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);
List list1 =
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
