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ParallelPerf.java
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114 lines (91 loc) · 3.38 KB
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/*
* 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.TimeUnit;
import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.infra.Blackhole;
import static java.util.concurrent.Flow.*;
import io.reactivex.rxjava4.core.*;
import io.reactivex.rxjava4.core.config.FlatMapConfig;
import io.reactivex.rxjava4.flowables.GroupedFlowable;
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(new Function<Integer, Publisher<Integer>>() {
@Override
public Publisher<Integer> apply(Integer v) {
return Flowable.just(v).subscribeOn(Schedulers.computation())
.map(ParallelPerf.this);
}
}, new FlatMapConfig(cpu));
groupBy = source.groupBy(new Function<Integer, Integer>() {
int i;
@Override
public Integer apply(Integer v) {
return (i++) % cpu;
}
})
.flatMap(new Function<GroupedFlowable<Integer, Integer>, Publisher<Integer>>() {
@Override
public Publisher<Integer> apply(GroupedFlowable<Integer, Integer> g) {
return 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);
}
}