使用JMH實際測試EhCache、GuavaCache和Caffeine之間的效能

測試程式碼

EhCache

@BenchmarkMode({Mode.AverageTime})
@OutputTimeUnit(TimeUnit.MICROSECONDS)
@Warmup(iterations=3, time = 5, timeUnit = TimeUnit.MILLISECONDS)
@Measurement(iterations=5,time = 1,timeUnit = TimeUnit.SECONDS)
@Threads(8)
@Fork(3)
@State(Scope.Thread)
 
public class EhCacheTest {
    private static CacheManager cacheManager = CacheManagerBuilder.newCacheManagerBuilder()
            .build(true);

    private static Cache<String, String> cache = cacheManager.createCache("myCache",
            CacheConfigurationBuilder.newCacheConfigurationBuilder(String.
 
class, String.class,
                    ResourcePoolsBuilder.newResourcePoolsBuilder().heap(100, MemoryUnit.MB))
                    .withExpiry(ExpiryPolicyBuilder.timeToLiveExpiration(Duration.ofSeconds(1L))).build());

    static {
        cache.put("test","test");
    }
    @Benchmark
    public void
 
 test(){
        cache.get("test");
    }
}

Guava Cache


@BenchmarkMode({Mode.AverageTime})
@OutputTimeUnit(TimeUnit.MICROSECONDS)
@Warmup(iterations=3, time = 5, timeUnit = TimeUnit.MILLISECONDS)
@Measurement(iterations=5,time = 1,timeUnit = TimeUnit.SECONDS)
@Threads(8)
@Fork(3)
@State(Scope.Thread)
public class GuavaTest {
    private static Cache<String,String> cache = CacheBuilder.newBuilder()
            .maximumSize(100)
            .expireAfterWrite(1,TimeUnit.SECONDS)
            .build();

    static {
        cache.put("test","test");
    }

    @Benchmark
    public void test(){
        cache.getIfPresent("test");
    }
}

Caffeine


@BenchmarkMode({Mode.AverageTime})
@OutputTimeUnit(TimeUnit.MICROSECONDS)
@Warmup(iterations=3, time = 5, timeUnit = TimeUnit.MILLISECONDS)
@Measurement(iterations=5,time = 1,timeUnit = TimeUnit.SECONDS)
@Threads(8)
@Fork(3)
@State(Scope.Thread)
public class CaffeineTest {
    private static Cache<String,String> cache = Caffeine.newBuilder()
            .maximumSize(100)
            .expireAfterWrite(1,TimeUnit.SECONDS)
            .build();

    static {
        cache.put("test","test");
    }

    @Benchmark
    public void test(){
        cache.getIfPresent("test");
    }
}

說明，實際測試程式碼共有六種情況（其實還有別的情況，不加任何引數使Caffeine使用UnboundedLocalCache，效能應該還會改變，大家如果有興趣可以自己嘗試）

直接放結果

• 奇特的地方
  • 在加過期時間的情況下三個快取方案的效能均有所提升
  • Guava不加過期時間的情況下高併發會OOM
  • EhCache在加過期時間的情況下竟然比Guava的效能要好
  • Caffeine讀比寫的效能要高很多

總結

• Guava使用jdk的Queue記錄快取的寫讀情況，導致OOM；而Caffeine使用Disruptor的RingBuffer資料結構記錄
• Caffeine對寫的所有執行緒共用一個RingBuffer；而對讀的每個執行緒維護一個RingBuffer
• 使用Caffeine是你不會後悔的選擇
• 可參考Caffeine