hashMap原理解析

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        我们都知道,在hashMap中不论是计算key的hashcode还是为了使得hashMap中元素分布更均匀的场景,hash算法的能力都不可低估。今天,小编就和大家一起来分享在hashMap中hash算法的研究:

        在述说原理之前,我们先来看一个hash算法在生活中的例子:

        在某农场A,主人养了50头小猪,由于在生长期,主人需要定期地根据每头小猪的体重调整它们的“宿舍”,假设现在有10个猪舍(每个猪舍都有体重的范围),那么主人需要根据每头小猪的体重来分猪舍。这样,每头小猪都有了自己的住处,而且这种方法相当于主人对当前这50头小猪进行了分类,甚至是排序。当某一天,主人需要找某一头时只需要知道它的体重是多少,就可以很快的定位到它的位置,在确定的猪舍中进行查找会很快捷并且方便,就不需要对50头小猪都进行排查。

       其实这就是一个hash算法的实现过程,在hashmap中,当我们put某一个元素时,hashMap内部会做几层操作:计算当前key的hashCode --> 获取该key在数组中的index --> 把key放置到确定好的数组 index对应的链表头部:

/**     * Associates the specified value with the specified key in this map.     * If the map previously contained a mapping for the key, the old     * value is replaced.     *     * @param key key with which the specified value is to be associated     * @param value value to be associated with the specified key     * @return the previous value associated with <tt>key</tt>, or     *         <tt>null</tt> if there was no mapping for <tt>key</tt>.     *         (A <tt>null</tt> return can also indicate that the map     *         previously associated <tt>null</tt> with <tt>key</tt>.)     */    public V put(K key, V value) {        if (table == EMPTY_TABLE) {            inflateTable(threshold);        }        if (key == null)            return putForNullKey(value);        int hash = hash(key);        int i = indexFor(hash, table.length);        for (Entry<K,V> e = table[i]; e != null; e = e.next) {            Object k;            if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {                V oldValue = e.value;                e.value = value;                e.recordAccess(this);                return oldValue;            }        }        modCount++;        addEntry(hash, key, value, i);        return null;    }
      其中涉及到求hashCode,根据code和数组长度-1 计算出的index值和添加当前元素到hashmap 中三步:

/**     * Retrieve object hash code and applies a supplemental hash function to the     * result hash, which defends against poor quality hash functions.  This is     * critical because HashMap uses power-of-two length hash tables, that     * otherwise encounter collisions for hashCodes that do not differ     * in lower bits. Note: Null keys always map to hash 0, thus index 0.     */    final int hash(Object k) {        int h = hashSeed;        if (0 != h && k instanceof String) {            return sun.misc.Hashing.stringHash32((String) k);        }        h ^= k.hashCode();        // This function ensures that hashCodes that differ only by        // constant multiples at each bit position have a bounded        // number of collisions (approximately 8 at default load factor).        h ^= (h >>> 20) ^ (h >>> 12);        return h ^ (h >>> 7) ^ (h >>> 4);    }

/**     * Returns index for hash code h.     */    static int indexFor(int h, int length) {        // assert Integer.bitCount(length) == 1 : "length must be a non-zero power of 2";        return h & (length-1);    }    

/**     * Adds a new entry with the specified key, value and hash code to     * the specified bucket.  It is the responsibility of this     * method to resize the table if appropriate.     *     * Subclass overrides this to alter the behavior of put method.     */    void addEntry(int hash, K key, V value, int bucketIndex) {        if ((size >= threshold) && (null != table[bucketIndex])) {            resize(2 * table.length);            hash = (null != key) ? hash(key) : 0;            bucketIndex = indexFor(hash, table.length);        }        createEntry(hash, key, value, bucketIndex);    }       

      上述四段代码就是把每一只称过体重的小猪按照体重的范围,分配猪舍的过程。这样,我们可以保证每只小猪都已经有了很好的归属,而在所有的猪舍中由于体重分布不一定均匀,所有可能会出现某猪舍中有10头小猪,而某猪舍中只有两头,而这种场景在hashMap中的体现就是链表,如果有key相同的也就是hashMap中的碰撞现象,就将当前key插入到链表的头部,这样久而久之就形成了一个链表。也就是hashMap的数据结构:数组+链表!