LintCode & LeetCode
  • Introduction
  • Linked List
    • Sort List
    • Merge Two Sorted Lists
    • Merge k Sorted Lists
    • Linked List Cycle
    • Linked List Cycle II
    • Add Two Numbers II
    • Add Two Numbers
    • Odd Even Linked List
    • Intersection of Two Linked Lists
    • Reverse Linked List
    • Reverse Linked List II
    • Remove Linked List Elements
    • Remove Nth Node From End of List
    • Middle of the Linked List
    • Design Linked List
      • Design Singly Linked List
      • Design Doubly Linked List
    • Palindrome Linked List
    • Remove Duplicates from Sorted List
    • Remove Duplicates from Sorted List II
    • Implement Stack Using Singly Linked List
    • Copy List with Random Pointer
  • Binary Search
    • Search in Rotated Sorted Array
    • Search in Rotated Sorted Array II
    • Search in a Sorted Array of Unknown Size
    • First Bad Version
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    • Find Minimum in Rotated Sorted Array II
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    • Search Insert Position
    • Peak Index in a Mountain Array
    • Heaters
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    • Subdomain Visit Count
    • Design HashMap
    • Design HashSet
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  • Array
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    • Maximum Subarray III
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    • Majority Element
    • Can Place Flowers
    • Candy
  • Matrix
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    • Set Matrix Zeroes
    • Diagonal Traverse
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    • Design Circular Queue
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    • Implement Stack using Queues
    • Moving Average from Data Stream
    • Walls and Gates
    • Open the Lock
    • Sliding Window Maximum
    • Implement Queue Using Fixed Length Array
    • Animal Shelter
  • Stack
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    • Longest Valid Parentheses
    • Min Stack
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    • Daily Temperatures
    • Evaluate Reverse Polish Notation
    • Next Greater Element I
    • Next Greater Element II
    • Next Greater Element III
    • Largest Rectangle in Histogram
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  • Heap
    • Trapping Rain Water II
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    • Kth Smallest Sum In Two Sorted Arrays
    • K Closest Points to the Origin
    • Merge K Sorted Lists
    • Merge K Sorted Arrays
    • Top K Frequent Words - Map Reduce
  • Data Structure & Design
    • Hash Function
    • Heapify
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    • Design Hit Counter
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    • Read N Characters Given Read4
    • Flatten 2D Vector
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    • Design Search Autocomplete System
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    • Design Tic-Tac-Toe
    • Insert Delete GetRandom O(1)
  • Union Find
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    • Graph Valid Tree
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    • Redundant Connection
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    • Implement Trie
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    • Word Search II
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    • Construct Binary Tree from Preorder and Inorder Traversal
    • Populating Next Right Pointers in Each Node
    • Populating Next Right Pointers in Each Node II
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    • Path Sum
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    • Path Sum III
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    • Same Tree
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    • Nested List Weight Sum II
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    • Minimum Distance (Difference) Between BST Nodes
    • Closet Common Manager
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    • Diameter of a Binary Tree
    • Print Binary Trees
  • Segment Tree
    • Segment Tree Build
    • Range Sum Query - Mutable
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    • N Queens
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    • The Maze III
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    • Jump Game II
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  • Backtracking
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    • Combination Sum IV
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    • Nuts & Bolts Problem
    • Valid Palindrome
    • The Smallest Difference
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    • Max Consecutive Ones
    • Max Consecutive Ones II
    • Remove Duplicates from Sorted Array
    • Remove Duplicates from Sorted Array II
    • Move Zeroes
    • Longest Repeating Character Replacement
    • 3Sum With Multiplicity
    • Merge Sorted Array
    • 3Sum Smaller
    • Backspace String Compare
  • Mathematics
    • Ugly Number
    • Ugly Number II
    • Super Ugly Number
    • Sqrt(x)
    • Random Number 1 to 7 With Equal Probability
    • Pow(x, n)
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    • Add N Days to Given Date
    • Reverse Integer
    • Greatest Common Divisor or Highest Common Factor
  • Bit Operation
    • IP to CIDR
  • Random
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    • Linked List Random Node
  • Dynamic Programming
    • House Robber
    • House Robber II
    • House Robber III
    • Longest Increasing Continuous Subsequence
    • Longest Increasing Continuous Subsequence II
    • Coins in a Line
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    • Stone Game
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    • Min Cost Climbing Stairs
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    • Minimum Path Sum
    • Word Break
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    • Range Sum Query - Immutable
    • Decode Ways
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    • Longest Increasing Subsequence
    • Target Sum
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    • Coin Change
    • Jump Game
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    • Maximum Sum Rectangle in a 2D Matrix
    • Cherry Pick
  • Knapsack
    • Backpack
    • Backpack II
    • Backpack III
    • Backpack IV
    • Backpack V
    • Backpack VI
    • Backpack VII
    • Coin Change
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  • High Frequency
    • 2 Sum Closest
    • 3 Sum
    • 3 Sum Closest
    • Sort Colors II
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    • Majority Number II
    • Majority Number III
    • Best Time to Buy and Sell Stock
    • Best Time to Buy and Sell Stock II
    • Best Time to Buy and Sell Stock III
    • Best Time to Buy and Sell Stock IV
    • Two Sum
    • Two Sum II - Input array is sorted
    • Two Sum III - Data structure design
    • Two Sum IV - Input is a BST
    • 4 Sum
    • 4 Sum II
  • Sorting
  • Greedy
    • Jump Game II
    • Remove K Digits
  • Minimax
    • Nim Game
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  • Sweep Line & Interval
    • Meeting Rooms
    • Meeting Rooms II
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    • Closest Pair of Points
    • My Calendar I
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    • My Calendar III
    • Add Bold Tag in String
  • Other Algorithms and Data Structure
    • Huffman Coding
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    • Construct Quad Tree
  • Company Tag
    • Google
      • Guess the Word
      • Raindrop on Sidewalk
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      • Display Pages (Pagination)
    • Amazon
  • Problem Solving Summary
    • String or Array Rotation
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    • Substring or Subarray Search
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    • K Sums
    • Combination Sum Series
    • Knapsack Problems
    • Depth-first Search
    • Large Number Operation
    • Implementation - Simulation
    • Monotonic Stack & Queue
    • Top K Problems
    • Java Interview Tips
      • OOP in Java
      • Conversion in Java
      • Data Structures in Java
    • Algorithm Optimization Tips
  • Reference
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  • Merge k Sorted Lists
  • Description
  • Example
  • 题解思路
  • 源代码

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  1. Linked List

Merge k Sorted Lists

PreviousMerge Two Sorted ListsNextLinked List Cycle

Last updated 5 years ago

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Merge k Sorted Lists

Heap

Description

Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity.

Example

Example 1

Input:   [2->4->null, null, -1->null]
Output:  -1->2->4->null

Example 2

Input: [2->6->null, 5->null, 7->null]
Output: 2->5->6->7->null

Example 3

Input:
[
  1->4->5,
  1->3->4,
  2->6
]
Output: 1->1->2->3->4->4->5->6

题解思路

归并k个已排序链表,可以分解问题拆解成为,重复k次,归并2个已排序链表。不过这种方法会在LeetCode中TLE(超出时间限制)。总共需要k次merge two sorted lists的合并过程。

改进方法:

  1. 使用merge sort中的二分的思维,将包含k个链表的列表逐次分成两个部分,再逐次对两个链表合并,这样就有 log(k)次合并过程,每次均使用merge two sorted lists的算法。时间复杂度O(nlog(k)),不需要额外空间,因此空间复杂度O(1)。

  2. 使用Priority Queues。这样保持每次取出的节点中是当前最小的,依次加入新的链表,从而得到合并的结果。时间复杂度O(nlogk),空间复杂度O(k) 是PriorityQueue的空间。

源代码

  • Divide and Conquer

/**
 * Definition for ListNode.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode(int val) {
 *         this.val = val;
 *         this.next = null;
 *     }
 * }
 */
public class Solution {
    public ListNode mergeTwoLists(ListNode l1, ListNode l2) {
        ListNode dummy = new ListNode(0);
        ListNode lastNode = dummy;

        while (l1 != null && l2 != null) {
            if (l1.val < l2.val) {
                lastNode.next = l1;
                l1 = l1.next;
            } else {
                lastNode.next = l2;
                l2 = l2.next;
            }
            lastNode = lastNode.next;
        }

        if (l1 != null) {
            lastNode.next = l1;
        } else {
            lastNode.next = l2;
        }

        return dummy.next;
    }
    /**
     * @param lists: a list of ListNode
     * @return: The head of one sorted list.
     */
    public ListNode mergeKListsNaive(List<ListNode> lists) {
        if (lists == null || lists.size() == 0) {
            return null;
        }
        if (lists.size() == 1) {
            return lists.get(0);
        }

        int listSize = lists.size();

        ListNode base = lists.get(0);

        for (int i = 1; i < listSize; i++) {
            base = mergeTwoLists(base, lists.get(i));
        }
        return base;
    }
    /**
     * @param lists: a list of ListNode
     * @return: The head of one sorted list.
     */
     public ListNode mergeKLists(List<ListNode> lists) {
         if (lists.size() == 0) {
             return null;
         }
         if (lists.size() == 1) {
             return lists.get(0);
         }
         if (lists.size() == 2) {
             return mergeTwoLists(lists.get(0), lists.get(1));
         }
         return mergeTwoLists(
            mergeKLists(lists.subList(0, lists.size()/2)),
            mergeKLists(lists.subList(lists.size()/2, lists.size()))
         );
     }
}
  • Divide & Conquer Another implementation

public class Solution {
    /**
     * @param lists: a list of ListNode
     * @return: The head of one sorted list.
     */
    public ListNode mergeKLists(List<ListNode> lists) {
        if (lists.size() == 0) {
            return null;
        }
        return mergeHelper(lists, 0, lists.size() - 1);
    }

    private ListNode mergeHelper(List<ListNode> lists, int start, int end) {
        if (start == end) {
            return lists.get(start);
        }

        int mid = start + (end - start) / 2;
        ListNode left = mergeHelper(lists, start, mid);
        ListNode right = mergeHelper(lists, mid + 1, end);
        return mergeTwoLists(left, right);
    }

    private ListNode mergeTwoLists(ListNode list1, ListNode list2) {
        ListNode dummy = new ListNode(0);
        ListNode tail = dummy;
        while (list1 != null && list2 != null) {
            if (list1.val < list2.val) {
                tail.next = list1;
                tail = list1;
                list1 = list1.next;
            } else {
                tail.next = list2;
                tail = list2;
                list2 = list2.next;
            }
        }
        if (list1 != null) {
            tail.next = list1;
        } else {
            tail.next = list2;
        }

        return dummy.next;
    }
}
  • Heap*

public class Solution {
    private Comparator<ListNode> ListNodeComparator = new Comparator<ListNode>() {
        public int compare(ListNode left, ListNode right) {
            if (left == null) {
                return 1;
            } else if (right == null) {
                return -1;
            }
            return left.val - right.val;
        }
    };

    public ListNode mergeKLists(ArrayList<ListNode> lists) {
        if (lists == null || lists.size() == 0) {
            return null;
        }

        Queue<ListNode> heap = new PriorityQueue<ListNode>(lists.size(), ListNodeComparator);
        for (int i = 0; i < lists.size(); i++) {
            if (lists.get(i) != null) {
                heap.add(lists.get(i));
            }
        }

        ListNode dummy = new ListNode(0);
        ListNode tail = dummy;
        while (!heap.isEmpty()) {
            ListNode head = heap.poll();
            tail.next = head;
            tail = head;
            if (head.next != null) {
                heap.add(head.next);
            }
        }
        return dummy.next;
    }
}
Leetcode: Merge k Sorted Lists | LeetCode OJ
Lintcode: Merge k Sorted Lists