集合框架map学习笔记-WeakHashMap

Map： 

1、HashMap 

2、LinkedHashMap 

3、IdentityHashMap 

4、WeakHashMap 

5、TreeMap 

6、EnumMap 

7、ConcurrentHashMap 

8、ConcurrentSkipListMap 

今天主要学习的是WeakHashMap。

1、WeakHashMap的学习前提知识

转载一篇很详细介绍四种引用的文章

原文地址：http://weblogs.java.net/blog/enicholas/archive/2006/05/understanding_w.html

Strong references

First I need to start with a refresher on strong references. A strong reference is an ordinary Java reference, the kind you use every day. For example, the code:

StringBuffer buffer = new StringBuffer();

creates a new StringBuffer() and stores a strong reference to it in the variable buffer. Yes, yes, this is kiddie stuff, but bear with me. The important part about strong references -- the part that makes them "strong" -- is how they interact with the garbage collector. Specifically, if an object is reachable via a chain of strong references (strongly reachable), it is not eligible for garbage collection. As you don't want the garbage collector destroying objects you're working on, this is normally exactly what you want.

When strong references are too strong

It's not uncommon for an application to use classes that it can't reasonably extend. The class might simply be marked final, or it could be something more complicated, such as an interface returned by a factory method backed by an unknown (and possibly even unknowable) number of concrete implementations. Suppose you have to use a class Widget and, for whatever reason, it isn't possible or practical to extend Widget to add new functionality.

What happens when you need to keep track of extra information about the object? In this case, suppose we find ourselves needing to keep track of each Widget's serial number, but the Widget class doesn't actually have a serial number property -- and because Widget isn't extensible, we can't add one. No problem at all, that's what HashMaps are for:

serialNumberMap.put(widget, widgetSerialNumber);

This might look okay on the surface, but the strong reference to widget will almost certainly cause problems. We have to know (with 100% certainty) when a particular Widget's serial number is no longer needed, so we can remove its entry from the map. Otherwise we're going to have a memory leak (if we don't remove Widgets when we should) or we're going to inexplicably find ourselves missing serial numbers (if we remove Widgets that we're still using). If these problems sound familiar, they should: they are exactly the problems that users of non-garbage-collected languages face when trying to manage memory, and we're not supposed to have to worry about this in a more civilized language like Java.

Another common problem with strong references is caching, particular with very large structures like images. Suppose you have an application which has to work with user-supplied images, like the web site design tool I work on. Naturally you want to cache these images, because loading them from disk is very expensive and you want to avoid the possibility of having two copies of the (potentially gigantic) image in memory at once.

Because an image cache is supposed to prevent us from reloading images when we don't absolutely need to, you will quickly realize that the cache should always contain a reference to any image which is already in memory. With ordinary strong references, though, that reference itself will force the image to remain in memory, which requires you (just as above) to somehow determine when the image is no longer needed in memory and remove it from the cache, so that it becomes eligible for garbage collection. Once again you are forced to duplicate the behavior of the garbage collector and manually determine whether or not an object should be in memory.

Weak references

A weak reference, simply put, is a reference that isn't strong enough to force an object to remain in memory. Weak references allow you to leverage the garbage collector's ability to determine reachability for you, so you don't have to do it yourself. You create a weak reference like this:

WeakReference<Widget> weakWidget = new WeakReference<Widget>(widget);

and then elsewhere in the code you can use weakWidget.get() to get the actual Widget object. Of course the weak reference isn't strong enough to prevent garbage collection, so you may find (if there are no strong references to the widget) that weakWidget.get() suddenly starts returningnull.

To solve the "widget serial number" problem above, the easiest thing to do is use the built-in WeakHashMap class. WeakHashMap works exactly likeHashMap, except that the keys (not the values!) are referred to using weak references. If a WeakHashMap key becomes garbage, its entry is removed automatically. This avoids the pitfalls I described and requires no changes other than the switch from HashMap to a WeakHashMap. If you're following the standard convention of referring to your maps via the Map interface, no other code needs to even be aware of the change.

Reference queues

Once a WeakReference starts returning null, the object it pointed to has become garbage and the WeakReference object is pretty much useless. This generally means that some sort of cleanup is required; WeakHashMap, for example, has to remove such defunct entries to avoid holding onto an ever-increasing number of dead WeakReferences.

The ReferenceQueue class makes it easy to keep track of dead references. If you pass a ReferenceQueue into a weak reference's constructor, the reference object will be automatically inserted into the reference queue when the object to which it pointed becomes garbage. You can then, at some regular interval, process the ReferenceQueue and perform whatever cleanup is needed for dead references.

Different degrees of weakness

Up to this point I've just been referring to "weak references", but there are actually four different degrees of reference strength: strong, soft, weak, and phantom, in order from strongest to weakest. We've already discussed strong and weak references, so let's take a look at the other two.

Soft references

A soft reference is exactly like a weak reference, except that it is less eager to throw away the object to which it refers. An object which is only weakly reachable (the strongest references to it are WeakReferences) will be discarded at the next garbage collection cycle, but an object which is softly reachable will generally stick around for a while.

SoftReferences  aren't  required  to behave any differently than  WeakReferences , but in practice softly reachable objects are generally retained as long as memory is in plentiful supply. This makes them an excellent foundation for a cache, such as the image cache described above, since you can let the garbage collector worry about both how reachable the objects are (a strongly reachable object will  never  be removed from the cache) and how badly it needs the memory they are consuming.

Phantom references

A phantom reference is quite different than either SoftReference or WeakReference. Its grip on its object is so tenuous that you can't even retrieve the object -- its get() method always returns null. The only use for such a reference is keeping track of when it gets enqueued into aReferenceQueue, as at that point you know the object to which it pointed is dead. How is that different from WeakReference, though?

The difference is in exactly when the enqueuing happens. WeakReferences are enqueued as soon as the object to which they point becomes weakly reachable. This is before finalization or garbage collection has actually happened; in theory the object could even be "resurrected" by an unorthodoxfinalize() method, but the WeakReference would remain dead. PhantomReferences are enqueued only when the object is physically removed from memory, and the get() method always returns null specifically to prevent you from being able to "resurrect" an almost-dead object.

What good are PhantomReferences? I'm only aware of two serious cases for them: first, they allow you to determine exactly when an object was removed from memory. They are in fact the only way to determine that. This isn't generally that useful, but might come in handy in certain very specific circumstances like manipulating large images: if you know for sure that an image should be garbage collected, you can wait until it actually is before attempting to load the next image, and therefore make the dreaded OutOfMemoryError less likely.

Second, PhantomReferences avoid a fundamental problem with finalization: finalize() methods can "resurrect" objects by creating new strong references to them. So what, you say? Well, the problem is that an object which overrides finalize() must now be determined to be garbage in at least two separate garbage collection cycles in order to be collected. When the first cycle determines that it is garbage, it becomes eligible for finalization. Because of the (slim, but unfortunately real) possibility that the object was "resurrected" during finalization, the garbage collector has to run again before the object can actually be removed. And because finalization might not have happened in a timely fashion, an arbitrary number of garbage collection cycles might have happened while the object was waiting for finalization. This can mean serious delays in actually cleaning up garbage objects, and is why you can get OutOfMemoryErrors even when most of the heap is garbage.

With PhantomReference, this situation is impossible -- when a PhantomReference is enqueued, there is absolutely no way to get a pointer to the now-dead object (which is good, because it isn't in memory any longer). Because PhantomReference cannot be used to resurrect an object, the object can be instantly cleaned up during the first garbage collection cycle in which it is found to be phantomly reachable. You can then dispose whatever resources you need to at your convenience.

Arguably, the finalize() method should never have been provided in the first place. PhantomReferences are definitely safer and more efficient to use, and eliminating finalize() would have made parts of the VM considerably simpler. But, they're also more work to implement, so I confess to still using finalize() most of the time. The good news is that at least you have a choice.

2、WeakHashMap的介绍

java.util 
Class WeakHashMap

java.lang.Object
  java.util.AbstractMap
      java.util.WeakHashMap

All Implemented Interfaces:

Map

---

public class  WeakHashMap

extends  AbstractMap

implements  Map

A hashtable-based Map implementation with weak keys. An entry in a WeakHashMap will automatically be removed when its key is no longer in ordinary use. More precisely, the presence of a mapping for a given key will not prevent the key from being discarded by the garbage collector, that is, made finalizable, finalized, and then reclaimed. When a key has been discarded its entry is effectively removed from the map, so this class behaves somewhat differently than other Map implementations.

Both null values and the null key are supported. This class has performance characteristics similar to those of the HashMap class, and has the same efficiency parameters of initial capacity and load factor.

Like most collection classes, this class is not synchronized. A synchronized WeakHashMap may be constructed using the Collections.synchronizedMap method.

This class is intended primarily for use with key objects whose equals methods test for object identity using the == operator. Once such a key is discarded it can never be recreated, so it is impossible to do a lookup of that key in a WeakHashMap at some later time and be surprised that its entry has been removed. This class will work perfectly well with key objects whose equals methods are not based upon object identity, such as String instances. With such recreatable key objects, however, the automatic removal of WeakHashMap entries whose keys have been discarded may prove to be confusing.

The behavior of the WeakHashMap class depends in part upon the actions of the garbage collector, so several familiar (though not required) Map invariants do not hold for this class. Because the garbage collector may discard keys at any time, a WeakHashMap may behave as though an unknown thread is silently removing entries. In particular, even if you synchronize on a WeakHashMap instance and invoke none of its mutator methods, it is possible for the size method to return smaller values over time, for the isEmpty method to return false and then true, for the containsKey method to return true and later false for a given key, for the get method to return a value for a given key but later return null, for the put method to return null and the remove method to return false for a key that previously appeared to be in the map, and for successive examinations of the key set, the value set, and the entry set to yield successively smaller numbers of elements.

Each key object in a WeakHashMap is stored indirectly as the referent of a weak reference. Therefore a key will automatically be removed only after the weak references to it, both inside and outside of the map, have been cleared by the garbage collector.

Implementation note: The value objects in a WeakHashMap are held by ordinary strong references. Thus care should be taken to ensure that value objects do not strongly refer to their own keys, either directly or indirectly, since that will prevent the keys from being discarded. Note that a value object may refer indirectly to its key via the WeakHashMap itself; that is, a value object may strongly refer to some other key object whose associated value object, in turn, strongly refers to the key of the first value object. One way to deal with this is to wrap values themselves within WeakReferences before inserting, as in: m.put(key, new WeakReference(value)), and then unwrapping upon each get.

The iterators returned by all of this class's "collection view methods" are fail-fast: if the map is structurally modified at any time after the iterator is created, in any way except through the iterator's own remove or add methods, the iterator will throw a ConcurrentModificationException. Thus, in the face of concurrent modification, the iterator fails quickly and cleanly, rather than risking arbitrary, non-deterministic behavior at an undetermined time in the future.

Note that the fail-fast behavior of an iterator cannot be guaranteed as it is, generally speaking, impossible to make any hard guarantees in the presence of unsynchronized concurrent modification. Fail-fast iterators throw ConcurrentModificationException on a best-effort basis. Therefore, it would be wrong to write a program that depended on this exception for its correctness: the fail-fast behavior of iterators should be used only to detect bugs.

This class is a member of the Java Collections Framework.