for(int i=0;i<msg.length();i++){ String value=map.get(msg.charAt(i)); if(value!=null){ sb.append(value); }else{ System.out.println(“包含不能识别的字符”); break; } } if(sb.length()==msg.length()*2){ System.out.println(“原文”+msg); System.out.println(“密文”+sb.t...
HashMap有多个构造函数,但是从源码可以看出,构造方法的处理逻辑都是设置了HashMap的属性loadFactor和threshold的值,初始化时的threshold的值实际就是通过计算数组长度的tableSizeFor方法计算出来的 这里有一个tableSizeFor方法,该方法的作用是根据传入参数计算比参数大的最近一个2的幂次方的值。比如传入10,那么比10大的最...
AI代码解释 //创建HashMap集合的对象,指定数组长度是10,不是2的幂HashMap hashMap=newHashMap(10);publicHashMap(int initialCapacity){//initialCapacity=10this(initialCapacity,DEFAULT_LOAD_FACTOR);}publicHashMap(int initialCapacity,float loadFactor){//initialCapacity=10if(initialCapacity<0)thrownewIllegalArgume...
* Ideally, under random hashCodes, the frequency of * nodes in bins follows a Poisson distribution * (http://en.wikipedia.org/wiki/Poisson_distribution) with a * parameter of about 0.5 on average for the default resizing * threshold of 0.75, although with a large variance because of * res...
笔者在Java的基本数据类型、拆装箱(深入版)介绍过,int类型的数据所占空间大小为32位,所以如果超过这个范围之后,会出现溢出。所以,1<<30是在int类型取值范围中2次幂的最大值,即为HashMap的容量最大值。 2.2. HashMap的加载因子为什么是0.75? 笔者在HashMap的加载因子为什么是0.75?有详细解答过,加载因子0.75是提高...
Ideally, under random hashCodes, the frequency of nodes in bins follows a Poisson distribution (http://en.wikipedia.org/wiki/Poisson_distribution) with a parameter of about 0.5 on average for the default resizing threshold of 0.75, although with a large variance because of ...
其中,key.hashCode()是Java中自带的hashCode()方法,返回一个int类型的散列值,后面hashCode再右移16位,正好是32bit的一半,与自己本身做异或操作(相同为0,不同为1),主要是为了混合哈希值的高位和低位,增加低位的随机性,这样就实现了HashMap的哈希算法。 总结 HashMap在JDK1.7时,使用的是数组+链表实现的,而在JDK...
Java8及以后的版本中,HashMap底层数据结构引入了红黑树,当添加元素的时候,如果桶中链表元素超过8,会自动转为红黑树。那么阈值为什么是8呢?来看HashMap源码中的这段注释: * Ideally, under random hashCodes, the frequency of * nodes in bins follows a Poisson distribution ...
the frequency of nodes in bins follows a Poissondistribution(http://en.wikipedia.org/wiki/Poisson_distribution)with a parameter of about0.5on averageforthedefaultresizing threshold of0.75, although with a large variance because of resizing granularity. Ignoring variance, ...
Ideally, under random hashCodes, the frequency of nodes in bins follows a Poisson distribution with a parameter of about 0.5 on average for the default resizing threshold of 0.75, although with a large variance because of resizing granularity. Ignoring variance, the expected occurrences of list siz...