ES|QL deserves a new hash table #98749
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,163 @@ | ||
| /* | ||
| * 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.compute.operator; | ||
|
|
||
| import org.apache.lucene.util.BytesRef; | ||
| import org.elasticsearch.common.breaker.NoopCircuitBreaker; | ||
| import org.elasticsearch.common.settings.Settings; | ||
| import org.elasticsearch.common.util.BigArrays; | ||
| import org.elasticsearch.common.util.BytesRefHash; | ||
| import org.elasticsearch.common.util.LongHash; | ||
| import org.elasticsearch.common.util.LongLongHash; | ||
| import org.elasticsearch.common.util.LongObjectPagedHashMap; | ||
| import org.elasticsearch.common.util.PageCacheRecycler; | ||
| import org.elasticsearch.compute.aggregation.blockhash.Ordinator64; | ||
| 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.OperationsPerInvocation; | ||
| 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.Warmup; | ||
|
|
||
| import java.util.concurrent.TimeUnit; | ||
| import java.util.stream.IntStream; | ||
| import java.util.stream.LongStream; | ||
|
|
||
| @Warmup(iterations = 5) | ||
| @Measurement(iterations = 7) | ||
| @BenchmarkMode(Mode.AverageTime) | ||
| @OutputTimeUnit(TimeUnit.NANOSECONDS) | ||
| @State(Scope.Thread) | ||
| @Fork(value = 1, jvmArgsAppend = { "--enable-preview", "--add-modules", "jdk.incubator.vector" }) | ||
| public class HashBenchmark { | ||
| static { | ||
| // Smoke test all the expected values and force loading subclasses more like prod | ||
| try { | ||
| for (String unique : HashBenchmark.class.getField("unique").getAnnotationsByType(Param.class)[0].value()) { | ||
| HashBenchmark bench = new HashBenchmark(); | ||
| bench.unique = Integer.parseInt(unique); | ||
| bench.initTestData(); | ||
| bench.longHash(); | ||
| bench.bytesRefHash(); | ||
| bench.longLongHash(); | ||
| bench.longObjectHash(); | ||
| bench.ordinator(); | ||
| bench.ordinatorArray(); | ||
| } | ||
| } catch (NoSuchFieldException e) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
|
|
||
| private static final int ITERATIONS = 10_000_000; | ||
|
|
||
| @Param({ "5", "1000", "10000", "100000", "1000000" }) | ||
| public int unique; | ||
|
|
||
| private long[] testLongs; | ||
| private BytesRef[] testBytes; | ||
| private int[] targetInts; | ||
| private long[] targetLongs; | ||
| private Object[] targetObject; | ||
|
|
||
| @Setup | ||
| public void initTestData() { | ||
| testLongs = LongStream.range(0, ITERATIONS).map(l -> l % unique).toArray(); | ||
| BytesRef[] uniqueBytes = IntStream.range(0, unique).mapToObj(i -> new BytesRef(Integer.toString(i))).toArray(BytesRef[]::new); | ||
| testBytes = IntStream.range(0, ITERATIONS).mapToObj(i -> uniqueBytes[i % unique]).toArray(BytesRef[]::new); | ||
| targetInts = new int[ITERATIONS]; | ||
| targetLongs = new long[ITERATIONS]; | ||
| targetObject = new Object[ITERATIONS]; | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void longHash() { | ||
| LongHash hash = new LongHash(16, BigArrays.NON_RECYCLING_INSTANCE); | ||
| for (int i = 0; i < testLongs.length; i++) { | ||
| targetLongs[i] = hash.add(testLongs[i]); | ||
| } | ||
| if (hash.size() != unique) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void bytesRefHash() { | ||
| BytesRefHash hash = new BytesRefHash(16, BigArrays.NON_RECYCLING_INSTANCE); | ||
| for (int i = 0; i < testLongs.length; i++) { | ||
| targetLongs[i] = hash.add(testBytes[i]); | ||
| } | ||
| if (hash.size() != unique) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void longLongHash() { | ||
| LongLongHash hash = new LongLongHash(16, BigArrays.NON_RECYCLING_INSTANCE); | ||
| for (int i = 0; i < testLongs.length; i++) { | ||
| targetLongs[i] = hash.add(testLongs[i], testLongs[i]); | ||
| } | ||
| if (hash.size() != unique) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void longObjectHash() { | ||
| LongObjectPagedHashMap<Object> hash = new LongObjectPagedHashMap<>(16, BigArrays.NON_RECYCLING_INSTANCE); | ||
| Object o = new Object(); | ||
| for (int i = 0; i < testLongs.length; i++) { | ||
| targetObject[i] = hash.put(testLongs[i], o); | ||
| } | ||
| if (hash.size() != unique) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void ordinator() { | ||
| Ordinator64 hash = new Ordinator64( | ||
| new PageCacheRecycler(Settings.EMPTY), | ||
| new NoopCircuitBreaker("bench"), | ||
| new Ordinator64.IdSpace() | ||
| ); | ||
| for (int i = 0; i < testLongs.length; i++) { | ||
| targetInts[i] = hash.add(testLongs[i]); | ||
| } | ||
| if (hash.currentSize() != unique) { | ||
| throw new AssertionError("expected " + hash.currentSize() + " to be " + unique); | ||
| } | ||
| } | ||
|
|
||
| @Benchmark | ||
| @OperationsPerInvocation(ITERATIONS) | ||
| public void ordinatorArray() { | ||
| Ordinator64 hash = new Ordinator64( | ||
| new PageCacheRecycler(Settings.EMPTY), | ||
| new NoopCircuitBreaker("bench"), | ||
| new Ordinator64.IdSpace() | ||
| ); | ||
| hash.add(testLongs, targetInts, testLongs.length); | ||
| if (hash.currentSize() != unique) { | ||
| throw new AssertionError(); | ||
| } | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I've updated this to work with the new hash, but it doesn't produce the lovely performance numbers - yet. Partly that's because we're not integrating with the hash super well - the vector case needs to consume the array somehow. Or something similar. But that feels like something for another time.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
The other reason this doesn't show the performance bump we expect is because we don't enable all of the other aggregations - and because we don't aggregate much larger groups. Either way, this benchmark is much better at showing the performance of aggs, not the groupings. At least not yet.