Java源码解析HashMap简介

本文基于jdk1.8进行分析

10年积累的成都做网站、成都网站设计经验,可以快速应对客户对网站的新想法和需求。提供各种问题对应的解决方案。让选择我们的客户得到更好、更有力的网络服务。我虽然不认识你,你也不认识我。但先制作网站后付款的网站建设流程,更有龙港免费网站建设让你可以放心的选择与我们合作。

HashMap是java开发中可以说必然会用到的一个集合。本文就HashMap的源码实现进行分析。

首先看一下源码中类的javadoc注释对HashMap的解释。如下图。HashMap是对Map接口的基于hash表的实现。这个实现提供了map的所有可选操作,并且允许null值(可以多个)和一个null的key(仅限一个)。HashMap和HashTable十分相似,除了HashMap是非同步的且允许null元素。这个类不保证map里的顺序,更进一步,随着时间的推移,它甚至不保证顺序一直不变。

这个实现为get和put这样的基本操作提供常量级性能,它假设hash函数把元素们比较好的分散到各个桶里。用迭代器遍历集合需要的时间,和HashMap的容量与HashMap里的Entry数量的和成正比。所以,如果遍历性能很重要的话,一定不要把初始容量设置的太大,或者把负载因子设置的太小。

一个hashmap有两个影响它的性能的参数,初始容量和负载因子。容量是哈希表中桶的数量,初始容量就是创建哈希表时桶的数量。负载银子是哈希表的容量自动扩容前哈希表能够达到多满。当哈希表中条目的数量超过当前容量和负载因子的乘积后,哈希表会进行重新哈希(也就是,内部数据结构重建),以使哈希表大约拥有2倍数量的桶。

作为一个通常的规则,默认负载银子(0.75) 提供了一个时间和空间的比较好的平衡。更高的负载因子会降低空间消耗但是会增加查找的消耗。当设置初始容量时,哈希表中期望的条目数量和它的负载因子应该考虑在内,以尽可能的减小重新哈希的次数。如果初始容量比条目最大数量除以负载因子还大,那么重新哈希操作就不会发生。

如果许多entry需要存储在哈希表中,用能够容纳entry的足够大的容量来创建哈希表,比让它在需要的时候自动扩容更有效率。请注意,使用多个hash值相等的key肯定会降低任何哈希表的效率。

请注意这个实现不是同步的。如果多个线程同时访问哈希表,并且至少有一个线程会修改哈希表的结构,那么哈希表外部必须进行同步。

/**
 * Hash table based implementation of the Map interface. This
 * implementation provides all of the optional map operations, and permits
 * null values and the null key. (The HashMap
 * class is roughly equivalent to Hashtable, except that it is
 * unsynchronized and permits nulls.) This class makes no guarantees as to
 * the order of the map; in particular, it does not guarantee that the order
 * will remain constant over time.
 * 

This implementation provides constant-time performance for the basic * operations (get and put), assuming the hash function * disperses the elements properly among the buckets. Iteration over * collection views requires time proportional to the "capacity" of the * HashMap instance (the number of buckets) plus its size (the number * of key-value mappings). Thus, it's very important not to set the initial * capacity too high (or the load factor too low) if iteration performance is * important. *

An instance of HashMap has two parameters that affect its * performance: initial capacity and load factor. The * capacity is the number of buckets in the hash table, and the initial * capacity is simply the capacity at the time the hash table is created. The * load factor is a measure of how full the hash table is allowed to * get before its capacity is automatically increased. When the number of * entries in the hash table exceeds the product of the load factor and the * current capacity, the hash table is rehashed (that is, internal data * structures are rebuilt) so that the hash table has approximately twice the * number of buckets. *

As a general rule, the default load factor (.75) offers a good * tradeoff between time and space costs. Higher values decrease the * space overhead but increase the lookup cost (reflected in most of * the operations of the HashMap class, including * get and put). The expected number of entries in * the map and its load factor should be taken into account when * setting its initial capacity, so as to minimize the number of * rehash operations. If the initial capacity is greater than the * maximum number of entries divided by the load factor, no rehash * operations will ever occur. *

If many mappings are to be stored in a HashMap * instance, creating it with a sufficiently large capacity will allow * the mappings to be stored more efficiently than letting it perform * automatic rehashing as needed to grow the table. Note that using * many keys with the same {@code hashCode()} is a sure way to slow * down performance of any hash table. To ameliorate impact, when keys * are {@link Comparable}, this class may use comparison order among * keys to help break ties. *

Note that this implementation is not synchronized. * If multiple threads access a hash map concurrently, and at least one of * the threads modifies the map structurally, it must be * synchronized externally. (A structural modification is any operation * that adds or deletes one or more mappings; merely changing the value * associated with a key that an instance already contains is not a * structural modification.) This is typically accomplished by * synchronizing on some object that naturally encapsulates the map. * If no such object exists, the map should be "wrapped" using the * {@link Collections#synchronizedMap Collections.synchronizedMap} * method. This is best done at creation time, to prevent accidental * unsynchronized access to the map:

 *  Map m = Collections.synchronizedMap(new HashMap(...));
*

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 method, the iterator will throw a * {@link 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. * @param the type of keys maintained by this map * @param the type of mapped values * @author Doug Lea * @author Josh Bloch * @author Arthur van Hoff * @author Neal Gafter * @see Object#hashCode() * @see Collection * @see Map * @see TreeMap * @see Hashtable * @since 1.2 **/

This is the end。

总结

以上就是这篇文章的全部内容了,希望本文的内容对大家的学习或者工作具有一定的参考学习价值,谢谢大家对创新互联的支持。如果你想了解更多相关内容请查看下面相关链接


网页标题:Java源码解析HashMap简介
文章链接:http://azwzsj.com/article/pioiid.html