Algorithms
  • Introduction
  • Analysis of Algorithms
  • Numbers
    • Reverse Integer
    • Palindroms
      • Valid Palindrome
    • Prime factor
    • Prime Number
    • Roman to Integer
    • Happy Number
    • p^k
  • Searching
    • Union-Find Algorithms
    • Finding Peak
    • Find Sum in Array
    • Binary Search
      • Find Index Binary Search
      • Sqrt(x)
      • Search in Rotated Sorted Array
      • Guess Number Higher or Lower
      • First Bad Version
      • Find Peak Element
      • Find Minimum in Rotated Sorted Array
      • Find Minimum in Rotated Sorted Array II
      • Search for a Range
      • Closest Binary Search Tree Value
      • Find K Closest Elements
      • Search in a Sorted Array of Unknown Size
      • Pow(x, n)
      • Valid Perfect Square
      • Find Minimum in Rotated Sorted Array II
      • Intersection of Two Arrays
      • Intersection of Two Arrays II
      • Two Sum II - Input array is sorted
      • Find the Duplicate Number
    • Longest Common Prefix
  • Sorting
    • Elementary Sorts
    • Insertion Sort
    • Bubble Sort
    • Mergesort
    • Quicksort
    • Radix Sort
    • Heap Sort
  • Data Structures
    • Array & List
      • Find Pivot Index
      • Largest Number At Least Twice of Others
      • Plus One
      • Diagonal Traverse
      • Spiral Matrix
      • Pascal's Triangle
      • Implement strStr()
      • Add Binary
      • Duplicate Counts
      • Find Duplicates
      • Reverse String
      • Array Partition I
      • Two Sum II - Input array is sorted
      • Remove Element
      • Max Consecutive Ones
      • Minimum Size Subarray Sum
      • Reverse Words in a String
      • Reverse Words in a String III
      • Remove Duplicates from Sorted Array
      • Move Zeroes
      • Rotate Array
      • Rotate Image
      • Best Time to Buy and Sell Stock
      • Best Time to Buy and Sell Stock II
      • Valid Anagram
      • 3Sum
      • String to Integer (atoi)
      • Count and Say
      • Merge Sorted Array
      • Shuffle an Array
      • Max Area of Island
    • Matrix
    • Stack
      • Valid Parentheses
      • Min Stack
    • Queue
    • Linked List
      • Design Linked List
      • Design Doubly Linked List
      • Find Middle Element
      • Doubly Linked List
      • Cyclic Linked List
      • Linked List Cycle II
      • Find Nth Element from End
      • Remove Nth Node From End of List
      • Add Two Numbers
      • Merge Two Sorted Lists
      • Remove Nth Node From End of List
      • Reverse Linked List
      • Remove Linked List Elements
      • Odd Even Linked List
      • Design Doubly Linked List
      • Flatten a Multilevel Doubly Linked List
      • Rotate List
      • Copy List with Random Pointer
      • Insert into a Cyclic Sorted List
      • Delete Node in a Linked List
      • Palindrome Linked List
    • Set
      • Intersection of Two Arrays
      • Single Number
      • Contains Duplicate
      • Contains Duplicate II
      • Jewels and Stones
      • Longest Substring Without Repeating Characters
      • Two Sum III - Data structure design
      • Valid Sudoku
      • Missing Number
    • Map
      • Two Sum
      • Isomorphic Strings
      • Minimum Index Sum of Two Lists
      • First Unique Character in a String
      • Intersection of Two Arrays II
      • Logger Rate Limiter
      • Group Anagrams
      • Group Shifted Strings
      • Find Duplicate Subtrees
      • 4Sum II
      • Top K Frequent Elements
      • Unique Word Abbreviation
      • Insert Delete GetRandom O(1)
    • Binary Tree
      • Binary Tree Preorder Traversal
      • Binary Tree Inorder Traversal
      • Binary Tree Postorder Traversal
      • Binary Tree Level Order Traversal
      • Maximum Depth of Binary Tree
      • Symmetric Tree
      • Path Sum
      • Balanced Binary Tree
      • Count Univalue Subtrees
      • Construct Binary Tree from Inorder and Postorder Traversal
      • Construct Binary Tree from Preorder and Inorder Traversal
      • Populating Next Right Pointers in Each Node
      • Lowest Common Ancestor of a Binary Tree
      • Serialize and Deserialize Binary Tree
      • Median of Two Sorted Arrays
      • Invert Binary Tree
      • Find K-th Smallest Pair Distance
      • Split Array Largest Sum
    • Heap
    • Binary Search Tree
      • Validate Binary Search Tree
      • Inorder Successor in BST
      • Binary Search Tree Iterator
      • Search in a Binary Search Tree
      • Insert into a Binary Search Tree
      • Delete Node in a BST
      • Kth Largest Element in a Stream
      • Lowest Common Ancestor of a Binary Search Tree
      • Contains Duplicate III
      • Height-Balanced BST
        • Balanced Binary Tree
        • Convert Sorted Array to Binary Search Tree
    • Map
    • N-ary Tree
      • N-ary Tree Preorder Traversal
      • N-ary Tree Postorder Traversal
      • N-ary Tree Level Order Traversal
      • Maximum Depth of N-ary Tree
      • Encode N-ary Tree to Binary Tree
      • Serialize and Deserialize N-ary Tree
    • Trie
      • Implement Trie (Prefix Tree)
      • Map Sum Pairs
      • Replace Words
      • Design Search Autocomplete System
      • Maximum XOR of Two Numbers in an Array
      • Add and Search Word - Data structure design
      • Word Search II
      • Word Squares
      • Longest Common Prefix
      • Palindrome Pairs
    • Balanced Tree
      • B-Tree
      • Red-black Tree
      • AVL Tree
    • Graph
      • A* Search
      • Breadth First Search
      • Depth First Search
      • Dijkstra Algorithm
  • Sequences
    • Fibonacci Sequence
  • Dynamic Programming
    • Knapsack problem
    • Climbing Stairs
    • Best Time to Buy and Sell Stock
    • Maximum Subarray
    • House Robber
  • Interviews
    • Google Leetcode
      • Repeated String Match
      • K Empty Slots
      • Next Closest Time
      • Longest Univalue Path
      • License Key Formatting
      • Spiral Matrix
      • Plus One
      • Trapping Rain Water
      • Longest Substring with At Most K Distinct Characters
      • Add Bold Tag in String
      • Game of Life
      • Read N Characters Given Read4
      • Read N Characters Given Read4 II - Call multiple times
      • One Edit Distance
      • Valid Palindrome
      • Valid Number
      • Valid Parentheses
      • Image Smoother
      • Intersection of Two Arrays
      • Max Consecutive Ones
      • Max Consecutive Ones II
      • Shortest Palindrome
      • First Missing Positive
      • First Unique Character in a String
      • Move Zeroes
      • Remove Duplicates from Sorted Array
      • Merge k Sorted Lists
      • Insert into a Cyclic Sorted List
      • Evaluate Division
      • Inorder Successor in BST
      • Robot Room Cleaner
      • Redundant Connection II
      • Course Schedule
      • Validate Binary Search Tree
      • Closest Binary Search Tree Value
      • Word Squares
      • Strobogrammatic Number II
      • Word Search II
      • Android Unlock Patterns
      • Minimum Window Substring
      • Kth Largest Element in an Array
      • Shortest Distance from All Buildings
      • Find K-th Smallest Pair Distance
      • Find K Pairs with Smallest Sums
      • Range Module
      • Insert Interval
      • Sort Transformed Array
      • Merge Intervals
      • Longest Palindromic Substring
      • Next Greater Element I
      • Pacific Atlantic Water Flow
      • Evaluate Reverse Polish Notation
      • Decode Ways
      • Word Break
      • Sentence Screen Fitting
      • Maximum Vacation Days
      • Edit Distance
      • Minimum Path Sum
      • House Robber II
      • Moving Average from Data Stream
      • Peeking Iterator
      • Binary Search Tree Iterator
      • Zigzag Iterator
      • Design Tic-Tac-Toe
      • Range Sum Query 2D - Mutable
      • UTF-8 Validation
      • Maximum Product of Word Lengths
  • Other
    • Game of Life
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  1. Data Structures

Map

Map stores values behind keys. That said, values in a map can be obtained using a key.

Lets create very simple hash map. This hash map is fixed size and does not count other types than integer.

class MyHashMap {

    Integer[] values = new Integer[1000000];

    /** Initialize your data structure here. */
    public MyHashMap() {
    }

    /** value will always be positive. */
    public void put(int key, int value) {
        values[hash(key)] = value;
    }

    /** Returns the value to which the specified key is mapped, or -1 if this map contains no mapping for the key */
    public int get(int key) {
        Integer result = values[hash(key)];
        if (result == null) {
            return -1;
        }
        return result;
    }

    /** Removes the mapping of the specified value key if this map contains a mapping for the key */
    public void remove(int key) {
        values[hash(key)] = null;
    }

    private int hash(int value) {
        return values.length % value;
        // or we can use bit operator to limit number to upper boundary, which is length of array
        // return hashCode & (entries.length - 1);
        // hashCode: 10 , n: 9
        // hashCode (in binary): 1010 , n (in binary): 1001
        // position (in binary): 1000 (8 in decimal)
    }
}

Now we can use the hash map as follows.

MyHashMap hashMap = new MyHashMap();
hashMap.put(1, 1);          
hashMap.put(2, 2);         
hashMap.get(1);            // returns 1
hashMap.get(3);            // returns -1 (not found)
hashMap.put(2, 1);          // update the existing value
hashMap.get(2);            // returns 1 
hashMap.remove(2);          // remove the mapping for 2
hashMap.get(2);            // returns -1 (not found)

Implementation using Entry

We need to use Entry class to handle duplicates (when two objects have the same hash code but they are not equal).

class HashMap<K, V> {
    private Entry[] entries;

    HashMap() {
        entries = new Entry[10];
    }

    public void put(K key, V value) {
        Entry<K, V> entry = new Entry<>(key, value);
        int position = calculateHashCode(key);
        if (entries[position] == null) {
            entries[position] = entry;
        } else {
            Entry<K, V> available = findNextAvailableEntry(position);
            available.next = entry;
        }
    }

    public V get(K key) {
        int position = calculateHashCode(key);
        Entry entry = entries[position];
        while (!entry.key.equals(key)) {
            entry = entry.next;
        }
        return (V) entry.value;
    }

    Entry<K, V> findNextAvailableEntry(int position) {
        Entry<K, V> current = entries[position];
        if (current.next != null) {
            current = current.next;
        }
        return current;
    }

    int calculateHashCode(K key) {
        return key.hashCode() % entries.length;
    }

    class Entry<K, V> {
        K key;
        V value;
        Entry<K, V> next; // linked list

        Entry(K key, V value) {
            this.key = key;
            this.value = value;
        }
    }
}

Lets try to use the hash map.

public class Test {

    public static void main(String... args) {
        HashMap<String, Integer> map = new HashMap<>();
        map.put("a", 1);
        map.put("b", 2);
        map.put("k", 3); // k has conflicting position 

        Integer one = map.get("a");
        System.out.println(one);

        Integer three = map.get("k");
        System.out.println(three);

        System.out.println("a: " + map.calculateHashCode("a"));
        System.out.println("b: " + map.calculateHashCode("b"));
        System.out.println("c: " + map.calculateHashCode("c"));
        System.out.println("d: " + map.calculateHashCode("d"));
        System.out.println("e: " + map.calculateHashCode("e"));
        System.out.println("f: " + map.calculateHashCode("f"));
        System.out.println("g: " + map.calculateHashCode("g"));
        System.out.println("h: " + map.calculateHashCode("h"));
        System.out.println("i: " + map.calculateHashCode("i"));
        System.out.println("j: " + map.calculateHashCode("j"));
        System.out.println("k: " + map.calculateHashCode("k"));
    }
}

How the position is calculated.

println "a".hashCode()
println "b".hashCode()
println "k".hashCode()
println "u".hashCode()

println "a".hashCode() % 10
println "k".hashCode() % 10
println "u".hashCode() % 10

Here is the output.

97
98
107
117

7
7
7
PreviousMissing NumberNextTwo Sum

Last updated 5 years ago

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