• 二分查找


    @Test
    public void testBinSearch() {
        int[] i = {1, 3, 5, 6, 8};
        int[] r1 = {bS1(i, 0), bS1(i, 1), bS1(i, 3), bS1(i, 6), bS1(i, 8), bS1(i, 9)};
        System.out.println(Arrays.toString(r1));
        System.out.println("--------------------");
        int[] r2 = {bS2(i, 0), bS2(i, 1), bS2(i, 3), bS2(i, 6), bS2(i, 8), bS2(i, 9)};
        System.out.println(Arrays.toString(r2));
        System.out.println("--------------------");
        int[] r3 = {bS3(i, 0), bS3(i, 1), bS3(i, 3), bS3(i, 6), bS3(i, 8), bS3(i, 9)};
        System.out.println(Arrays.toString(r3));
        System.out.println("--------------------");
        int[] r4 = {bS4(i, 0), bS4(i, 1), bS4(i, 3), bS4(i, 6), bS4(i, 8), bS4(i, 9)};
        System.out.println(Arrays.toString(r4));
    }
    
    public int bS1(int[] nums, int target) {
        int left = 0;
        int right = nums.length - 1;
        // 终止条件[right + 1, right],此时搜索区间为空
        while (left <= right) {
            int mid = left + ((right - left) >> 1);
            if (nums[mid] == target) return mid;
            if (nums[mid] < target) left = mid + 1;
            if (nums[mid] > target) right = mid - 1;
        }
        return -1;
    }
    
    public int bS2(int[] nums, int target) {
        int left = 0;
        int right = nums.length; // 右边界初始为length,取不到
        // 终止条件[right, right],此时搜索区间非空,但右边界不可能为target
        while (left < right) {
            int mid = left + ((right - left) >> 1);
            if (nums[mid] == target) return mid;
            if (nums[mid] < target) left = mid + 1;
            if (nums[mid] > target) right = mid; // right边界永远不可能为target,不需要对结果打补丁
        }
        return -1;
    }
    
    public int bS3(int[] nums, int target) {
        int left = 0;
        int right = nums.length - 1; // 右边界初始为最后一个元素
        // 终止条件[right, right],此时搜索区间非空,且右边界可能为target,需要对单独最后一个元素进行判断
        while (left < right) {
            int mid = left + ((right - left) >> 1);
            if (nums[mid] == target) return mid;
            if (nums[mid] < target) left = mid + 1;
            if (nums[mid] > target) right = mid - 1; // right边界有可能为target,需要对结果打补丁
        }
        return nums[left] == target ? left : -1;
    }
    
    public int bS4(int[] nums, int target) {
        int left = 0;
        int right = nums.length; // 右边界初始为length,有可能有边界从始至终都没有变化,需要单独处理
        // 终止条件[right, right],此时搜索区间非空,且右边界可能为target,需要对单独最后一个元素进行判断
        while (left < right) {
            int mid = left + ((right - left) >> 1);
            if (nums[mid] == target) return mid;
            if (nums[mid] < target) left = mid + 1;
            if (nums[mid] > target) right = mid - 1; // right边界有可能为target,需要对结果打补丁
        }
        if (right == nums.length) return -1;
        return nums[left] == target ? left : -1;
    }
    
    @Test
    public void testBinSearchPlus() {
        int[] nums = {1, 2, 2, 2, 3};
        int[] r1 = {bSL(nums, 0), bSL(nums, 1), bSL(nums, 2), bSL(nums, 3), bSL(nums, 4)};
        System.out.println(Arrays.toString(r1));
        System.out.println("-----------------");
        int[] r2 = {bSR(nums, 0), bSR(nums, 1), bSR(nums, 2), bSR(nums, 3), bSR(nums, 4)};
        System.out.println(Arrays.toString(r2));
    }
    
    // 最左侧的target
    public int bSL(int[] nums, int target) {
        int left = 0;
        int right = nums.length;
        while (left < right) { // 结束条件left == right
            int mid = left + ((right - left) >> 1);
            if (nums[mid] >= target) right = mid; // 右边界可能为target
            if (nums[mid] < target) left = mid + 1; // 左边界依次逼近右边界
        }
        if (left == nums.length) return -1;
        return nums[left] == target ? left : -1;
    }
    
    // 最右侧的target
    public int bSR(int[] nums, int target) {
        int left = 0;
        int right = nums.length;
        while (left < right) {
            int mid = left + ((right - left) >> 1);
            if (nums[mid] <= target) left = mid + 1; // 左边界的左侧可能为target
            if (nums[mid] > target) right = mid;
        }
        if (left == 0) return -1;
        return nums[left - 1] == target ? left - 1 : -1;
    }
    

      

  • 相关阅读:
    Linux 性能优化之 IO 子系统
    Percona 开始尝试基于Ceph做上层感知的分布式 MySQL 集群,使用 Ceph 提供的快照,备份和 HA 功能来解决分布式数据库的底层存储问题
    Ceph常用维护操作
    linux系统数据落盘之细节
    Ceph: validate that the RBD cache is active
    linux初始化
    GlusterFS 安装
    GlusterFS常用设置命令
    kubernetes --- Glusterfs
    kubernetes --- weave
  • 原文地址:https://www.cnblogs.com/oumae/p/15484335.html
Copyright © 2020-2023  润新知