柱状图中的最大矩形-leetcode87
思路
采用单调递增栈,元素前面的就是元素的左边界,将元素弹出的就是元素的右边界,
复杂度分析
时间复杂度:o(n)
空间复杂度:O(n)
代码
class Solution {
public int largestRectangleArea(int[] heights) {
int[] left = new int[heights.length];
int[] right = new int[heights.length];
Arrays.fill(right, heights.length);
Deque<Integer> heightDeque = new ArrayDeque<>();
Deque<Integer> indexDeque = new ArrayDeque<>();
for (int i = 0; i < heights.length; i++) {
while (heightDeque.peek() != null && heightDeque.peek() >= heights[i]) {
heightDeque.pop();
right[indexDeque.pop()] = i;
}
left[i] = indexDeque.peek() == null ? -1 : indexDeque.peek();
heightDeque.push(heights[i]);
indexDeque.push(i);
}
int result = 0;
for (int i = 0; i < right.length; i++) {
result = Math.max(result, heights[i] * (right[i] - left[i] - 1));
}
return result;
}
}
快速排序
最好时间复杂度:O(n*logn)
最坏时间复杂度:O(n^2)
平均:O(n*logn)
public static void quickSort(int[] arr, int start, int end) {
if (start >= end) {
return;
}
int pivot = arr[start];
int left = start + 1;
int right = end;
while (left <= right) {
while (left <= end && arr[left] < pivot) {
left++;
}
while (right > start && arr[right] >= pivot) {
right--;
}
if (right > left) {
int temp = arr[right];
arr[right] = arr[left];
arr[left] = temp;
}
}
arr[start] = arr[right];
arr[right] = pivot;
quickSort(arr, right + 1, end);
quickSort(arr, start, right - 1);
}
堆排序
最好最坏以及平均的时间复杂度都是O(logn * n)
空间复杂度是O(1)
非稳定排序
重点在于构造大堆
public static void heapSort(int[] arr) {
for (int i = arr.length / 2 - 1; i >= 0; i--) {
heapify(arr, i, arr.length);
}
for (int i = 0; i < arr.length; i++) {
sweap(arr, 0, arr.length - i - 1);
heapify(arr, 0, arr.length - i - 1);
}
}
public static void sweap(int[] arr, int left, int right) {
int temp = arr[left];
arr[left] = arr[right];
arr[right] = temp;
}
public static void heapify(int[] arr, int i, int length) {
int left = i * 2 + 1;
int right = i * 2 + 2;
int largest = i;
if (left < length && arr[left] > arr[largest]) {
largest = left;
}
if (right < length && arr[right] > arr[largest]) {
largest = right;
}
if (largest != i) {
int temp = arr[i];
arr[i] = arr[largest];
arr[largest] = temp;
heapify(arr, largest, length);
}
}
复习一下双重校验锁
public class Singleton {
// 使用volatile关键字确保多线程环境下的可见性
private static volatile Singleton instance;
// 私有构造函数,防止外部实例化
private Singleton() {
// 初始化代码(如果有)
}
/**
* 获取单例实例的方法
*
* @return 单例实例
*/
public static Singleton getInstance() {
// 第一次检查,避免不必要的同步
if (instance == null) {
// 同步块,确保只有一个线程可以进入
synchronized (Singleton.class) {
// 第二次检查,确保实例未被其他线程创建
if (instance == null) {
instance = new Singleton();
}
}
}
return instance;
}
// 其他方法
public void doSomething() {
System.out.println("Singleton instance is doing something.");
}
}
使用volatile的原因是防止指令重排
死锁
代码
package com.wll;
public class DeadLock {
private static final DeadLock d1 = new DeadLock();
private static final DeadLock d2 = new DeadLock();
public static void main(String[] args) {
deadLock();
}
public static void deadLock() {
Thread t = new Thread(() -> {
synchronized (d1) {
try {
System.out.println("T获得D1");
Thread.sleep(1000);
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
synchronized (d2) {
System.out.println("t等待D2");
}
}
});
Thread t1 = new Thread(() -> {
synchronized (d2) {
try {
System.out.println("T1获得D2");
Thread.sleep(100);
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
synchronized (d1) {
System.out.println("T1等待d1");
}
}
});
t.start();
t1.start();
}
}
Thread的run方法,是一个方法,调用这个方法的时候,并不会新起一个线程。
start方法会新起一个线程,不能多次调用