JVM性能调优监控工具专题一:JVM自带性能调优工具(jps,jstack,jmap,jhat,jstat,hprof)

前提概要: 

       JDK本身提供了很多方便的JVM性能调优监控工具,除了集成式的VisualVM和jConsole外,还有jps、jstack、jmap、jhat、jstat、hprof等小巧的工具,每一种工具都有其自身的特点,用户可以根据你需要检测的应用或者程序片段的状况,适当的选择相应的工具进行检测。接下来的两个专题分别会讲VisualVM的具体应用。


现实企业级Java开发中,有时候我们会碰到下面这些问题:

  • OutOfMemoryError,内存不足

  • 内存泄露

  • 线程死锁

  • 锁争用(Lock Contention)

  • Java进程消耗CPU过高

  • ......

这些问题在日常开发中可能被很多人忽视(比如有的人遇到上面的问题只是重启服务器或者调大内存,而不会深究问题根源),但能够理解并解决这些问题是Java程序员进阶的必备要求。


基本工具命令

 

    jps

      实际中这是最常用的命令,下面要介绍的小工具更多的都是先要使用jps查看出当前有哪些Java进程,获取该Java进程的id后再对该进程进行处理。

    jps主要用来输出JVM中运行的进程状态信息。语法格式如下:

    

jps [options] [hostid]  

 如果不指定hostid就默认为当前主机或服务器。

   命令行参数选项说明如下:

-q 不输出类名、Jar名和传入main方法的参数
-m 输出传入main方法的参数
-l 输出main类或Jar的全限名
-v 输出传入JVM的参数

  比如

1、我现在有一个WordCountTopo的Strom程序正在本机运行。

2、使用java -jar deadlock.jar & 启动一个线程死锁的程序 

wangsheng@WANGSHENG-PC /E
$ jps -ml
14200 deadlock.jar
13952 com.wsheng.storm.topology.WordCountTopo D://input/ 3
13248 sun.tools.jps.Jps -ml
9728

    jstack 

jstack主要用来查看某个Java进程内的线程堆栈信息。语法格式如下:

jstack [option] pid
jstack [option] executable core
jstack [option] [server-id@]remote-hostname-or-ip

命令行参数选项说明如下
-l long listings,会打印出额外的锁信息,在发生死锁时可以用  jstack -l pid  来观察锁持有情况
-m mixed mode,不仅会输出Java堆栈信息,还会输出C/C++堆栈信息(比如Native方法)

  jstack可以定位到线程堆栈,根据堆栈信息我们可以定位到具体代码,所以它在JVM性能调优中使用得非常多。

    下面我们来一个实例:

     找出某个Java进程中最耗费CPU的Java线程并定位堆栈信息,用到的命令有ps、top、printf、jstack、grep。

   

    先找出Java进程ID,服务器上的Java应用名称为wordcount.jar:

[root@storm-master home]# ps -ef | grep wordcount | grep -v grep
root       2860   2547 13 02:09 pts/0    00:02:03 java -jar wordcount.jar /home/input 3

    得到进程ID为2860(也可以使用其它方式得到java的进程号),

 

    找出该进程内最耗费CPU的线程,可以使用如下3个命令,这里我们使用第3个命令得出如下结果:

1)ps -Lfp pid : 即 ps -Lfp 2860
2)ps -mp pid -o THREAD, tid, time :即 ps -mp 2860 -o THREAD,tid,time
3)top -Hp pid: 即   top -Hp 2860

JVM性能调优监控工具专题一:JVM自带性能调优工具(jps,jstack,jmap,jhat,jstat,hprof)_第1张图片
 

  TIME列就是各个Java线程耗费的CPU时间,显然CPU时间最长的是ID为2968的线程,用 

printf "%x\n" 2968

    得到2968的十六进制值为b98,下面会用到。     

    终于轮到jstack上场了,它用来输出进程2860的堆栈信息,然后根据线程ID的十六进制值grep,如下: 

[root@storm-master home]# jstack 2860 | grep b98
"SessionTracker" prio=10 tid=0x00007f55a44e4800 nid=0xb53 in Object.wait() [0x00007f558e06c000

 可以看到CPU消耗在SessionTracker这个类的Object.wait(),于是就能很容易的定位到相关的代码了。

 

jmap和 jhat


     jmap用来查看堆内存使用状况,一般结合jhat使用。

 

     jmap语法格式如下: 

jmap [option] pid
jmap [option] executable core
jmap [option] [server-id@]remote-hostname-or-ip

 如果运行在64位JVM上,由于linux操作系统的不同,可能需要指定-J-d64命令选项参数。

 

    打印进程的类加载器和类加载器加载的持久代对象信息: jmap -permstat pid

个人感觉这个不是太有用蠢话

 

输出:类加载器名称、对象是否存活(不可靠)、对象地址、父类加载器、已加载的类大小等信息,如图:

 JVM性能调优监控工具专题一:JVM自带性能调优工具(jps,jstack,jmap,jhat,jstat,hprof)_第2张图片


    查看进程堆内存使用情况:包括使用的GC算法、堆配置参数和各代中堆内存使用jmap -heap pid

比如下面的例子 

[root@storm-master home]# jmap -heap 2860
Attaching to process ID 2860, please wait...
Debugger attached successfully.
Server compiler detected.
JVM version is 20.45-b01

using thread-local object allocation.
Mark Sweep Compact GC

Heap Configuration:
   MinHeapFreeRatio = 40
   MaxHeapFreeRatio = 70
   MaxHeapSize      = 257949696 (246.0MB)
   NewSize          = 1310720 (1.25MB)
   MaxNewSize       = 17592186044415 MB
   OldSize          = 5439488 (5.1875MB)
   NewRatio         = 2
   SurvivorRatio    = 8
   PermSize         = 21757952 (20.75MB)
   MaxPermSize      = 85983232 (82.0MB)

Heap Usage:
New Generation (Eden + 1 Survivor Space):
   capacity = 12189696 (11.625MB)
   used     = 6769392 (6.4557952880859375MB)
   free     = 5420304 (5.1692047119140625MB)
   55.53372290826613% used
Eden Space:
   capacity = 10878976 (10.375MB)
   used     = 6585608 (6.280525207519531MB)
   free     = 4293368 (4.094474792480469MB)
   60.53518272307982% used
From Space:
   capacity = 1310720 (1.25MB)
   used     = 183784 (0.17527008056640625MB)
   free     = 1126936 (1.0747299194335938MB)
   14.0216064453125% used
To Space:
   capacity = 1310720 (1.25MB)
   used     = 0 (0.0MB)
   free     = 1310720 (1.25MB)
   0.0% used
tenured generation:
   capacity = 26619904 (25.38671875MB)
   used     = 15785896 (15.054603576660156MB)
   free     = 10834008 (10.332115173339844MB)
   59.30110040967841% used
Perm Generation:
   capacity = 33554432 (32.0MB)
   used     = 33323352 (31.779624938964844MB)
   free     = 231080 (0.22037506103515625MB)
   99.31132793426514% used

    查看堆内存中的对象数目、大小统计直方图,如果带上live则只统计活对象:jmap -histo[:live] pid

 

[root@storm-master Desktop]# jmap -histo 2860

 num     #instances         #bytes  class name
----------------------------------------------
   1:         13917       11432488  [B
   2:          6117        6181448  <instanceKlassKlass>
   3:         39520        6004504  <constMethodKlass>
   4:          6117        5517072  <constantPoolKlass>
   5:         39520        5383280  <methodKlass>
   6:          5148        3150944  <constantPoolCacheKlass>
   7:         29954        2810640  [C
   8:         50179        2469272  <symbolKlass>
   9:         42122        1791704  [Ljava.lang.Object;
  10:          1804         961464  <methodDataKlass>
  11:         11747         941200  [Ljava.util.HashMap$Entry;
  12:         28786         921152  java.lang.String
  13:          6347         660088  java.lang.Class
  14:          7374         625616  [S
  15:         11740         563520  java.util.HashMap
  16:         23447         562728  clojure.lang.PersistentHashMap$BitmapIndexedNode
  17:         10980         351360  clojure.lang.Symbol
  18:          8544         341760  java.lang.ref.SoftReference
  19:          8028         336632  [[I
  20:          3944         283968  java.lang.reflect.Constructor
  21:          4744         227712  java.nio.HeapByteBuffer
  22:          6854         219328  java.util.AbstractList$Itr
  23:          2185         195192  [I
  24:          3854         184992  java.nio.HeapCharBuffer
  25:          5500         176000  java.util.concurrent.ConcurrentHashMap$HashEntry

   class name是对象类型,说明如下: 

 

B  byte
C  char
D  double
F  float
I  int
J  long
Z  boolean
[  数组,如[I表示int[]
[L+类名 其他对象

    还有一个很常用的情况是:用jmap把进程内存使用情况dump到文件中,再用jhat分析查看。需要注意的是 dump出来的文件还可以用MAT、VisualVM等工具查看。

jmap进行dump命令格式如下:


jmap -dump:format=b,file=dumpFileName pid

    我一样地对上面进程ID为2860进行Dump:

[root@storm-master Desktop]# jmap -dump:format=b,file=/home/dump.dat 2860
Dumping heap to /home/dump.dat ...
Heap dump file created

  然后使用jhat来对上面dump出来的内容进行分析   

[root@storm-master Desktop]# jhat -port 8888 /home/dump.dat 
Reading from /home/dump.dat...
Dump file created Sat Aug 01 04:21:12 PDT 2015
Snapshot read, resolving...
Resolving 411123 objects...
Chasing references, expect 82 dots..................................................................................
Eliminating duplicate references..................................................................................
Snapshot resolved.
Started HTTP server on port 8888
Server is ready.

    注意如果Dump文件太大,可能需要加上-J-Xmx512m参数以指定最大堆内存,即jhat -J-Xmx512m -port 8888 /home/dump.dat。然后就可以在浏览器中输入主机地址:8888查看了: 

JVM性能调优监控工具专题一:JVM自带性能调优工具(jps,jstack,jmap,jhat,jstat,hprof)_第3张图片 

点击每一个蓝色的超链接,你都会看到其相关更具体的信息,而最后一项更是支持OQL(对象查询语言)。

 

    jstat: 看看各个区内存和GC的情况

 

    语法格式如下:

 

jstat [ generalOption | outputOptions vmid [interval[s|ms] [count]] ]

 vmid是Java虚拟机ID,在Linux/Unix系统上一般就是进程ID。interval是采样时间间隔。count是采样数目。比如下面输出的是GC信息,采样时间间隔为250ms,采样数为6:

 

[root@storm-master Desktop]# jstat -gc 2860 250 6



要明白上面各列的意义,先看JVM堆内存布局:

JVM性能调优监控工具专题一:JVM自带性能调优工具(jps,jstack,jmap,jhat,jstat,hprof)_第4张图片

 

可以看出:

堆内存 = 年轻代 + 年老代 + 永久代
年轻代 = Eden区 + 两个Survivor区(From和To)

 现在来解释各列含义:

S0C、S1C、S0U、S1U:Survivor 0/1区容量(Capacity)和使用量(Used)
EC、EU:Eden区容量和使用量
OC、OU:年老代容量和使用量
PC、PU:永久代容量和使用量
YGC、YGT:年轻代GC次数和GC耗时
FGC、FGCT:Full GC次数和Full GC耗时
GCT:GC总耗时<span style="color: rgb(51, 51, 51); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 13px; line-height: 24px; text-indent: 36pt; background-color: rgb(255, 255, 255);">   </span>


    hprof   

 hprof能够展现CPU使用率,统计堆内存使用情况。

 HPROF: 一个Heap/CPU Profiling工具:J2SE中提供了一个简单的命令行工具来对java程序的cpu和heap进行 profiling,叫做HPROF。HPROF实际上是JVM中的一个native的库,它会在JVM启动的时候通过命令行参数来动态加载,并成为 JVM进程的一部分。若要在java进程启动的时候使用HPROF,用户可以通过各种命令行参数类型来使用HPROF对java进程的heap或者 (和)cpu进行profiling的功能。HPROF产生的profiling数据可以是二进制的,也可以是文本格式的。这些日志可以用来跟踪和分析 java进程的性能问题和瓶颈,解决内存使用上不优的地方或者程序实现上的不优之处。二进制格式的日志还可以被JVM中的HAT工具来进行浏览和分析,用 以观察java进程的heap中各种类型和数据的情况。在J2SE 5.0以后的版本中,HPROF已经被并入到一个叫做Java Virtual Machine Tool Interface(JVM TI)中。


语法格式如下:

java -agentlib:hprof[=options] ToBeProfiledClass
java -Xrunprof[:options] ToBeProfiledClass
javac -J-agentlib:hprof[=options] ToBeProfiledClass

 完整的命令选项如下:

Option Name and Value  Description                    Default
---------------------  -----------                    -------
heap=dump|sites|all    heap profiling                 all
cpu=samples|times|old  CPU usage                      off
monitor=y|n            monitor contention             n
format=a|b             text(txt) or binary output     a
file=<file>            write data to file             java.hprof[.txt]
net=<host>:<port>      send data over a socket        off
depth=<size>           stack trace depth              4
interval=<ms>          sample interval in ms          10
cutoff=<value>         output cutoff point            0.0001
lineno=y|n             line number in traces?         y
thread=y|n             thread in traces?              n
doe=y|n                dump on exit?                  y
msa=y|n                Solaris micro state accounting n
force=y|n              force output to <file>         y
verbose=y|n            print messages about dumps     y

- Get sample cpu information every 20 millisec, with a stack depth of 3: 

         java -agentlib:hprof=cpu=samples,interval=20,depth=3 classname 
     - Get heap usage information based on the allocation sites: 
         java -agentlib:hprof=heap=sites classname 

      上面每隔20毫秒采样CPU消耗信息,堆栈深度为3,生成的profile文件名称是java.hprof.txt,在当前目录。 

      默认情况下,java进程profiling的信息(sites和dump)都会被 写入到一个叫做java.hprof.txt的文件中。大多数情况下,该文件中都会对每个trace,threads,objects包含一个ID,每一 个ID代表一个不同的观察对象。通常,traces会从300000开始。 默认,force=y,会将所有的信息全部输出到output文件中,所以如果含有 多个JVMs都采用的HRPOF enable的方式运行,最好将force=n,这样能够将单独的JVM的profiling信息输出到不同的指定文件。 interval选项只在 cpu=samples的情况下生效,表示每隔多少毫秒对java进程的cpu使用情况进行一次采集。 msa选项仅仅在Solaris系统下才有效, 表示会使用Solaris下的Micro State Accounting功能 

 

实例部分

该部分将使用相关的实例和前面提到的JVM性能调优工具来进行性能诊断。

 

    使用jstack来分析死锁问题:

       上面说明中提到 jstack主要用来查看某个Java进程内的线程堆栈信息,您可以使用它查明问题。jstack [-l] <pid>,pid可以通过使用jps命令来查看当前Java程序的pid值,-l是可选参数,它可以显示线程阻塞/死锁情况

 

package com.wsheng.aggregator.thread.performance;

import org.springframework.stereotype.Component;

/**
 * Dead lock example
 * 
 * @author Josh Wang(Sheng)
 *
 * @email  [email protected]
 */
@Component
public class DeadLock {  
  
    public static void main(String[] args) {  
    	System.out.println(" start the example ----- ");
        final Object obj_1 = new Object(), obj_2 = new Object();  
          
        Thread t1 = new Thread("t1") {  
            @Override  
            public void run() {  
                synchronized (obj_1) {  
                    try {  
                    	System.out.println("thread t1 start...");
                        Thread.sleep(3000);  
                    } catch (InterruptedException e) {e.printStackTrace();}  
                      
                    synchronized (obj_2) {  
                        System.out.println("thread t1 done....");  
                    }  
                }  
            }  
        };  
          
        Thread t2 = new Thread("t2") {  
            @Override  
            public void run() {  
                synchronized (obj_2) {  
                    try {  
                    	System.out.println("thread t2 start...");
                        Thread.sleep(3000);  
                    } catch (InterruptedException e) {e.printStackTrace();}  
                      
                    synchronized (obj_1) {  
                        System.out.println("thread t2 done...");  
                    }  
                }  
            }  
        };  
          
        t1.start();  
        t2.start();  
    }  
      
}

 

    以上DeadLock类是一个死锁的例子,假使在我们不知情的情况下,运行DeadLock后,发现等了N久都没有在屏幕打印线程完成信息。这个时候我们就可以使用jps查看该程序的pid值和使用jstack来生产堆栈结果问题。

java -jar deadlock.jar com.wsheng.aggregator.thread.performance.DeadLock
$ jps  
  3076 Jps  
  448 DeadLock  
$ jstack -l 448 deadlock.jstack


 结果文件deadlock.jstack内容如下:

2014-11-29 13:31:06
Full thread dump Java HotSpot(TM) 64-Bit Server VM (24.65-b04 mixed mode):

"Attach Listener" daemon prio=5 tid=0x00007fd9d4002800 nid=0x440b waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"DestroyJavaVM" prio=5 tid=0x00007fd9d4802000 nid=0x1903 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"t2" prio=5 tid=0x00007fd9d30ac000 nid=0x5903 waiting for monitor entry [0x000000011da46000]
   java.lang.Thread.State: BLOCKED (on object monitor)
	at DeadLock$2.run(DeadLock.java:38)
	- waiting to lock <0x00000007aaba7e58> (a java.lang.Object)
	- locked <0x00000007aaba7e68> (a java.lang.Object)

   Locked ownable synchronizers:
	- None

"t1" prio=5 tid=0x00007fd9d30ab800 nid=0x5703 waiting for monitor entry [0x000000011d943000]
   java.lang.Thread.State: BLOCKED (on object monitor)
	at DeadLock$1.run(DeadLock.java:23)
	- waiting to lock <0x00000007aaba7e68> (a java.lang.Object)
	- locked <0x00000007aaba7e58> (a java.lang.Object)

   Locked ownable synchronizers:
	- None

"Service Thread" daemon prio=5 tid=0x00007fd9d2809000 nid=0x5303 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"C2 CompilerThread1" daemon prio=5 tid=0x00007fd9d304e000 nid=0x5103 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"C2 CompilerThread0" daemon prio=5 tid=0x00007fd9d2800800 nid=0x4f03 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"Signal Dispatcher" daemon prio=5 tid=0x00007fd9d3035000 nid=0x4d03 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"Finalizer" daemon prio=5 tid=0x00007fd9d2013000 nid=0x3903 in Object.wait() [0x000000011d18d000]
   java.lang.Thread.State: WAITING (on object monitor)
	at java.lang.Object.wait(Native Method)
	- waiting on <0x00000007aaa85608> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135)
	- locked <0x00000007aaa85608> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:151)
	at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:209)

   Locked ownable synchronizers:
	- None

"Reference Handler" daemon prio=5 tid=0x00007fd9d2012000 nid=0x3703 in Object.wait() [0x000000011d08a000]
   java.lang.Thread.State: WAITING (on object monitor)
	at java.lang.Object.wait(Native Method)
	- waiting on <0x00000007aaa85190> (a java.lang.ref.Reference$Lock)
	at java.lang.Object.wait(Object.java:503)
	at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:133)
	- locked <0x00000007aaa85190> (a java.lang.ref.Reference$Lock)

   Locked ownable synchronizers:
	- None

"VM Thread" prio=5 tid=0x00007fd9d5011000 nid=0x3503 runnable 

"GC task thread#0 (ParallelGC)" prio=5 tid=0x00007fd9d200b000 nid=0x2503 runnable 

"GC task thread#1 (ParallelGC)" prio=5 tid=0x00007fd9d200b800 nid=0x2703 runnable 

"GC task thread#2 (ParallelGC)" prio=5 tid=0x00007fd9d200c800 nid=0x2903 runnable 

"GC task thread#3 (ParallelGC)" prio=5 tid=0x00007fd9d200d000 nid=0x2b03 runnable 

"GC task thread#4 (ParallelGC)" prio=5 tid=0x00007fd9d200d800 nid=0x2d03 runnable 

"GC task thread#5 (ParallelGC)" prio=5 tid=0x00007fd9d200e000 nid=0x2f03 runnable 

"GC task thread#6 (ParallelGC)" prio=5 tid=0x00007fd9d200f000 nid=0x3103 runnable 

"GC task thread#7 (ParallelGC)" prio=5 tid=0x00007fd9d200f800 nid=0x3303 runnable 

"VM Periodic Task Thread" prio=5 tid=0x00007fd9d3033800 nid=0x5503 waiting on condition 

JNI global references: 114


Found one Java-level deadlock:
=============================
"t2":
  waiting to lock monitor 0x00007fd9d30aebb8 (object 0x00000007aaba7e58, a java.lang.Object),
  which is held by "t1"
"t1":
  waiting to lock monitor 0x00007fd9d28128b8 (object 0x00000007aaba7e68, a java.lang.Object),
  which is held by "t2"

Java stack information for the threads listed above:
===================================================
"t2":
	at DeadLock$2.run(DeadLock.java:38)
	- waiting to lock <0x00000007aaba7e58> (a java.lang.Object)
	- locked <0x00000007aaba7e68> (a java.lang.Object)
"t1":
	at DeadLock$1.run(DeadLock.java:23)
	- waiting to lock <0x00000007aaba7e68> (a java.lang.Object)
	- locked <0x00000007aaba7e58> (a java.lang.Object)

Found 1 deadlock.

 从这个结果文件我们一看到发现了一个死锁,具体是线程t2在等待线程t1,而线程t1在等待线程t2造成的,同时也记录了线程的堆栈和代码行数,通过这个堆栈和行数我们就可以去检查对应的代码块,从而发现问题和解决问题。

可通过下面的代码解决死锁问题:

import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;

/**
 * Dead lock example
 * 
 * @author Josh Wang(Sheng)
 *
 * @email  [email protected]
 */
public class DeadLock2Live {  
  
    public static void main(String[] args) {  
    	System.out.println(" start the example ----- ");
        final Lock lock = new ReentrantLock(); 
          
        Thread t1 = new Thread("t1") {  
            @Override  
            public void run() {  
            	try {  
	           	lock.lock();
	                Thread.sleep(3000); 
	                System.out.println("thread t1 done.");
            	} catch (InterruptedException e) {
            		e.printStackTrace();
            	} finally {
            		lock.unlock();
            	}
            }
            };  
          
        Thread t2 = new Thread("t2") {  
            @Override  
            public void run() {  
            	try {  
            		lock.lock();
                	Thread.sleep(3000);
                    System.out.println("thread t2 done.");
                   

                }  catch (InterruptedException e) {
                	e.printStackTrace();
                } finally {
                	lock.unlock();
                }
            }  
        };  
          
        t1.start();  
        t2.start();  
    
}
        
} 

 

    继续使用jstack来分析HashMap在多线程情况下的死锁问题:

       对于如下代码,使用10个线程来处理提交的2000个任务,每个任务会分别循环往hashmap中分别存入和取出1000个数,通过测试发现,程序并不能完整执行完成。[PS:该程序能不能成功执行完,有时也取决于所使用的服务器的运行状况,我在笔记本上测试的时候,大多时候该程序不能成功执行完成,有时会出现CPU转速加快,发热等情况]

 

import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
/**
 * @author Josh Wang(Sheng)
 *
 * @email  [email protected]
 */
public class HashMapDeadLock implements Callable<Integer> {
	
	private static ExecutorService threadPool = Executors.newFixedThreadPool(10);
	
	private static Map<Integer, Integer> results = new HashMap<>();

	@Override
	public Integer call() throws Exception {
		results.put(1, 1);
		results.put(2, 2);
		results.put(3, 3);
		
		for (int i = 0; i < 1000; i++) {
			results.put(i, i);
		}
		
		Thread.sleep(1000);
		
		for (int i= 0; i < 1000; i++) {
			results.remove(i);
		}
		
		System.out.println(" ---- " + Thread.currentThread().getName()  + "		" + results.get(0));
		
		return results.get(1);
	}
	
	
public static void main(String[] args) throws InterruptedException, ExecutionException {
	try {
		for (int i = 0; i < 2000; i++) {
		     HashMapDeadLock hashMapDeadLock  = new HashMapDeadLock();
//		     Future<Integer> future = threadPool.submit(hashMapDeadLock);
//		     future.get();
		     threadPool.submit(hashMapDeadLock);
		}
	 } catch (Exception e) {
		e.printStackTrace();
	 } finally {
		threadPool.shutdown();
	 }
	}
}

1) 使用jps查看线程可得:

43221 Jps
30056 
43125 HashMapDeadLock

2)使用jstack导出多线程栈区信息:

 jstack -l 43125 > hash.jstack 

 3) hash.jstack的内容如下:

2014-11-29 18:14:22
Full thread dump Java HotSpot(TM) 64-Bit Server VM (24.65-b04 mixed mode):

"Attach Listener" daemon prio=5 tid=0x00007f83ee08a000 nid=0x5d07 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"DestroyJavaVM" prio=5 tid=0x00007f83eb016800 nid=0x1903 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"pool-1-thread-10" prio=5 tid=0x00007f83ec80a000 nid=0x6903 runnable [0x000000011cd19000]
   java.lang.Thread.State: RUNNABLE
	at java.util.HashMap.transfer(HashMap.java:601)
	at java.util.HashMap.resize(HashMap.java:581)
	at java.util.HashMap.addEntry(HashMap.java:879)
	at java.util.HashMap.put(HashMap.java:505)
	at HashMapDeadLock.call(HashMapDeadLock.java:30)
	at HashMapDeadLock.call(HashMapDeadLock.java:1)
	at java.util.concurrent.FutureTask.run(FutureTask.java:262)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)

   Locked ownable synchronizers:
	- <0x00000007aaba84c8> (a java.util.concurrent.ThreadPoolExecutor$Worker)

"Service Thread" daemon prio=5 tid=0x00007f83eb839800 nid=0x5303 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"C2 CompilerThread1" daemon prio=5 tid=0x00007f83ee002000 nid=0x5103 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"C2 CompilerThread0" daemon prio=5 tid=0x00007f83ee000000 nid=0x4f03 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"Signal Dispatcher" daemon prio=5 tid=0x00007f83ec04c800 nid=0x4d03 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
	- None

"Finalizer" daemon prio=5 tid=0x00007f83eb836800 nid=0x3903 in Object.wait() [0x000000011bc58000]
   java.lang.Thread.State: WAITING (on object monitor)
	at java.lang.Object.wait(Native Method)
	- waiting on <0x00000007aaa85608> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135)
	- locked <0x00000007aaa85608> (a java.lang.ref.ReferenceQueue$Lock)
	at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:151)
	at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:209)

   Locked ownable synchronizers:
	- None

"Reference Handler" daemon prio=5 tid=0x00007f83eb01a800 nid=0x3703 in Object.wait() [0x000000011bb55000]
   java.lang.Thread.State: WAITING (on object monitor)
	at java.lang.Object.wait(Native Method)
	- waiting on <0x00000007aaa85190> (a java.lang.ref.Reference$Lock)
	at java.lang.Object.wait(Object.java:503)
	at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:133)
	- locked <0x00000007aaa85190> (a java.lang.ref.Reference$Lock)

   Locked ownable synchronizers:
	- None

"VM Thread" prio=5 tid=0x00007f83ed808800 nid=0x3503 runnable 

"GC task thread#0 (ParallelGC)" prio=5 tid=0x00007f83ec80d800 nid=0x2503 runnable 

"GC task thread#1 (ParallelGC)" prio=5 tid=0x00007f83ec80e000 nid=0x2703 runnable 

"GC task thread#2 (ParallelGC)" prio=5 tid=0x00007f83ec001000 nid=0x2903 runnable 

"GC task thread#3 (ParallelGC)" prio=5 tid=0x00007f83ec002000 nid=0x2b03 runnable 

"GC task thread#4 (ParallelGC)" prio=5 tid=0x00007f83ec002800 nid=0x2d03 runnable 

"GC task thread#5 (ParallelGC)" prio=5 tid=0x00007f83ec003000 nid=0x2f03 runnable 

"GC task thread#6 (ParallelGC)" prio=5 tid=0x00007f83ec003800 nid=0x3103 runnable 

"GC task thread#7 (ParallelGC)" prio=5 tid=0x00007f83ec004800 nid=0x3303 runnable 

"VM Periodic Task Thread" prio=5 tid=0x00007f83ec814800 nid=0x5503 waiting on condition 

JNI global references: 134

 4)从上边部分可看出,代码中的30行出问题了,即往hashmap中写入数据出问题了:

results.put(i, i);  

很快就明白因为Hashmap不是线程安全的,所以问题就出在这个地方,我们可以使用线程安全的map即

ConcurrentHashMap后者HashTable来解决该问题:

 

import java.util.Map;
import java.util.concurrent.Callable;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

/**
 * 
 */

/**
 * @author Josh Wang(Sheng)
 *
 * @email  [email protected]
 */
public class HashMapDead2LiveLock implements Callable<Integer> {
	
	private static ExecutorService threadPool = Executors.newFixedThreadPool(10);
	
	private static Map<Integer, Integer> results = new ConcurrentHashMap<>();

	@Override
	public Integer call() throws Exception {
		results.put(1, 1);
		results.put(2, 2);
		results.put(3, 3);
		
		for (int i = 0; i < 1000; i++) {
			results.put(i, i);
		}
		
		Thread.sleep(1000);
		
		for (int i= 0; i < 1000; i++) {
			results.remove(i);
		}
		
		System.out.println(" ---- " + Thread.currentThread().getName()  + "		" + results.get(0));
		
		return results.get(1);
	}
	
	
	public static void main(String[] args) throws InterruptedException, ExecutionException {
		try {
			for (int i = 0; i < 2000; i++) {
					HashMapDead2LiveLock hashMapDeadLock  = new HashMapDead2LiveLock();
//					Future<Integer> future = threadPool.submit(hashMapDeadLock);
//					future.get();
					threadPool.submit(hashMapDeadLock);
				}
		} catch (Exception e) {
			e.printStackTrace();
		} finally {
			threadPool.shutdown();
		}
	
		
		
		
	}

	
}

改成ConcurrentHashMap后,重新执行该程序,你会发现很快该程序就执行完了。

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