ThreadLocalRandom.current().nextFloat(); | ||
|
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| dir = new MMapDirectory(Files.createTempDirectory("nativeScalarQuantBench")); | ||
| try (IndexOutput out = dir.createOutput("vector.data", IOContext.DEFAULT)) { | ||
| out.writeBytes(vec1, 0, vec1.length); | ||
| out.writeInt(Float.floatToIntBits(vec1Offset)); | ||
| out.writeBytes(vec2, 0, vec2.length); | ||
| out.writeInt(Float.floatToIntBits(vec2Offset)); | ||
| } | ||
| in = dir.openInput("vector.data", IOContext.DEFAULT); | ||
|
|
||
| luceneDotScorer = ScalarQuantizedVectorSimilarity.fromVectorSimilarity( | ||
| VectorSimilarityFunction.DOT_PRODUCT, | ||
| scoreCorrectionConstant | ||
| ); | ||
| luceneSqrScorer = ScalarQuantizedVectorSimilarity.fromVectorSimilarity(VectorSimilarityFunction.EUCLIDEAN, scoreCorrectionConstant); | ||
| nativeDotScorer = factory.getScalarQuantizedVectorScorer(dims, size, scoreCorrectionConstant, DOT_PRODUCT, in).get(); | ||
| nativeSqrScorer = factory.getScalarQuantizedVectorScorer(dims, size, scoreCorrectionConstant, EUCLIDEAN, in).get(); | ||
|
|
||
| // sanity | ||
| var f1 = dotProductLucene(); | ||
| var f2 = dotProductNative(); | ||
| var f3 = dotProductScalar(); | ||
| if (f1 != f2) { | ||
| throw new AssertionError("lucene[" + f1 + "] != " + "native[" + f2 + "]"); | ||
| } | ||
| if (f1 != f3) { | ||
| throw new AssertionError("lucene[" + f1 + "] != " + "scalar[" + f3 + "]"); | ||
| } | ||
| // square distance | ||
| f1 = squareDistanceLucene(); | ||
| f2 = squareDistanceNative(); | ||
| f3 = squareDistanceScalar(); | ||
| if (f1 != f2) { | ||
| throw new AssertionError("lucene[" + f1 + "] != " + "native[" + f2 + "]"); | ||
| } | ||
| if (f1 != f3) { | ||
| throw new AssertionError("lucene[" + f1 + "] != " + "scalar[" + f3 + "]"); | ||
| } | ||
| } | ||
|
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| @TearDown | ||
| public void teardown() throws IOException { | ||
| IOUtils.close(dir, in); | ||
| } | ||
|
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| @Benchmark | ||
| public float dotProductLucene() { | ||
| return luceneDotScorer.score(vec1, vec1Offset, vec2, vec2Offset); | ||
| } | ||
|
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| @Benchmark | ||
| public float dotProductNative() throws IOException { | ||
| return nativeDotScorer.score(0, 1); | ||
| } | ||
|
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| @Benchmark | ||
| public float dotProductScalar() { | ||
| int dotProduct = 0; | ||
| for (int i = 0; i < vec1.length; i++) { | ||
| dotProduct += vec1[i] * vec2[i]; | ||
| } | ||
| float adjustedDistance = dotProduct * scoreCorrectionConstant + vec1Offset + vec2Offset; | ||
| return (1 + adjustedDistance) / 2; | ||
| } | ||
|
|
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| // -- square distance | ||
|
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| @Benchmark | ||
| public float squareDistanceLucene() { | ||
| return luceneSqrScorer.score(vec1, vec1Offset, vec2, vec2Offset); | ||
| } | ||
|
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| @Benchmark | ||
| public float squareDistanceNative() throws IOException { | ||
| return nativeSqrScorer.score(0, 1); | ||
| } | ||
|
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| @Benchmark | ||
| public float squareDistanceScalar() { | ||
| int squareDistance = 0; | ||
| for (int i = 0; i < vec1.length; i++) { | ||
| int diff = vec1[i] - vec2[i]; | ||
| squareDistance += diff * diff; | ||
| } | ||
| float adjustedDistance = squareDistance * scoreCorrectionConstant; | ||
| return 1 / (1f + adjustedDistance); | ||
| } | ||
| } |
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