單機壓測工具JMH

JMH Java準測試工具套件

什么是JMH

官網

http://openjdk.java.net/projects/code-tools/jmh/

創建JMH測試

1.創建Maven項目，添加依賴

<?xml version="1.0" encoding="UTF-8"?><project xmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><properties><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><encoding>UTF-8</encoding><java.version>1.8</java.version><maven.compiler.source>1.8</maven.compiler.source><maven.compiler.target>1.8</maven.compiler.target></properties><groupId>mashibing.com</groupId><artifactId>HelloJMH2</artifactId><version>1.0-SNAPSHOT</version><dependencies><!-- https://mvnrepository.com/artifact/org.openjdk.jmh/jmh-core --><dependency><groupId>org.openjdk.jmh</groupId><artifactId>jmh-core</artifactId><version>1.21</version></dependency><!-- https://mvnrepository.com/artifact/org.openjdk.jmh/jmh-generator-annprocess --><dependency><groupId>org.openjdk.jmh</groupId><artifactId>jmh-generator-annprocess</artifactId><version>1.21</version><scope>test</scope></dependency></dependencies></project>

2.idea安裝JMH插件 JMH plugin v1.0.3

3.由于用到了注解，打開運行程序注解配置

compiler -> Annotation Processors -> Enable Annotation Processing

4.定義需要測試類PS (ParallelStream)

package com.mashibing.jmh;import java.util.ArrayList; import java.util.List; import java.util.Random;public class PS {static List<Integer> nums = new ArrayList<>();static {Random r = new Random();for (int i = 0; i < 10000; i++) nums.add(1000000 + r.nextInt(1000000));}static void foreach() {nums.forEach(v->isPrime(v));}static void parallel() {nums.parallelStream().forEach(PS::isPrime);}static boolean isPrime(int num) {for(int i=2; i<=num/2; i++) {if(num % i == 0) return false;}return true;} }

5.寫單元測試

這個測試類一定要在 test package下面

package com.mashibing.jmh;import org.openjdk.jmh.annotations.*;import static org.junit.jupiter.api.Assertions.*;public class PSTest {@Benchmark@Warmup(iterations = 1, time = 3)@Fork(5)@BenchmarkMode(Mode.Throughput)@Measurement(iterations = 1, time = 3)public void testForEach() {PS.foreach();} }

6.運行測試類，如果遇到下面的錯誤：

ERROR: org.openjdk.jmh.runner.RunnerException: ERROR: Exception while trying to acquire the JMH lock (C:\WINDOWS\/jmh.lock): C:\WINDOWS\jmh.lock (拒絕訪問。), exiting. Use -Djmh.ignoreLock=true to forcefully continue.at org.openjdk.jmh.runner.Runner.run(Runner.java:216)at org.openjdk.jmh.Main.main(Main.java:71)

這個錯誤是因為JMH運行需要訪問系統的TMP目錄，解決辦法是：

打開RunConfiguration -> Environment Variables -> include system environment viables

7.閱讀測試報告

JMH中的基本概念

Warmup
預熱，由于JVM中對于特定代碼會存在優化（本地化），預熱對于測試結果很重要

Mesurement
總共執行多少次測試

Timeout

Threads
線程數，由fork指定

Benchmark mode
基準測試的模式

Benchmark
測試哪一段代碼

Next

官方樣例：
http://hg.openjdk.java.net/code-tools/jmh/file/tip/jmh-samples/src/main/java/org/openjdk/jmh/samples/

---

Disruptor單機最快MQ

內存里的高效隊列

介紹

主頁：http://lmax-exchange.github.io/disruptor/

源碼：https://github.com/LMAX-Exchange/disruptor

GettingStarted: https://github.com/LMAX-Exchange/disruptor/wiki/Getting-Started

api: http://lmax-exchange.github.io/disruptor/docs/index.html

maven: https://mvnrepository.com/artifact/com.lmax/disruptor

Disruptor的特點

對比ConcurrentLinkedQueue : 鏈表實現

JDK中沒有ConcurrentArrayQueue

Disruptor是數組實現的

無鎖，高并發，使用環形Buffer，直接覆蓋（不用清除）舊的數據，降低GC頻率

實現了基于事件的生產者消費者模式（觀察者模式）

RingBuffer

環形隊列

RingBuffer的序號，指向下一個可用的元素

采用數組實現，沒有首尾指針

對比ConcurrentLinkedQueue，用數組實現的速度更快

假如長度為8，當添加到第12個元素的時候在哪個序號上呢？用12%8決定

當Buffer被填滿的時候到底是覆蓋還是等待，由Producer決定

長度設為2的n次冪，利于二進制計算，例如：12%8 = 12 & (8 - 1) pos = num & (size -1)

Disruptor開發步驟

定義Event - 隊列中需要處理的元素

定義Event工廠，用于填充隊列

這里牽扯到效率問題：disruptor初始化的時候，會調用Event工廠，對ringBuffer進行內存的提前分配

GC產頻率會降低

定義EventHandler（消費者），處理容器中的元素

事件發布模板

long sequence = ringBuffer.next(); // Grab the next sequence try {LongEvent event = ringBuffer.get(sequence); // Get the entry in the Disruptor// for the sequenceevent.set(8888L); // Fill with data } finally {ringBuffer.publish(sequence); }

使用EventTranslator發布事件

//===============================================================EventTranslator<LongEvent> translator1 = new EventTranslator<LongEvent>() {@Overridepublic void translateTo(LongEvent event, long sequence) {event.set(8888L);}};ringBuffer.publishEvent(translator1);//===============================================================EventTranslatorOneArg<LongEvent, Long> translator2 = new EventTranslatorOneArg<LongEvent, Long>() {@Overridepublic void translateTo(LongEvent event, long sequence, Long l) {event.set(l);}};ringBuffer.publishEvent(translator2, 7777L);//===============================================================EventTranslatorTwoArg<LongEvent, Long, Long> translator3 = new EventTranslatorTwoArg<LongEvent, Long, Long>() {@Overridepublic void translateTo(LongEvent event, long sequence, Long l1, Long l2) {event.set(l1 + l2);}};ringBuffer.publishEvent(translator3, 10000L, 10000L);//===============================================================EventTranslatorThreeArg<LongEvent, Long, Long, Long> translator4 = new EventTranslatorThreeArg<LongEvent, Long, Long, Long>() {@Overridepublic void translateTo(LongEvent event, long sequence, Long l1, Long l2, Long l3) {event.set(l1 + l2 + l3);}};ringBuffer.publishEvent(translator4, 10000L, 10000L, 1000L);//===============================================================EventTranslatorVararg<LongEvent> translator5 = new EventTranslatorVararg<LongEvent>() {@Overridepublic void translateTo(LongEvent event, long sequence, Object... objects) {long result = 0;for(Object o : objects) {long l = (Long)o;result += l;}event.set(result);}};ringBuffer.publishEvent(translator5, 10000L, 10000L, 10000L, 10000L);

使用Lamda表達式

package com.mashibing.disruptor;import com.lmax.disruptor.RingBuffer; import com.lmax.disruptor.dsl.Disruptor; import com.lmax.disruptor.util.DaemonThreadFactory;public class Main03 {public static void main(String[] args) throws Exception{// Specify the size of the ring buffer, must be power of 2.int bufferSize = 1024;// Construct the DisruptorDisruptor<LongEvent> disruptor = new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);// Connect the handlerdisruptor.handleEventsWith((event, sequence, endOfBatch) -> System.out.println("Event: " + event));// Start the Disruptor, starts all threads runningdisruptor.start();// Get the ring buffer from the Disruptor to be used for publishing.RingBuffer<LongEvent> ringBuffer = disruptor.getRingBuffer();ringBuffer.publishEvent((event, sequence) -> event.set(10000L));System.in.read();} }

ProducerType生產者線程模式

ProducerType有兩種模式 Producer.MULTI和Producer.SINGLE

默認是MULTI，表示在多線程模式下產生sequence

如果確認是單線程生產者，那么可以指定SINGLE，效率會提升

如果是多個生產者（多線程），但模式指定為SINGLE，會出什么問題呢？

等待策略

1，(常用）BlockingWaitStrategy：通過線程阻塞的方式，等待生產者喚醒，被喚醒后，再循環檢查依賴的sequence是否已經消費。

2，BusySpinWaitStrategy：線程一直自旋等待，可能比較耗cpu

3，LiteBlockingWaitStrategy：線程阻塞等待生產者喚醒，與BlockingWaitStrategy相比，區別在signalNeeded.getAndSet,如果兩個線程同時訪問一個訪問waitfor,一個訪問signalAll時，可以減少lock加鎖次數.

4，LiteTimeoutBlockingWaitStrategy：與LiteBlockingWaitStrategy相比，設置了阻塞時間，超過時間后拋異常。

5，PhasedBackoffWaitStrategy：根據時間參數和傳入的等待策略來決定使用哪種等待策略

6，TimeoutBlockingWaitStrategy：相對于BlockingWaitStrategy來說，設置了等待時間，超過后拋異常

7，（常用）YieldingWaitStrategy：嘗試100次，然后Thread.yield()讓出cpu

8，（常用）SleepingWaitStrategy : sleep

消費者異常處理

默認：disruptor.setDefaultExceptionHandler()

覆蓋：disruptor.handleExceptionFor().with()

總結

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