/*
* Copyright 2014 Ben Manes. All Rights Reserved.
*
* 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 com.github.benmanes.caffeine.cache;
import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;
import java.util.function.Function;
import org.openjdk.jmh.annotations.Benchmark;
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.Threads;
import org.rapidoid.cache.Caching;
import org.rapidoid.lambda.Mapper;
import com.google.common.cache.CacheBuilder;
import com.google.common.cache.CacheLoader;
import com.yahoo.ycsb.generator.NumberGenerator;
import com.yahoo.ycsb.generator.ScrambledZipfianGenerator;
/**
* @author ben.manes@gmail.com (Ben Manes)
*/
@State(Scope.Benchmark)
public class ComputeBenchmark {
static final int SIZE = (2 << 14);
static final int MASK = SIZE - 1;
static final int ITEMS = SIZE / 3;
static final Integer COMPUTE_KEY = SIZE / 2;
static final Mapper<Integer, Boolean> mapper = any -> Boolean.TRUE;
static final Function<Integer, Boolean> mappingFunction = any -> Boolean.TRUE;
static final CacheLoader<Integer, Boolean> cacheLoader = CacheLoader.from(key -> Boolean.TRUE);
@Param({"ConcurrentHashMap", "Caffeine", "Guava", "Rapidoid"})
String computeType;
Function<Integer, Boolean> benchmarkFunction;
Integer[] ints;
@State(Scope.Thread)
public static class ThreadState {
static final Random random = new Random();
int index = random.nextInt();
}
public ComputeBenchmark() {
ints = new Integer[SIZE];
NumberGenerator generator = new ScrambledZipfianGenerator(ITEMS);
for (int i = 0; i < SIZE; i++) {
ints[i] = generator.nextValue().intValue();
}
}
@Setup
public void setup() {
if (computeType.equals("ConcurrentHashMap")) {
setupConcurrentHashMap();
} else if (computeType.equals("Caffeine")) {
setupCaffeine();
} else if (computeType.equals("Guava")) {
setupGuava();
} else if (computeType.equals("Rapidoid")) {
setupRapidoid();
} else {
throw new AssertionError("Unknown computingType: " + computeType);
}
Arrays.stream(ints).forEach(benchmarkFunction::apply);
}
@Benchmark @Threads(32)
public Boolean compute_sameKey(ThreadState threadState) {
return benchmarkFunction.apply(COMPUTE_KEY);
}
@Benchmark @Threads(32)
public Boolean compute_spread(ThreadState threadState) {
return benchmarkFunction.apply(ints[threadState.index++ & MASK]);
}
private void setupConcurrentHashMap() {
ConcurrentMap<Integer, Boolean> map = new ConcurrentHashMap<>();
benchmarkFunction = key -> map.computeIfAbsent(key, mappingFunction);
}
private void setupCaffeine() {
Cache<Integer, Boolean> cache = Caffeine.newBuilder().build();
benchmarkFunction = key -> cache.get(key, mappingFunction);
}
private void setupGuava() {
com.google.common.cache.LoadingCache<Integer, Boolean> cache =
CacheBuilder.newBuilder().concurrencyLevel(64).build(cacheLoader);
benchmarkFunction = cache::getUnchecked;
}
private void setupRapidoid() {
org.rapidoid.cache.Cache<Integer, Boolean> cache = Caching.of(mapper).build();
benchmarkFunction = cache::get;
}
}