src/jmh/java/io/reactivex/rxjava4/parallel/ParallelPerf.java - 4.x - githubmirror/RxJava

src/jmh/java/io/reactivex/rxjava4/parallel/ParallelPerf.java
103 строки3 KB
David Karnok
4.x: Streamable + takeUntil + groupBy + refactor + helpers (#8215)
05 июл 2026, 01:45
05 июл 2026, 01:45580b39c
/*
 * Copyright (c) 2016-present, RxJava Contributors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
 * compliance with the License. You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software distributed under the License is
 * distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See
 * the License for the specific language governing permissions and limitations under the License.
 */

package io.reactivex.rxjava4.parallel;

import java.util.Arrays;
import java.util.concurrent.Flow.Publisher;
import java.util.concurrent.TimeUnit;

import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.infra.Blackhole;

import io.reactivex.rxjava4.core.*;
import io.reactivex.rxjava4.core.config.StandardConcurrentBufferedConfig;
import io.reactivex.rxjava4.functions.Function;
import io.reactivex.rxjava4.schedulers.Schedulers;

@SuppressWarnings("exports")
@BenchmarkMode(Mode.Throughput)
@Warmup(iterations = 5)
@Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
@Fork(value = 1, jvmArgsAppend = { "-XX:MaxInlineLevel=20" })
@OutputTimeUnit(TimeUnit.SECONDS)
@State(Scope.Thread)
public class ParallelPerf implements Function<Integer, Integer> {

    @Param({"10000"})
    public int count;

    @Param({"1", "10", "100", "1000", "10000"})
    public int compute;

    @Param({"1", "2", "3", "4"})
    public int parallelism;

    Flowable<Integer> flatMap;

    Flowable<Integer> groupBy;

    Flowable<Integer> parallel;

    @Override
    public Integer apply(Integer t) {
        Blackhole.consumeCPU(compute);
        return t;
    }

    @Setup
    public void setup() {

        final int cpu = parallelism;

        Integer[] ints = new Integer[count];
        Arrays.fill(ints, 777);

        Flowable<Integer> source = Flowable.fromArray(ints);

        flatMap = source.flatMap((Function<Integer, Publisher<Integer>>) v -> Flowable.just(v).subscribeOn(Schedulers.computation())
                .map(ParallelPerf.this), new StandardConcurrentBufferedConfig(cpu));

        groupBy = source.groupBy(new Function<Integer, Integer>() {
            int i;
            @Override
            public Integer apply(Integer v) {
                return (i++) % cpu;
            }
        })
        .flatMap((Function<GroupedFlowable<Integer, Integer>, Publisher<Integer>>) g -> g.observeOn(Schedulers.computation()).map(ParallelPerf.this));

        parallel = source.parallel(cpu).runOn(Schedulers.computation()).map(this).sequential();
    }

    void subscribe(Flowable<Integer> f, Blackhole bh) {
        PerfAsyncConsumer consumer = new PerfAsyncConsumer(bh);
        f.subscribe(consumer);
        consumer.await(count);
    }

    @Benchmark
    public void flatMap(Blackhole bh) {
        subscribe(flatMap, bh);
    }

    @Benchmark
    public void groupBy(Blackhole bh) {
        subscribe(groupBy, bh);
    }

    @Benchmark
    public void parallel(Blackhole bh) {
        subscribe(parallel, bh);
    }
}