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Java性能调优笔记
Java性能调优笔记调优步骤：衡量系统现状、设定调优目标、寻找性能瓶颈、性能调优、衡量是否到达目标(如果未到达目标，需重新寻找性能瓶颈）、性能调优结束。寻找性能瓶颈性能瓶颈的表象：资源消耗过多、外部处理系统的性能不足、资源消耗不多但程序的响应速度却仍达不到要求。资源消耗：CPU、文件IO、网络IO、内存。外部处理系统的性能不足：所调用的其他系统提供的功能或数据库操作的响应速度不够。资源消耗不多但程序的响应速度却仍达不到要求：程序代码运行效率不够高、未充分使用资源、程序结构不合理。CPU消耗分析CPU主要用于中断、内核、用户进程的任务处理，优先级为中断>内核>用户进程。上下文切换：每个线程分配一定的执行时间，当到达执行时间、线程中有IO阻塞或高优先级线程要执行时，将切换执行的线程。在切换时要存储目前线程的执行状态，并恢复要执行的线程的状态。对于Java应用，典型的是在进行文件IO操作、网络IO操作、锁等待、线程Sleep时，当前线程会进入阻塞或休眠状态，从而触发上下文切换，上下文切换过多会造成内核占据较多的CPU的使用。运行队列：每个CPU核都维护一个可运行的线程队列。系统的load主要由CPU的运行队列来决定。运行队列值越大，就意味着线程会要消耗越长的时间才能执行完成。利用率：CPU在用户进程、内核、中断处理、IO等待、空闲，这五个部分使用百分比。文件IO消耗分析Linux在操作文件时，将数据放入文件缓存区，直到内存不够或系统要释放内存给用户进程使用。所以通常情况下只有写文件和第一次读取文件时会产生真正的文件IO。对于Java应用，造成文件IO消耗高主要是多个线程需要进行大量内容写入（例如频繁的日志写入）的动作、磁盘设备本身的处理速度慢、文件系统慢、操作的文件本身已经很大。网络IO消耗分析对于分布式Java应用，网卡中断是不是均衡分配到各CPU(cat/proc/interrupts查看)。内存消耗分析（-Xms和-Xmx设为相同的值，避免运行期JVM堆内存要不断申请内存）对于Java应用，内存的消耗主要在Java堆内存上，只有创建线程和使用Direct ByteBuffer才会操作JVM堆外的内存。JVM内存消耗过多会导致GC执行频繁，CPU消耗增加，应用线程的执行速度严重下降，甚至造成OutOfMemoryError，最终导致Java进程退出。JVM堆外的内存swap的消耗、物理内存的消耗、JVM内存的消耗。 程序执行慢原因分析锁竞争激烈：很多线程竞争互斥资源，但资源有限， 造成其他线程都处于等待状态。未充分使用硬件资源：线程操作被串行化。数据量增长：单表数据量太大（如1个亿）造成数据库读写速度大幅下降（操作此表）。 调优 JVM调优（最关键参数为：-Xms -Xmx -Xmn -XX:SurvivorRatio -XX:MaxTenuringThreshold） 代大小调优：避免新生代大小设置过小、避免新生代大小设置过大、避免Survivor设置过小或过大、合理设置新生代存活周期。-Xmn 调整新生代大小，新生代越大通常也意味着更多对象会在minor GC阶段被回收，但可能有可能造成旧生代大小，造成频繁触发Full GC，甚至是OutOfMemoryError。-XX:SurvivorRatio调整Eden区与Survivor区的大小，Eden 区越大通常也意味着minor GC发生频率越低，但可能有可能造成Survivor区太小，导致对象minor GC后就直接进入旧生代，从而更频繁触发Full GC。 GC策略的调优：CMS GC多数动作是和应用并发进行的，确实可以减小GC动作给应用造成的暂停时间。对于Web应用非常需要一个对应用造成暂停时间短的GC，再加上Web应用 的瓶颈都不在CPU上，在G1还不够成熟的情况下，CMS GC是不错的选择。（如果系统不是CPU密集型，且从新生代进入旧生代的大部分对象是可以回收的，那么采用CMS GC可以更好地在旧生代满之前完成对象的回收，更大程度降低Full GC发生的可能） 在调整了内存管理方面的参数后应通过-XX:PrintGCDetails、-XX:+PrintGCTimeStamps、 -XX:+PrintGCApplicationStoppedTime以及jstat或visualvm等方式观察调整后的GC状况。出内存管理以外的其他方面的调优参数：-XX:CompileThreshold、-XX:+UseFastAccessorMethods、 -XX:+UseBaiasedLocking。 程序调优 CPU消耗严重的解决方法 CPU us高的解决方法：CPU us 高的原因主要是执行线程不需要任何挂起动作，且一直执行，导致CPU 没有机会去调度执行其他的线程。调优方案： 增加Thread.sleep，以释放CPU 的执行权，降低CPU 的消耗。以损失单次执行性能为代价的，但由于其降低了CPU 的消耗，对于多线程的应用而言，反而提高了总体的平均性能。（在实际的Java应用中类似场景， 对于这种场景最佳方式是改为采用wait/notify机制）对于其他类似循环次数过多、正则、计算等造成CPU us过高的状况， 则需要结合业务调优。对于GC频繁，则需要通过JVM调优或程序调优，降低GC的执行次数。 CPU sy高的解决方法：CPU sy 高的原因主要是线程的运行状态要经常切换，对于这种情况，常见的一种优化方法是减少线程数。调优方案： 将线程数降低这种调优过后有可能会造成CPU us过高，所以合理设置线程数非常关键。 对于Java分布式应用，还有一种典型现象是应用中有较多的网络IO操作和确实需要一些锁竞争机制（如数据库连接池），但为了能够支撑搞得并发量，可采用协程（Coroutine）来支撑更高的并发量，避免并发量上涨后造成CPU sy消耗严重、系统load迅速上涨和系统性能下降。在Java中实现协程的框架有Kilim，Kilim执行一项任务创建Task，使用Task的暂停机制，而不是Thread，Kilim承担了线程调度以及上下切换动作，Task相对于原生Thread而言就轻量级多了，且能更好利用CPU。Kilim带来的是线程使用率的提升，但同时由于要在JVM堆中保存Task上下文信息，因此在采用Kilim的情况下要消耗更多的内存。（目前JDK 7中也有一个支持协程方式的实现，另外基于JVM的Scala的Actor也可用于在Java使用协程） 文件IO消耗严重的解决方法从程序的角度而言，造成文件IO消耗严重的原因主要是多个线程在写进行大量的数据到同一文件，导致文件很快变得很大，从而写入速度越来越慢，并造成各线程激烈争抢文件锁。 常用调优方法：异步写文件批量读写限流限制文件大小 网络IO消耗严重的解决方法从程序的角度而言，造成网络IO消耗严重的原因主要是同时需要发送或接收的包太多。 常用调优方法：限流，限流通常是限制发送packet的频率，从而在网络IO消耗可接受的情况下来发送packget。 内存消耗严重的解决方法释放不必要的引用：代码持有了不需要的对象引用，造成这些对象无法被GC，从而占据了JVM堆内存。（使用ThreadLocal：注意在线程内动作执行完毕时，需执行ThreadLocal.set把对象清除，避免持有不必要的对象引用）使用对象缓存池：创建对象要消耗一定的CPU以及内存，使用对象缓存池一定程度上可降低JVM堆内存的使用。采用合理的缓存失效算法：如果放入太多对象在缓存池中，反而会造成内存的严重消耗， 同时由于缓存池一直对这些对象持有引用，从而造成Full GC增多，对于这种状况要合理控制缓存池的大小，避免缓存池的对象数量无限上涨。（经典的缓存失效算法来清除缓存池中的对象：FIFO、LRU、LFU等）合理使用SoftReference和WeekReference：SoftReference的对象会在内存不够用的时候回收，WeekReference的对象会在Full GC的时候回收。 资源消耗不多但程序执行慢的情况的解决方法 降低锁竞争： 多线多了，锁竞争的状况会比较明显，这时候线程很容易处于等待锁的状况，从而导致性能下降以及CPU sy上升。使用并发包中的类：大多数采用了lock-free、nonblocking算法。使用Treiber算法：基于CAS以及AtomicReference。使用Michael-Scott非阻塞队列算法：基于CAS以及AtomicReference，典型ConcurrentLindkedQueue。（基于CAS和AtomicReference来实现无阻塞是不错的选择，但值得注意的是，lock-free算法需不断的循环比较来保证资源的一致性的，对于冲突较多的应用场景而言，会带来更高的CPU消耗，因此不一定采用CAS实现无阻塞的就一定比采用lock方式的性能好。 还有一些无阻塞算法的改进：MCAS、WSTM等）尽可能少用锁：尽可能只对需要控制的资源做加锁操作（通常没有必要对整个方法加锁，尽可能让锁最小化，只对互斥及原子操作的地方加锁，加锁时尽可能以保护资源的最小化粒度为单位--如只对需要保护的资源加锁而不是this）。拆分锁：独占锁拆分为多把锁（读写锁拆分、类似ConcurrentHashMap中默认拆分为16把锁），很多程度上能提高读写的性能，但需要注意在采用拆分锁后，全局性质的操作会变得比较复杂（如ConcurrentHashMap中size操作）。（拆分锁太多也会造成副作用，如CPU消耗明显增加）去除读写操作的互斥：在修改时加锁，并复制对象进行修改，修改完毕后切换对象的引用，从而读取时则不加锁。这种称为CopyOnWrite，CopyOnWriteArrayList是典型实现，好处是可以明显提升读的性能，适合读多写少的场景， 但由于写操作每次都要复制一份对象，会消耗更多的内存。 充分利用硬件资源（CPU和内存）： 充分利用CPU在能并行处理的场景中未使用足够的线程（线程增加：CPU资源消耗可接受且不会带来激烈竞争锁的场景下）， 例如单线程的计算，可以拆分为多个线程分别计算，最后将结果合并，JDK 7中的fork-join框架。Amdahl定律公式：1/(F+(1-F)/N)。 充分利用内存数据的缓存、耗时资源的缓存（数据库连接创建、网络连接的创建等）、页面片段的缓存。毕竟内存的读取肯定远快于硬盘、网络的读取， 在内存消耗可接受、GC频率、以及系统结构（例如集群环境可能会带来缓存的同步）可接受情况下，应充分利用内存来缓存数据，提升系统的性能。 总结：好的调优策略是收益比（调优后提升的效果/调优改动所需付出的代价）最高的，通常来说简单的系统调优比较好做，因此尽量保持单机上应用的纯粹性， 这是大型系统的基本架构原则。调优的三大有效原则：充分而不过分使用硬件资源、合理调整JVM、合理使用JDK包。 学习参考资料：《分布式Java应用：基础与实践》 补充《分布式Java应用：基础与实践》一些代码样例： cpu----------------------------------- CpuNotUseEffectiveDemo[java] view plaincopy/** * */ package tune.program.cpu; import java.util.ArrayList; import java.util.List; import java.util.Random; /** * 未充分利用CPU：在能并行处理的场景中未使用足够的线程（线程增加：CPU资源消耗可接受且不会带来激烈竞争锁的场景下） * * @author yangwm Aug 25, 2010 9:54:50 AM */ public class CpuNotUseEffectiveDemo { private static int executeTimes = 10; private static int taskCount = 200; public static void main(String[] args) throws Exception { Task task = new Task(); for (int i = 0; i < taskCount; i++) { task.addTask(Integer.toString(i)); } long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); Thread thread = new Thread(task); thread.start(); thread.join(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) TaskCount Per Round( " + taskCount + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class Task implements Runnable { List tasks = new ArrayList(); Random random = new Random(); boolean exitFlag = false; public void addTask(String task) { List copyTasks = new ArrayList(tasks); copyTasks.add(task); tasks = copyTasks; } @Override public void run() { List runTasks = tasks; List removeTasks = new ArrayList(); for (String task : runTasks) { try { Thread.sleep(random.nextInt(10)); } catch (Exception e) { e.printStackTrace(); } removeTasks.add(task); } try { Thread.sleep(10); } catch (Exception e) { e.printStackTrace(); } } } } /* Round: 1 ...... Round: 10 Execute summary: Round( 10 ) TaskCount Per Round( 200 ) Execute Time ( 10687 ) ms */ CpuUseEffectiveDemo[java] view plaincopy/** * */ package tune.program.cpu; import java.util.ArrayList; import java.util.List; import java.util.Random; import java.util.concurrent.CountDownLatch; /** * 充分利用CPU：在能并行处理的场景中使用足够的线程（线程增加：CPU资源消耗可接受且不会带来激烈竞争锁的场景下） * * @author yangwm Aug 25, 2010 9:54:50 AM */ public class CpuUseEffectiveDemo { private static int executeTimes = 10; private static int taskCount = 200; private static final int TASK_THREADCOUNT = 16; private static CountDownLatch latch; public static void main(String[] args) throws Exception { Task[] tasks = new Task[TASK_THREADCOUNT]; for (int i = 0; i < TASK_THREADCOUNT; i++) { tasks[i] = new Task(); } for (int i = 0; i < taskCount; i++) { int mod = i % TASK_THREADCOUNT; tasks[mod].addTask(Integer.toString(i)); } long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); latch = new CountDownLatch(TASK_THREADCOUNT); for (int j = 0; j < TASK_THREADCOUNT; j++) { Thread thread = new Thread(tasks[j]); thread.start(); } latch.await(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) TaskCount Per Round( " + taskCount + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class Task implements Runnable { List tasks = new ArrayList(); Random random = new Random(); boolean exitFlag = false; public void addTask(String task) { List copyTasks = new ArrayList(tasks); copyTasks.add(task); tasks = copyTasks; } @Override public void run() { List runTasks = tasks; List removeTasks = new ArrayList(); for (String task : runTasks) { try { Thread.sleep(random.nextInt(10)); } catch (Exception e) { e.printStackTrace(); } removeTasks.add(task); } try { Thread.sleep(10); } catch (Exception e) { e.printStackTrace(); } latch.countDown(); } } } /* Round: 1 ...... Round: 10 Execute summary: Round( 10 ) TaskCount Per Round( 200 ) Execute Time ( 938 ) ms */ fileio------------------------------------------------------------------- IOWaitHighDemo[java] view plaincopy/** * */ package tune.program.fileio; import java.io.BufferedWriter; import java.io.File; import java.io.FileWriter; import java.util.Random; /** * 文件IO消耗严重的原因主要是多个线程在写进行大量的数据到同一文件， * 导致文件很快变得很大，从而写入速度越来越慢，并造成各线程激烈争抢文件锁。 * * @author yangwm Aug 21, 2010 9:48:34 PM */ public class IOWaitHighDemo { private String fileName = "iowait.log"; private static int threadCount = Runtime.getRuntime().availableProcessors(); private Random random = new Random(); public static void main(String[] args) throws Exception { if (args.length == 1) { threadCount = Integer.parseInt(args[1]); } IOWaitHighDemo demo = new IOWaitHighDemo(); demo.runTest(); } private void runTest() throws Exception { File file = new File(fileName); file.createNewFile(); for (int i = 0; i < threadCount; i++) { new Thread(new Task()).start(); } } class Task implements Runnable { @Override public void run() { while (true) { try { StringBuilder strBuilder = new StringBuilder("====begin====/n"); String threadName = Thread.currentThread().getName(); for (int i = 0; i < 100000; i++) { strBuilder.append(threadName); strBuilder.append("/n"); } strBuilder.append("====end====/n"); BufferedWriter writer = new BufferedWriter(new FileWriter(fileName, true)); writer.write(strBuilder.toString()); writer.close(); Thread.sleep(random.nextInt(10)); } catch (Exception e) { } } } } } /* C:/Documents and Settings/yangwm>jstack 2656 2010-08-21 23:24:17 Full thread dump Java HotSpot(TM) Client VM (17.0-b05 mixed mode): "DestroyJavaVM" prio=6 tid=0x00868c00 nid=0xde0 waiting on condition [0x00000000] java.lang.Thread.State: RUNNABLE "Thread-1" prio=6 tid=0x0ab9dc00 nid=0xb7c runnable [0x0b0bf000] java.lang.Thread.State: RUNNABLE at java.io.FileOutputStream.close0(Native Method) at java.io.FileOutputStream.close(FileOutputStream.java:336) at sun.nio.cs.StreamEncoder.implClose(StreamEncoder.java:320) at sun.nio.cs.StreamEncoder.close(StreamEncoder.java:149) - locked <0x034dd268> (a java.io.FileWriter) at java.io.OutputStreamWriter.close(OutputStreamWriter.java:233) at java.io.BufferedWriter.close(BufferedWriter.java:265) - locked <0x034dd268> (a java.io.FileWriter) at tune.IOWaitHighDemo$Task.run(IOWaitHighDemo.java:58) at java.lang.Thread.run(Thread.java:717) "Thread-0" prio=6 tid=0x0ab9d400 nid=0x80c runnable [0x0b06f000] java.lang.Thread.State: RUNNABLE at java.io.FileOutputStream.writeBytes(Native Method) at java.io.FileOutputStream.write(FileOutputStream.java:292) at sun.nio.cs.StreamEncoder.writeBytes(StreamEncoder.java:221) at sun.nio.cs.StreamEncoder.implWrite(StreamEncoder.java:282) at sun.nio.cs.StreamEncoder.write(StreamEncoder.java:125) - locked <0x034e1290> (a java.io.FileWriter) at java.io.OutputStreamWriter.write(OutputStreamWriter.java:207) at java.io.BufferedWriter.flushBuffer(BufferedWriter.java:128) - locked <0x034e1290> (a java.io.FileWriter) at java.io.BufferedWriter.write(BufferedWriter.java:229) - locked <0x034e1290> (a java.io.FileWriter) at java.io.Writer.write(Writer.java:157) at tune.IOWaitHighDemo$Task.run(IOWaitHighDemo.java:57) at java.lang.Thread.run(Thread.java:717) "Low Memory Detector" daemon prio=6 tid=0x0ab6f800 nid=0xfb0 runnable [0x00000000] java.lang.Thread.State: RUNNABLE "CompilerThread0" daemon prio=10 tid=0x0ab6c800 nid=0x5fc waiting on condition [0x00000000] java.lang.Thread.State: RUNNABLE "Attach Listener" daemon prio=10 tid=0x0ab67800 nid=0x6fc waiting on condition [0x00000000] java.lang.Thread.State: RUNNABLE "Signal Dispatcher" daemon prio=10 tid=0x0ab66800 nid=0x5a0 runnable [0x00000000] java.lang.Thread.State: RUNNABLE "Finalizer" daemon prio=8 tid=0x0ab54000 nid=0xe74 in Object.wait() [0x0ac8f000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) - waiting on <0x02f15d90> (a java.lang.ref.ReferenceQueue$Lock) at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135) - locked <0x02f15d90> (a java.lang.ref.ReferenceQueue$Lock) at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:151) at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:177) "Reference Handler" daemon prio=10 tid=0x0ab4f800 nid=0x8a4 in Object.wait() [0x0ac3f000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) - waiting on <0x02f15af8> (a java.lang.ref.Reference$Lock) at java.lang.Object.wait(Object.java:502) at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:133) - locked <0x02f15af8> (a java.lang.ref.Reference$Lock) "VM Thread" prio=10 tid=0x0ab4a800 nid=0x1d0 runnable "VM Periodic Task Thread" prio=10 tid=0x0ab7d400 nid=0x464 waiting on condition JNI global references: 693 C:/Documents and Settings/yangwm> */ LogControl[java] view plaincopy/** * */ package tune.program.fileio; import java.util.concurrent.atomic.AtomicInteger; /** * 日志控制：采用简单策略为统计一段时间内日志输出频率， 当超出这个频率时，一段时间内不再写log * * @author yangwm Aug 24, 2010 10:41:43 AM */ public class LogControl { public static void main(String[] args) { for (int i = 1; i <= 1000; i++) { if (LogControl.isLog()) { //logger.error(errorInfo, throwable); System.out.println("errorInfo " + i); } // if (i % 100 == 0) { try { Thread.sleep(1000); } catch (InterruptedException e) { e.printStackTrace(); } } } } private static final long INTERVAL = 1000; private static final long PUNISH_TIME = 5000; private static final int ERROR_THRESHOLD = 100; private static AtomicInteger count = new AtomicInteger(0); private static long beginTime; private static long punishTimeEnd; // 由于控制不用非常精确， 因此忽略此处的并发问题 public static boolean isLog() { //System.out.println(count.get() + ", " + beginTime + ", " + punishTimeEnd + ", " + System.currentTimeMillis()); // 不写日志阶段 if (punishTimeEnd > 0 && punishTimeEnd > System.currentTimeMillis()) { return false; } // 重新计数 if (count.getAndIncrement() == 0) { beginTime = System.currentTimeMillis(); return true; } else { // 已在计数 // 超过阀门值， 设置count为0并设置一段时间内不写日志 if (count.get() > ERROR_THRESHOLD) { count.set(0); punishTimeEnd = PUNISH_TIME + System.currentTimeMillis(); return false; } // 没超过阀门值， 且当前时间已超过计数周期，则重新计算 else if (System.currentTimeMillis() > (beginTime + INTERVAL)) { count.set(0); } return true; } } } /* errorInfo 1 errorInfo 2 ...... errorInfo 99 errorInfo 100 errorInfo 601 errorInfo 602 ...... errorInfo 699 errorInfo 700 */ memory------------------------------------------------------------------- MemoryHighDemo [java] view plaincopy/** * */ package tune.program.memory; import java.nio.ByteBuffer; /** * direct bytebuffer消耗的是jvm堆外的内存，但同样是基于GC方式来释放的。 * * @author yangwm Aug 21, 2010 9:40:18 PM */ public class MemoryHighDemo { public static void main(String[] args) throws Exception{ Thread.sleep(20000); System.out.println("read to create bytes,so jvm heap will be used"); byte[] bytes=new byte[128*1000*1000]; bytes[0]=1; bytes[1]=2; Thread.sleep(10000); System.out.println("read to allocate & put direct bytebuffer,no jvm heap should be used"); ByteBuffer buffer=ByteBuffer.allocateDirect(128*1024*1024); buffer.put(bytes); buffer.flip(); Thread.sleep(10000); System.out.println("ready to gc,jvm heap will be freed"); bytes=null; System.gc(); Thread.sleep(10000); System.out.println("read to get bytes,then jvm heap will be used"); byte[] resultbytes=new byte[128*1000*1000]; buffer.get(resultbytes); System.out.println("resultbytes[1] is: "+resultbytes[1]); Thread.sleep(10000); System.out.println("read to gc all"); buffer=null; resultbytes=null; System.gc(); Thread.sleep(10000); } } /* D:/study/tempProject/JavaLearn/classes>java -Xms140M -Xmx140M tune.MemoryHighDemo read to create bytes,so jvm heap will be used read to allocate & put direct bytebuffer,no jvm heap should be used ready to gc,jvm heap will be freed read to get bytes,then jvm heap will be used resultbytes[1] is: 2 read to gc all */ ObjectCachePool[java] view plaincopy/** * */ package tune.program.memory; import java.util.LinkedHashMap; import java.util.Map; import java.util.Set; /** * 采用合理的缓存失效算法: FIFO、LRU、LFU等 * * @author yangwm Aug 24, 2010 6:06:48 PM */ public class ObjectCachePool { public static void main(String[] args) { // FIFO_POLICY int size = 10; int policy = 1; ObjectCachePool objectCachePool = new ObjectCachePool(size, policy); for (int i = 1; i <= 15; i++) { objectCachePool.put(i, i); } for (int i = 15; i >= 1; i--) { objectCachePool.put(i, i); } System.out.println("size(" + size + "), policy(" + policy + ") FIFO "); for (Map.Entry entry : objectCachePool.entrySet()) { System.out.println(entry.getKey() + ", " + entry.getValue()); } // LRU_POLICY size = 10; policy = 2; objectCachePool = new ObjectCachePool(size, policy); for (int i = 1; i <= 15; i++) { objectCachePool.put(i, i); } for (int i = 15; i >= 1; i--) { objectCachePool.put(i, i); } System.out.println("size(" + size + "), policy(" + policy + ") LRU "); for (Map.Entry entry : objectCachePool.entrySet()) { System.out.println(entry.getKey() + ", " + entry.getValue()); } } private static final int FIFO_POLICY = 1; private static final int LRU_POLICY = 2; private static final int DEFAULT_SIZE = 10; private Map cacheObjects; public ObjectCachePool() { this(DEFAULT_SIZE); } public ObjectCachePool(int size) { this(size, FIFO_POLICY); } public ObjectCachePool(final int size, final int policy) { switch (policy) { case FIFO_POLICY: cacheObjects = new LinkedHashMap(size) { /** * */ private static final long serialVersionUID = 1L; protected boolean removeEldestEntry(Map.Entry eldest) { return size() > size; } }; break; case LRU_POLICY: cacheObjects = new LinkedHashMap(size, 0.75f, true) { /** * */ private static final long serialVersionUID = 1L; protected boolean removeEldestEntry(Map.Entry eldest) { return size() > size; } }; break; default: throw new IllegalArgumentException("Unknown policy: " + policy); } } public void put(K key, V value) { cacheObjects.put(key, value); } public void get(K key) { cacheObjects.get(key); } public void remove(K key) { cacheObjects.remove(key); } public void clear() { cacheObjects.clear(); } public Set> entrySet() { return cacheObjects.entrySet(); } } /* size(10), policy(1) FIFO 11, 11 12, 12 13, 13 14, 14 15, 15 5, 5 4, 4 3, 3 2, 2 1, 1 size(10), policy(2) LRU 10, 10 9, 9 8, 8 7, 7 6, 6 5, 5 4, 4 3, 3 2, 2 1, 1 */ ObjectPoolDemo[java] view plaincopy/** * */ package tune.program.memory; import java.util.HashMap; import java.util.Map; import java.util.concurrent.CountDownLatch; /** * 使用对象缓存池：创建对象要消耗一定的CPU以及内存，使用对象缓存池一定程度上可降低JVM堆内存的使用。 * * @author yangwm Aug 24, 2010 4:34:47 PM */ public class ObjectPoolDemo { private static int executeTimes = 10; private static int maxFactor = 10; private static int threadCount = 100; private static final int NOTUSE_OBJECTPOOL = 1; private static final int USE_OBJECTPOOL = 2; private static int runMode = NOTUSE_OBJECTPOOL; private static CountDownLatch latch = null; public static void main(String[] args) throws Exception { Task task = new Task(); long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); latch = new CountDownLatch(threadCount); for (int j = 0; j < threadCount; j++) { new Thread(task).start(); } latch.await(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) Thread Per Round( " + threadCount + " ) Object Factor ( " + maxFactor + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class Task implements Runnable { @Override public void run() { for (int j = 0; j < maxFactor; j++) { if (runMode == USE_OBJECTPOOL) { BigObjectPool.getInstance().getBigObject(j); } else { new BigObject(j); } } latch.countDown(); } } static class BigObjectPool { private static final BigObjectPool self = new BigObjectPool(); private final Map cacheObjects = new HashMap(); private BigObjectPool() { } public static BigObjectPool getInstance() { return self; } public BigObject getBigObject(int factor) { if (cacheObjects.containsKey(factor)) { return cacheObjects.get(factor); } else { BigObject object = new BigObject(factor); cacheObjects.put(factor, object); return object; } } } static class BigObject { private byte[] bytes = null; public BigObject(int factor) { bytes = new byte[(factor + 1) * 1024 * 1024]; } public byte[] getBytes() { return bytes; } } } /* -Xms128M -Xmx128M -Xmn64M , runMode is NOTUSE_OBJECTPOOL: Round: 1 ...... Execute summary: Round( 10 ) Thread Per Round( 100 ) Object Factor ( 10 ) Execute Time ( 50672 ) ms -Xms128M -Xmx128M -Xmn64M , runMode is USE_OBJECTPOOL: Round: 1 ...... Execute summary: Round( 10 ) Thread Per Round( 100 ) Object Factor ( 10 ) Execute Time ( 344 ) ms */ ThreadLocalDemo[java] view plaincopy/** * */ package tune.program.memory; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; /** * 释放不必要的引用：代码持有了不需要的对象引用，造成这些对象无法被GC，从而占据了JVM堆内存。 * （使用ThreadLocal：注意在线程内动作执行完毕时，需执行 ThreadLocal.set把对象清除，避免持有不必要的对象引用） * * @author yangwm Aug 24, 2010 11:29:59 AM */ public class ThreadLocalDemo { public static void main(String[] args) { ThreadLocalDemo demo = new ThreadLocalDemo(); demo.run(); } public void run() { ExecutorService executor = Executors.newFixedThreadPool(1); executor.execute(new Task()); System.gc(); } class Task implements Runnable { @Override public void run() { ThreadLocal localString = new ThreadLocal(); localString.set(new byte[1024 * 1024 * 30]); // 业务逻辑 //localString.set(null); // 释放不必要的引用 } } } concurrent----------------------------------------------------------------------- LockHotDemo[java] view plaincopy/** * */ package tune.program.concurrent; import java.util.Random; import java.util.concurrent.CountDownLatch; import java.util.concurrent.locks.Lock; import java.util.concurrent.locks.ReentrantLock; /** * 锁竞争的状况会比较明显，这时候线程很容易处于等待锁的状况，从而导致性能下降以及CPU sy上升 * * @author yangwm Aug 24, 2010 11:59:35 PM */ public class LockHotDemo { private static int executeTimes = 10; private static int threadCount = Runtime.getRuntime().availableProcessors() * 100; private static CountDownLatch latch = null; public static void main(String[] args) throws Exception { HandleTask task = new HandleTask(); long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); latch = new CountDownLatch(threadCount); for (int j = 0; j < threadCount; j++) { new Thread(task).start(); } latch.await(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) Thread Per Round( " + threadCount + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class HandleTask implements Runnable { private final Random random = new Random(); @Override public void run() { Handler.getInstance().handle(random.nextInt(10000)); latch.countDown(); } } static class Handler { private static final Handler self = new Handler(); private final Random random = new Random(); private final Lock lock = new ReentrantLock(); private Handler() { } public static Handler getInstance() { return self; } public void handle(int id) { try { lock.lock(); // execute sth try { Thread.sleep(random.nextInt(10)); } catch (Exception e) { e.printStackTrace(); } } finally { lock.unlock(); } } } } /* Round: 1 ...... Round: 10 Execute summary: Round( 10 ) Thread Per Round( 200 ) Execute Time ( 10625 ) ms */ ReduceLockHotDemo[java] view plaincopy/** * */ package tune.program.concurrent; import java.util.Random; import java.util.concurrent.CountDownLatch; import java.util.concurrent.locks.Lock; import java.util.concurrent.locks.ReentrantLock; /** * 尽可能少用锁：尽可能只对需要控制的资源做加锁操作 * * @author yangwm Aug 24, 2010 11:59:35 PM */ public class ReduceLockHotDemo { private static int executeTimes = 10; private static int threadCount = Runtime.getRuntime().availableProcessors() * 100; private static CountDownLatch latch = null; public static void main(String[] args) throws Exception { HandleTask task = new HandleTask(); long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); latch = new CountDownLatch(threadCount); for (int j = 0; j < threadCount; j++) { new Thread(task).start(); } latch.await(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) Thread Per Round( " + threadCount + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class HandleTask implements Runnable { private final Random random = new Random(); @Override public void run() { Handler.getInstance().handle(random.nextInt(10000)); latch.countDown(); } } static class Handler { private static final Handler self = new Handler(); private final Random random = new Random(); private final Lock lock = new ReentrantLock(); private Handler() { } public static Handler getInstance() { return self; } public void handle(int id) { // execute sth don‘t need lock try { Thread.sleep(random.nextInt(5)); } catch (Exception e) { e.printStackTrace(); } try { lock.lock(); // execute sth try { Thread.sleep(random.nextInt(5)); } catch (Exception e) { e.printStackTrace(); } } finally { lock.unlock(); } } } } /* Round: 1 ...... Round: 10 Execute summary: Round( 10 ) Thread Per Round( 200 ) Execute Time ( 5547 ) ms */ SplitReduceLockHotDemo[java] view plaincopy/** * */ package tune.program.concurrent; import java.util.Random; import java.util.concurrent.CountDownLatch; import java.util.concurrent.locks.Lock; import java.util.concurrent.locks.ReentrantLock; /** * 尽可能少用锁：尽可能只对需要控制的资源做加锁操作 * 拆分锁：独占锁拆分为多把锁（读写锁拆分、类似ConcurrentHashMap中默认拆分为16把锁） * * @author yangwm Aug 24, 2010 11:59:35 PM */ public class SplitReduceLockHotDemo { private static int executeTimes = 10; private static int threadCount = Runtime.getRuntime().availableProcessors() * 100; private static CountDownLatch latch = null; public static void main(String[] args) throws Exception { HandleTask task = new HandleTask(); long beginTime = System.currentTimeMillis(); for (int i = 0; i < executeTimes; i++) { System.out.println("Round: " + (i + 1)); latch = new CountDownLatch(threadCount); for (int j = 0; j < threadCount; j++) { new Thread(task).start(); } latch.await(); } long endTime = System.currentTimeMillis(); System.out.println("Execute summary: Round( " + executeTimes + " ) Thread Per Round( " + threadCount + " ) Execute Time ( " + (endTime - beginTime) + " ) ms"); } static class HandleTask implements Runnable { private final Random random = new Random(); @Override public void run() { Handler.getInstance().handle(random.nextInt(10000)); latch.countDown(); } } static class Handler { private static final Handler self = new Handler(); private final Random random = new Random(); private int lockCount = 10; private Lock[] locks = new Lock[lockCount]; private Handler() { for (int i = 0; i < lockCount; i++) { locks[i] = new ReentrantLock(); } } public static Handler getInstance() { return self; } public void handle(int id) { // execute sth don‘t need lock try { Thread.sleep(random.nextInt(5)); } catch (Exception e) { e.printStackTrace(); } int mod = id % lockCount; try { locks[mod].lock(); // execute sth try { Thread.sleep(random.nextInt(5)); } catch (Exception e) { e.printStackTrace(); } } finally { locks[mod].unlock(); } } } } /* Round: 1 ...... Round: 10 Execute summary: Round( 10 ) Thread Per Round( 200 ) Execute Time ( 843 ) ms */ ConcurrentStack和StackBenchmark[java] view plaincopy/** * */ package tune.program.concurrent; import java.util.concurrent.atomic.AtomicReference; /** * 使用Treiber算法实现Stack：基于CAS以及AtomicReference。 * * @author yangwm Aug 25, 2010 10:50:17 AM */ public class ConcurrentStack { AtomicReference> head = new AtomicReference>(); public void push(E item) { Node newHead = new Node(item); Node oldHead; do { oldHead = head.get(); newHead.next = oldHead; } while (!head.compareAndSet(oldHead, newHead)); } public E pop() { Node oldHead; Node newHead; do { oldHead = head.get(); if (oldHead == null) { return null; } newHead = oldHead.next; } while (!head.compareAndSet(oldHead, newHead)); return oldHead.item; } static class Node { final E item; Node next; public Node(E item) { this.item = item; } } } /** * */ package tune.program.concurrent; import java.util.Stack; import java.util.concurrent.CountDownLatch; import java.util.concurrent.CyclicBarrier; /** * 基准测试：Treiber算法实现Stack、同步实现的Stack * * @author yangwm Aug 25, 2010 11:36:14 AM */ public class StackBenchmark { public static void main(String[] args) throws Exception { StackBenchmark stackBenchmark = new StackBenchmark(); stackBenchmark.run(); } private Stack stack = new Stack(); private ConcurrentStack concurrentStack = new ConcurrentStack(); private static final int THREAD_COUNT = 300; private CountDownLatch latch = new CountDownLatch(THREAD_COUNT); private CyclicBarrier barrier = new CyclicBarrier(THREAD_COUNT); public void run() throws Exception { StackTask stackTask = new StackTask(); long beginTime = System.currentTimeMillis(); for (int i = 0; i < THREAD_COUNT; i++) { new Thread(stackTask).start(); } latch.await(); long endTime = System.currentTimeMillis(); System.out.println("Stack consume Time: " + (endTime - beginTime) + " ms"); latch = new CountDownLatch(THREAD_COUNT); barrier = new CyclicBarrier(THREAD_COUNT); ConcurrentStackTask concurrentStackTask = new ConcurrentStackTask(); beginTime = System.currentTimeMillis(); for (int i = 0; i < THREAD_COUNT; i++) { new Thread(concurrentStackTask).start(); } latch.await(); endTime = System.currentTimeMillis(); System.out.println("ConcurrentStack consume Time: " + (endTime - beginTime) + " ms"); } class StackTask implements Runnable { @Override public void run() { try { barrier.await(); } catch (Exception e) { e.printStackTrace(); } for (int i = 0; i < 10; i++) { stack.push(Thread.currentThread().getName()); stack.pop(); } latch.countDown(); } } class ConcurrentStackTask implements Runnable { @Override public void run() { try { barrier.await(); } catch (Exception e) { e.printStackTrace(); } for (int i = 0; i < 10; i++) { concurrentStack.push(Thread.currentThread().getName()); concurrentStack.pop(); } latch.countDown(); } } } /* Stack consume Time: 94 ms ConcurrentStack consume Time: 63 ms Stack consume Time: 78 ms ConcurrentStack consume Time: 62 ms */
Java性能调优笔记
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