Java GC回收机制

Posted 2020-08-15 灵犀一脚C

优秀Java程序员必须了解的GC工作原理

 

一个优秀的Java程序员必须了解GC的工作原理、如何优化GC的性能、如何与GC进行有限的交互，因为有一些应用程序对性能要求较高，例如嵌入式系统、实时系统等，只有全面提升内存的管理效率 ，才能提高整个应用程序的性能。

一个优秀的Java程序员必须了解GC的工作原理、如何优化GC的性能、如何与GC进行有限的交互，因为有一些应用程序对性能要求较高，例如嵌入式系统、实时系统等，只有全面提升内存的管理效率 ，才能提高整个应用程序的性能。本篇文章首先简单介绍GC的工作原理之后，然后再对GC的几个关键问题进行深入探讨，最后提出一些Java程序设计建议，从GC角度提高Java程序的性能。

GC的基本原理

Java的内存管理实际上就是对象的管理，其中包括对象的分配和释放。

对于程序员来说，分配对象使用new关键字；释放对象时，只要将对象所有引用赋值为null，让程序不能够再访问到这个对象，我们称该对象为\\"不可达的\\".GC将负责回收所有\\"不可达\\"对象的内存空间。

对于GC来说，当程序员创建对象时，GC就开始监控这个对象的地址、大小以及使用情况。通常，GC采用有向图的方式记录和管理堆（heap）中的所有对象（详见 参考资料1 ）。通过这种方式确定哪些对象是\\"可达的\\"，哪些对象是\\"不可达的\\".当GC确定一些对象为\\"不可达\\"时，GC就有责任回收这些内存空间。但是，为了保证GC能够在不同平台实现的问题，Java规范对GC的很多行为都没有进行严格的规定。例如，对于采用什么类型的回收算法、什么时候进行回收等重要问题都没有明确的规定。因此，不同的JVM的实现者往往有不同的实现算法。这也给Java程序员的开发带来行多不确定性。本文研究了几个与GC工作相关的问题，努力减少这种不确定性给Java程序带来的负面影响。

增量式GC（ Incremental GC ）

GC在JVM中通常是由一个或一组进程来实现的，它本身也和用户程序一样占用heap空间，运行时也占用CPU.当GC进程运行时，应用程序停止运行。因此，当GC运行时间较长时，用户能够感到 Java程序的停顿，另外一方面，如果GC运行时间太短，则可能对象回收率太低，这意味着还有很多应该回收的对象没有被回收，仍然占用大量内存。因此，在设计GC的时候，就必须在停顿时间和回收率之间进行权衡。一个好的GC实现允许用户定义自己所需要的设置，例如有些内存有限有设备，对内存的使用量非常敏感，希望GC能够准确的回收内存，它并不在意程序速度的放慢。另外一些实时网络游戏，就不能够允许程序有长时间的中断。增量式GC就是通过一定的回收算法，把一个长时间的中断，划分为很多个小的中断，通过这种方式减少GC对用户程序的影响。虽然，增量式GC在整体性能上可能不如普通GC的效率高，但是它能够减少程序的最长停顿时间。

Sun JDK提供的HotSpot JVM就能支持增量式GC.HotSpot JVM缺省GC方式为不使用增量GC，为了启动增量GC，我们必须在运行Java程序时增加-Xincgc的参数。HotSpot JVM增量式GC的实现是采用Train GC算法。它的基本想法就是，将堆中的所有对象按照创建和使用情况进行分组（分层），将使用频繁高和具有相关性的对象放在一队中，随着程序的运行，不断对组进行调整。当GC运行时，它总是先回收最老的（最近很少访问的）的对象，如果整组都为可回收对象，GC将整组回收。这样，每次GC运行只回收一定比例的不可达对象，保证程序的顺畅运行。

详解finalize函数

finalize是位于Object类的一个方法，该方法的访问修饰符为protected，由于所有类为Object的子类，因此用户类很容易访问到这个方法。由于，finalize函数没有自动实现链式调用，我们必须手动的实现，因此finalize函数的最后一个语句通常是super.finalize（）。通过这种方式，我们可以实现从下到上实现finalize的调用，即先释放自己的资源，然后再释放父类的资源。

根据Java语言规范，JVM保证调用finalize函数之前，这个对象是不可达的，但是JVM不保证这个函数一定会被调用。另外，规范还保证finalize函数最多运行一次。

很多Java初学者会认为这个方法类似与C++中的析构函数，将很多对象、资源的释放都放在这一函数里面。其实，这不是一种很好的方式。原因有三，其一，GC为了能够支持finalize函数，要对覆盖这个函数的对象作很多附加的工作。其二，在finalize运行完成之后，该对象可能变成可达的，GC还要再检查一次该对象是否是可达的。因此，使用 finalize会降低GC的运行性能。其三，由于GC调用finalize的时间是不确定的，因此通过这种方式释放资源也是不确定的。

通常，finalize用于一些不容易控制、并且非常重要资源的释放，例如一些I/O的操作，数据的连接。这些资源的释放对整个应用程序是非常关键的。在这种情况下，程序员应该以通过程序本身管理（包括释放）这些资源为主，以finalize函数释放资源方式为辅，形成一种双保险的管理机制，而不应该仅仅依靠finalize来释放资源。

下面给出一个例子说明，finalize函数被调用以后，仍然可能是可达的，同时也可说明一个对象的finalize只可能运行一次。

 1 class MyObject{
 2 
 3 Test main; //记录Test对象，在finalize中时用于恢复可达性
 4 
 5 public MyObject(Test t)
 6 
 7 {
 8 
 9 main=t; //保存Test 对象
10 
11 }
12 
13 protected void finalize()
14 
15 {
16 
17 main.ref=this;// 恢复本对象，让本对象可达
18 
19 System.out.println(\\"This is finalize\\");//用于测试finalize只运行一次
20 
21 }
22 
23 }
24 
25 class Test {
26 
27 MyObject ref;
28 
29 public static void main(String[] args) {
30 
31 Test test=new Test();
32 
33 test.ref=new MyObject(test);
34 
35 test.ref=null; //MyObject对象为不可达对象，finalize将被调用
36 
37 System.gc();
38 
39 if (test.ref!=null) System.out.println(\\"My Object还活着\\");
40 
41 }
42 
43 }
44 
45 运行结果：
46 
47 This is finalize
48 
49 MyObject还活着

 

此例子中，需要注意的是虽然MyObject对象在finalize中变成可达对象，但是下次回收时候，finalize却不再被调用，因为finalize函数最多只调用一次。


程序如何与GC进行交互

Java2增强了内存管理功能，增加了一个java.lang.ref包，其中定义了三种引用类。这三种引用类分别为SoftReference、WeakReference和 PhantomReference.通过使用这些引用类，程序员可以在一定程度与GC进行交互，以便改善GC的工作效率。这些引用类的引用强度介于可达对象和不可达对象之间。

创建一个引用对象也非常容易，例如如果你需要创建一个Soft Reference对象，那么首先创建一个对象，并采用普通引用方式（可达对象）；然后再创建一个SoftReference引用该对象；最后将普通引用设置为null.通过这种方式，这个对象就只有一个Soft Reference引用。同时，我们称这个对象为Soft Reference 对象。

Soft Reference的主要特点是据有较强的引用功能。只有当内存不够的时候，才进行回收这类内存，因此在内存足够的时候，它们通常不被回收。另外，这些引用对象还能保证在Java抛出OutOfMemory 异常之前，被设置为null.它可以用于实现一些常用图片的缓存，实现Cache的功能，保证最大限度的使用内存而不引起OutOfMemory.以下给出这种引用类型的使用伪代码；

 1 //申请一个图像对象
 2 
 3 Image image=new Image();//创建Image对象
 4 
 5 …
 6 
 7 //使用 image
 8 
 9 …
10 
11 //使用完了image，将它设置为soft 引用类型，并且释放强引用；
12 
13 SoftReference sr=new SoftReference(image);
14 
15 image=null;
16 
17 …
18 
19 //下次使用时
20 
21 if (sr!=null) image=sr.get();
22 
23 else{
24 
25 //由于GC由于低内存，已释放image，因此需要重新装载；
26 
27 image=new Image();
28 
29 sr=new SoftReference(image);
30 
31 }

 

Weak引用对象与Soft引用对象的最大不同就在于：GC在进行回收时，需要通过算法检查是否回收Soft引用对象，而对于Weak引用对象，GC总是进行回收。Weak引用对象更容易、更快被 GC回收。虽然，GC在运行时一定回收Weak对象，但是复杂关系的Weak对象群常常需要好几次GC的运行才能完成。Weak引用对象常常用于Map结构中，引用数据量较大的对象，一旦该对象的强引用为null时，GC能够快速地回收该对象空间。

Phantom引用的用途较少，主要用于辅助 finalize函数的使用。Phantom对象指一些对象，它们执行完了finalize函数，并为不可达对象，但是它们还没有被GC回收。这种对象可以辅助finalize进行一些后期的回收工作，我们通过覆盖Reference的clear（）方法，增强资源回收机制的灵活性。

一些Java编码的建议

根据GC的工作原理，我们可以通过一些技巧和方式，让GC运行更加有效率，更加符合应用程序的要求。以下就是一些程序设计的几点建议。

1.最基本的建议就是尽早释放无用对象的引用。大多数程序员在使用临时变量的时候，都是让引用变量在退出活动域（scope）后，自动设置为null.我们在使用这种方式时候，必须特别注意一些复杂的对象图，例如数组，队列，树，图等，这些对象之间有相互引用关系较为复杂。对于这类对象，GC回收它们一般效率较低。如果程序允许，尽早将不用的引用对象赋为null.这样可以加速GC的工作。

2.尽量少用finalize函数。finalize函数是Java提供给程序员一个释放对象或资源的机会。但是，它会加大GC的工作量，因此尽量少采用finalize方式回收资源。

3.如果需要使用经常使用的图片，可以使用soft应用类型。它可以尽可能将图片保存在内存中，供程序调用，而不引起OutOfMemory.

4.注意集合数据类型，包括数组，树，图，链表等数据结构，这些数据结构对GC来说，回收更为复杂。另外，注意一些全局的变量，以及一些静态变量。这些变量往往容易引起悬挂对象（dangling reference），造成内存浪费。

5.当程序有一定的等待时间，程序员可以手动执行System.gc（），通知GC运行，但是Java语言规范并不保证GC一定会执行。使用增量式GC可以缩短Java程序的暂停时间。

 

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目录

1. Java垃圾回收概况
2. Java内存区域
3. Java对象的访问方式
4. Java内存分配机制
5. Java GC机制
6. 垃圾收集器

Java垃圾回收概况

　　Java GC（Garbage Collection，垃圾收集，垃圾回收）机制，是Java与C++/C的主要区别之一，作为Java开发者，一般不需要专门编写内存回收和垃圾清理代 码，对内存泄露和溢出的问题，也不需要像C程序员那样战战兢兢。这是因为在Java虚拟机中，存在自动内存管理和垃圾清扫机制。概括地说，该机制对 JVM（Java Virtual Machine）中的内存进行标记，并确定哪些内存需要回收，根据一定的回收策略，自动的回收内存，永不停息（Nerver Stop）的保证JVM中的内存空间，放置出现内存泄露和溢出问题。

　　关于JVM，需要说明一下的是，目前使用最多的Sun公司的JDK中，自从 1999年的JDK1.2开始直至现在仍在广泛使用的JDK6，其中默认的虚拟机都是HotSpot。2009年，Oracle收购Sun，加上之前收购 的EBA公司，Oracle拥有3大虚拟机中的两个：JRockit和HotSpot，Oracle也表明了想要整合两大虚拟机的意图，但是目前在新发布 的JDK7中，默认的虚拟机仍然是HotSpot，因此本文中默认介绍的虚拟机都是HotSpot，相关机制也主要是指HotSpot的GC机制。

　　Java GC机制主要完成3件事：确定哪些内存需要回收，确定什么时候需要执行GC，如何执行GC。经过这么长时间的发展（事实上，在Java语言出现之前，就有 GC机制的存在，如Lisp语言），Java GC机制已经日臻完善，几乎可以自动的为我们做绝大多数的事情。然而，如果我们从事较大型的应用软件开发，曾经出现过内存优化的需求，就必定要研究 Java GC机制。

　　学习Java GC机制，可以帮助我们在日常工作中排查各种内存溢出或泄露问题，解决性能瓶颈，达到更高的并发量，写出更高效的程序。

　　我们将从4个方面学习Java GC机制，1，内存是如何分配的；2，如何保证内存不被错误回收（即：哪些内存需要回收）；3，在什么情况下执行GC以及执行GC的方式；4，如何监控和优化GC机制。

Java内存区域

　　了解Java GC机制，必须先清楚在JVM中内存区域的划分。在Java运行时的数据区里，由JVM管理的内存区域分为下图几个模块：

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