硬體描述：
model name : Intel(R) Xeon(R) CPU E5-2640 0 @ 2.50GHz
cpu core : 4
cache size : 15360 KB
OS : Linux 64bit
JDK : 1.7.0_21-b11
Disruptor 3.2.1：
ringBufferSize : 1024
producerType : ProducerType.MULTI
WaitStrategy : BlockingWaitStrategy
測試代碼（dtest.zip common-disruptor）：
| 代碼如下 |
複製代碼 |
package org.chinasb.test;
import java.util.concurrent.CountDownLatch;
import org.chinasb.common.disruptor.Event;
import org.chinasb.common.disruptor.dispatch.Dispatcher;
import org.chinasb.common.disruptor.dispatch.RingbufferDispatcher;
public class Test {
static long LOGIC_LOOP = 0;
static long COST = 0;
static int NUM = 5000000;
public static void main(String[] args) {
boolean multithread = false;
int bufferSize = 1024;
if (args.length > 0) {
if (args.length > 0) {
NUM = Integer.parseInt(args[0]);
}
if (args.length > 1) {
multithread = Boolean.parseBoolean(args[1]);
}
if (args.length > 2) {
bufferSize = Integer.parseInt(args[2]);
}
if (args.length > 3) {
LOGIC_LOOP = Long.parseLong(args[3]);
}
}
final Dispatcher dispatcher = new RingbufferDispatcher(multithread, "任務執行器", bufferSize);
long start = System.nanoTime();
final CountDownLatch countDownLatch = new CountDownLatch(NUM);
final int coreSize = Runtime.getRuntime().availableProcessors();
for (int i = 0; i < coreSize; i++) {
new Thread(new Runnable() {
@Override
public void run() {
for (int i = 0; i < NUM / coreSize; i++) {
dispatcher.dispatch(Event.wrap(new Runnable() {
@Override
public void run() {
// logic
long start = System.nanoTime();
for (long i = 0; i < LOGIC_LOOP; i++) {}
double elapsed = (System.nanoTime() - start) / 1000.0;
COST+=elapsed;
countDownLatch.countDown();
}
}));
}
}
}).start();
}
try {
countDownLatch.await();
double elapsed = (System.nanoTime() - start) / 1000000.0;
long throughput = (long) (NUM / (elapsed / 1000.0));
System.out.println("throughput: " + throughput + "/sec in " + (long) elapsed + "ms");
System.out.println("average logic: " + COST / NUM + "us");
} catch (InterruptedException e) {
e.printStackTrace();
}
dispatcher.shutdown();
}
} |
測試1描述：多生產者模式下單個消費者事件消費能力（無耗時商務邏輯，僅測試事件分發吞吐能力），每種類型操作分別測試3次。
測試1結果：
測試2描述：多生產者模式下單個消費者事件消費能力（有耗時商務邏輯，每個事件平均耗時1.8ms，測試事件分發處理吞吐能力），每種類型操作分別測試3次。
測試2結果：
總結：測試1情境中當事件數目量超過1000w，其事件分發吞吐能力穩定在300w左右，測試2情境中在兩種不同事件數目量類型的分發處事過程中，其事件分發處理吞吐能力穩定在540左右。
按照這個測試結果，如果在遊戲中引入Disruptor替代傳統的BlockQueue處理訊息事件，承載數量應該可以提高3倍左右。
