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HashMap小记

程序员文章站 2022-04-22 11:39:43
HashMap小记HashMap线程不安全,ConcurrentHashMap线程安全1.7HashMap数组+链表数组查询快,插入慢;链表插入删除快,查询慢先了解一下里面定义的一些变量static final int DEFAULT_INITIAL_CAPACITY = 16;//默认初始容量大小 static final int MAXIMUM_CAPACITY = 1073741824;//最大容量 static final float DEFAULT_LOAD_FACTO...

HashMap小记

HashMap线程不安全,ConcurrentHashMap线程安全

1.7HashMap

数组+链表
数组查询快,插入慢;链表插入删除快,查询慢

先了解一下里面定义的一些变量

static final int DEFAULT_INITIAL_CAPACITY = 16;//默认初始容量大小
    static final int MAXIMUM_CAPACITY = 1073741824;//最大容量
    static final float DEFAULT_LOAD_FACTOR = 0.75F;//加载因子
    static final HashMap.Entry<?, ?>[] EMPTY_TABLE = new HashMap.Entry[0];//存储的对象
    transient HashMap.Entry<K, V>[] table;//数组
    transient int size;//大小
    int threshold;//阀值
    final float loadFactor;//负荷系数
    transient int modCount;//计数
    static final int ALTERNATIVE_HASHING_THRESHOLD_DEFAULT = 2147483647;//哈希阀值
    transient int hashSeed;
    private transient Set<java.util.Map.Entry<K, V>> entrySet;
    private static final long serialVersionUID = 362498820763181265L;

HashMap小记

put(k,v)插入方式:头插法

public V put(K var1, V var2) {
        if (this.table == EMPTY_TABLE) {
            this.inflateTable(this.threshold);
        }

        if (var1 == null) {//如果k为空,直接放到:this.table[0]
            return this.putForNullKey(var2);
        } else {
            int var3 = this.hash(var1);//生成hashcode
            int var4 = indexFor(var3, this.table.length);//找到插入位置
            //直接放到头部,如果头部有值了,值往下移var5 = var5.next
            for(HashMap.Entry var5 = this.table[var4]; var5 != null; var5 = var5.next) {
                Object var6;
                if (var5.hash == var3 && ((var6 = var5.key) == var1 || var1.equals(var6))) {
                    Object var7 = var5.value;
                    var5.value = var2;
                    var5.recordAccess(this);
                    return var7;
                }
            }

            ++this.modCount;
            this.addEntry(var3, var1, var2, var4);
            return null;
        }
    }
private V putForNullKey(V var1) {
        for(HashMap.Entry var2 = this.table[0]; var2 != null; var2 = var2.next) {
            if (var2.key == null) {
                Object var3 = var2.value;
                var2.value = var1;
                var2.recordAccess(this);
                return var3;
            }
        }
        ++this.modCount;
        this.addEntry(0, (Object)null, var1, 0);
        return null;
    }

扩容:1.7先扩容,再添加

为什么要扩容?

不扩容,链表会非常长,遍历效率会慢

void addEntry(int var1, K var2, V var3, int var4) {
		//如果size大小大于或等于临界值(阀值),添加的不是空,就扩容
        if (this.size >= this.threshold && null != this.table[var4]) {
        	//两倍扩容
            this.resize(2 * this.table.length);
            var1 = null != var2 ? this.hash(var2) : 0;
            var4 = indexFor(var1, this.table.length);
        }
		//添加
        this.createEntry(var1, var2, var3, var4);
    }

    void createEntry(int var1, K var2, V var3, int var4) {
        HashMap.Entry var5 = this.table[var4];
        this.table[var4] = new HashMap.Entry(var1, var2, var3, var5);
        ++this.size;
    }

注:可能会出现死循环
HashMap小记

1.8HashMap

数组+链表+红黑树

为什么使用红黑树,什么时候使用红黑树?

  • 红黑树的插入与查询的效率最平衡
  • 当链表长度大于等于TREEIFY_THRESHOLD(树化阀值:8)时,树化
  • 初始TREEIFY_THRESHOLD为8;因为根据泊松分步,链表长度大于8的概率已经很低了
  • 红黑树链化:当进行移除操作后,达到UNTREEIFY_THRESHOLD(链化阀值:6)时,链化
  • 如果一小于8就链化,效率比较低,切树化和链化操作会很频繁
 /**默认初始大小*/
    static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16

    /**最大容量 */
    static final int MAXIMUM_CAPACITY = 1 << 30;

    /**树化阀值 */
    static final int TREEIFY_THRESHOLD = 8;

    /**链化阀值 */
    static final int UNTREEIFY_THRESHOLD = 6;

    /* 最小负载容量,当数组达到64,且满足树化阀值时才将链表树化*/
    static final int MIN_TREEIFY_CAPACITY = 64;

put(K,V):尾插法

看一段源码

public V put(K key, V value) {
        return putVal(hash(key), key, value, false, true);
    }

    /**
     * Implements Map.put and related methods.
     * @param hash hash for key
     * @param key the key
     * @param value the value to put
     * @param onlyIfAbsent if true, don't change existing value
     * @param evict if false, the table is in creation mode.
     * @return previous value, or null if none
     */
    final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, i;
        if ((tab = table) == null || (n = tab.length) == 0)
            n = (tab = resize()).length;
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
        else {
            Node<K,V> e; K k;
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode)
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {
            	//遍历链表
                for (int binCount = 0; ; ++binCount) {
                    if ((e = p.next) == null) {
                    	//在尾部插入
                        p.next = newNode(hash, key, value, null);
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st大于阀值-1;树化,但并不是真正的树化,里面还有判断
                            treeifyBin(tab, hash);
                        break;
                    }
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }

从源码可以得知:它在遍历时,遍历结束后,顺便把put的的值放入链尾

扩容:先插入再扩容

扩容源码

final Node<K,V>[] resize() {
        Node<K,V>[] oldTab = table;
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        int oldThr = threshold;
        int newCap, newThr = 0;
        if (oldCap > 0) {
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }
            else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                     oldCap >= DEFAULT_INITIAL_CAPACITY)
                newThr = oldThr << 1; // double threshold
        }
        else if (oldThr > 0) // initial capacity was placed in threshold
            newCap = oldThr;
        else {               // zero initial threshold signifies using defaults
            newCap = DEFAULT_INITIAL_CAPACITY;
            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
        }
        if (newThr == 0) {
            float ft = (float)newCap * loadFactor;
            newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
                      (int)ft : Integer.MAX_VALUE);
        }
        threshold = newThr;
        @SuppressWarnings({"rawtypes","unchecked"})
        Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
        table = newTab;
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
                            next = e.next;
                            //对原链表进行分组,等于0还在原来的数组下标,等于1,原下标+原容量
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            else {
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }

问题1:为什么hashMap每次扩容为之前的两倍(即以2的幂次方扩容)

看一段源码

final int hash(Object var1) {
        int var2 = this.hashSeed;
        if (0 != var2 && var1 instanceof String) {
            return Hashing.stringHash32((String)var1);
        } else {
            var2 ^= var1.hashCode();
            var2 ^= var2 >>> 20 ^ var2 >>> 12;
            return var2 ^ var2 >>> 7 ^ var2 >>> 4;
        }
    }

    static int indexFor(int var0, int var1) {
        return var0 & var1 - 1;
    }

indexFor方法中使用生成的hashcode与数组大小-1;进行与&比较
这里面已经把他们转换为了2进制;

16: 0001 0000

var0: 1011 0101

16-1: 0000 1111

&: 0000 0101

这保证了,插入数据的下标一定在数组容量中,而这也是它需要每次以2的幂次方扩容的原因

为什么hashcode需要进行右移和异或处理

var2 ^= var1.hashCode();
var2 ^= var2 >>> 20 ^ var2 >>> 12;
return var2 ^ var2 >>> 7 ^ var2 >>> 4;

这可以减少哈希碰撞,减少某个链表过长的情况,使get(K)不至于太慢

加载因子有什么用

加载因子也叫作扩容因子,用来判断什么时候进行扩容,假设加载因子为0.75,HashMap的初始容量为16,当HashMap中有16 * 0.75 = 12个容量时,HashMap就会进行扩容。

如果加载因子越大,扩容发生的频率就会比较低,占用空间比较小,但是发生hash冲突的几率会提升,对元素操作时间会增加,运行效率降低;

如果加载因子太小,那么表中的数据将过于稀疏(很多空间还没用,就开始扩容了),对空间造成严重浪费;

而且因为容量默认为2的次方,当加载因子为0.75时,容量和加载因子的乘积为整数。

所以系统默认加载因子取了0.5 -1 之间的0.75

本文地址:https://blog.csdn.net/qq_41510551/article/details/109271108