本文基于jdk1.8进行分析
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。
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
|
/** * hash table based implementation of the <tt>map</tt> interface. this * implementation provides all of the optional map operations, and permits * <tt>null</tt> values and the <tt>null</tt> key. (the <tt>hashmap</tt> * class is roughly equivalent to <tt>hashtable</tt>, 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. * <p>this implementation provides constant-time performance for the basic * operations (<tt>get</tt> and <tt>put</tt>), assuming the hash function * disperses the elements properly among the buckets. iteration over * collection views requires time proportional to the "capacity" of the * <tt>hashmap</tt> 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. * <p>an instance of <tt>hashmap</tt> has two parameters that affect its * performance: <i>initial capacity</i> and <i>load factor</i>. the * <i>capacity</i> 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 * <i>load factor</i> 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 <i>rehashed</i> (that is, internal data * structures are rebuilt) so that the hash table has approximately twice the * number of buckets. * <p>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 <tt>hashmap</tt> class, including * <tt>get</tt> and <tt>put</tt>). 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. * <p>if many mappings are to be stored in a <tt>hashmap</tt> * 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. * <p><strong>note that this implementation is not synchronized.</strong> * if multiple threads access a hash map concurrently, and at least one of * the threads modifies the map structurally, it <i>must</i> 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:<pre> * map m = collections.synchronizedmap(new hashmap(...));</pre> * <p>the iterators returned by all of this class's "collection view methods" * are <i>fail-fast</i>: if the map is structurally modified at any time after * the iterator is created, in any way except through the iterator's own * <tt>remove</tt> 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. * <p>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 <tt>concurrentmodificationexception</tt> on a best-effort basis. * therefore, it would be wrong to write a program that depended on this * exception for its correctness: <i>the fail-fast behavior of iterators * should be used only to detect bugs.</i> * <p>this class is a member of the * <a href="{@docroot}/../technotes/guides/collections/index.html" rel="external nofollow" > * java collections framework</a>. * @param <k> the type of keys maintained by this map * @param <v> 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,谢谢大家对服务器之家的支持。如果你想了解更多相关内容请查看下面相关链接
原文链接:https://blog.csdn.net/li_canhui/article/details/85076521