ArrayList
1.基于数组,需要连续内存
2.随机访问快(指根据下标访问,不是根据内容访问)
3.尾部插入,删除性能可以,其它部分插入,删除都会移动数据,因此性能会低
4.可以利用cpu缓存,局部性原理
linkedList
1.基于双向链表,无需连续内存
2.随机访问慢(要沿着链表遍历)
3.头尾插入删除性能高
4.占用内存多
关于往头部,中间,尾部add的 demo代码:
public static void main(String[] args) { int n = 1000; int insertIndex = n; for (int i = 0; i < 1; i++) { //randomArray生面随机数组,这里意思是1000个随机数 int[] array = randomArray(n); Listlist1 = Arrays.stream(array).boxed().collect(Collectors.toList()); linkedList list2 = new linkedList<>(list1); addFirst(list1,list2); addMiddle(list1, list2, n / 2); addLast(list1,list2); arrayListSize((ArrayList ) list1); linkedListSize(list2); } } private static void addMiddle(List list1, linkedList list2, int mid) { StopWatch sw = new StopWatch(); sw.start("ArrayList"); list1.add(mid, 100); sw.stop(); sw.start("linkedList"); list2.add(mid, 100); sw.stop(); System.out.println(sw.prettyPrint()); } private static void addFirst(List list1, linkedList list2) { StopWatch sw = new StopWatch(); sw.start("ArrayList"); list1.add(0, 100); sw.stop(); sw.start("linkedList"); list2.addFirst(100); sw.stop(); System.out.println(sw.prettyPrint()); } private static void addLast(List list1, linkedList list2) { StopWatch sw = new StopWatch(); sw.start("ArrayList"); list1.add(100); sw.stop(); sw.start("linkedList"); list2.add(100); sw.stop(); System.out.println(sw.prettyPrint()); }
执行往头部addFirst插入的运行截图如下:linkedList的效率比ArrayList的效率好很多
Connected to the target VM, address: '127.0.0.1:59369', transport: 'socket' StopWatch '': running time = 81898 ns --------------------------------------------- ns % Task name --------------------------------------------- 000073599 090% ArrayList 000008299 010% linkedList Disconnected from the target VM, address: '127.0.0.1:59369', transport: 'socket' Process finished with exit code 0
执行往中间addMiddle插入的运行结果: linkedList效率并不是很高,因为插入前要遍历
Connected to the target VM, address: '127.0.0.1:62319', transport: 'socket' StopWatch '': running time = 5230109099 ns --------------------------------------------- ns % Task name --------------------------------------------- 1677949199 032% ArrayList 3552159900 068% linkedList
往最后插入运行截图:
ns % Task name --------------------------------------------- 000027600 087% ArrayList 000004200 013% linkedList
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