Study Notes
  • Kuma Blog
  • AI
    • AI-Resources
    • AI-books
    • Prompts
      • Prompts Free Courses
  • Movies
    • 2024
    • 2024
    • 2024
  • Google
    • chunked-palindrome
  • Setup
    • How to add a new user into Ubuntu and setup ssh key?
    • How to set up VSCode remote server connect with browser with Docker
  • kubernetes
  • Books
    • Designing-Data-Intensive-Applications
      • 第一章 — 可靠性,可扩展性,可维护性的应用程序(Reliable, Scalable, and Maintainable Applications)
    • System-Performance
      • Design-Data-Intensive-Application
      • Chapter 2: Methodologies
  • Languages
    • japanese
      • japanese-week
  • Leetcode
    • 30DayChallenge
      • LRU-cache
      • backspace-string-compare
      • binary-tree-maximum-path-sum
      • bitwise-and-number-range
      • check-string-valid-sequence-from-root-to-leaves-path-in-bst
      • construct-binary-search-tree-from-preorder-traversal
      • contiguous-array
      • counting-elements
      • diameter-of-binary-tree
      • first-unique-number
      • group-anagrams
      • jump-game
      • last-stone-weight
      • leftmost-column-with-at-least-a-one
      • longest-common-subsequect
      • maximal-square
      • maximum-subarray
      • middle-of-the-linked-list
      • min-stack
      • minimun-path-sum
      • move-zeroes
      • perform-string-shifts
      • product-of-array-except-itself
      • search-in-rotated-sorted-array
      • subarray-sum-equals-k
      • valid-parenthesis-string
    • English Solution
      • 1168.optimize-water-distribution-in-a-village-en
      • 1171.remove-zero-sum-consecutive-nodes-from-linked-list-en
      • 1177.can-make-palindrome-from-substring-en
      • 1343.number-of-avg-subarr-sizek-greater-or-equal-threshold
      • 1345.jump-game-iv
      • 25.reverse-nodes-in-k-groups-en
      • 474.ones-and-zeros-en
      • 53.maximum-sum-subarray-en
      • 547.friend-circles-en
      • 79.word-search-en
    • May2020Challenge
      • check-if-straight-line
      • cousins-in-binary-tree
      • find-town-judge
      • first-bad-version
      • first-unique-character-in-a-string
      • flood-fill
      • implement-trie
      • jewels-and-stones
      • majority-element
      • maximum-sum-circular-subarray
      • number-complement
      • odd-even-linkedlist
      • ransom-note
      • remove-k-digits
      • single-element-in-sorted-array
      • valid-perfect-square
    • python
      • 000017-Letter-Combinations-of-a-Phone-Number
      • 000032-Longest-Valid-Parentheses
      • 000033-Search-in-Rotated-Sorted-Array
      • 000046-Permutations
      • 000074-Search-a-2D-Matrix
      • 000077-Combinations
      • 000081-Search-in-Rotated-Sorted-Array-II
      • 000137-single-number-ii
      • 000139-Word-Break
      • 000207-courses-schedule
      • 000209-Minimum-Size-Subarray-Sum
      • 000376-wiggle-subsequence
      • 000445-Add-Two-Numbers-II
      • 000486-Predict-the-Winner
      • 000518-Coin-Change-II
      • 000673-Number-of-Longest-Increasing-Subsequence
      • 000688-Knight-Probability-in-Chessboard
      • 000735-Asteroid-Collision
      • 000852-Peak-Index-in-a-Mountain-Array
      • 859-Buddy-Strings
      • 000864-Shortest-Path-to-Get-All-Keys
      • 000920-Number-of-Music-Playlists
      • 001218-Longest-Arithmetic-Subsequence-of-Given-Difference
      • 001235-Maximum-Profit-in-Job-Scheduling
      • 001493-Longest-Subarray-of 1-After-Deleting-One-Element
      • Problem
      • 002024-Maximize-the-Confusion-of-an-Exam
      • 2305-Fair-Distribution-of-Cookies
      • 002616-Minimize-the-Maximum-Difference-of-Pairs
      • 00802-Find-Eventual-Safe-States
    • 中文版解题
      • 1147.longest-chunked-palindrome-decomposition-cn
      • 1168.optimize-water-distribution-in-a-village-cn
      • 1171.remove-zero-sum-consecutive-nodes-from-linked-list-cn
      • 1177.can-make-palindrome-from-substring-cn
      • 215.kth-largest-element-in-an-array-cn
      • 25.reverse-nodes-in-k-groups-cn
      • 30.substring-with-concatenation-of-all-words-cn
      • 4.median-of-two-sorted-array-cn
      • 460.LFU-cache-cn
      • 474.ones-and-zeros-cn
      • 53.maximum-sum-subarray-cn
      • 79.word-search-cn
  • Readings
    • 2020
      • Design-Data-Intensive-Application
      • 亲爱的提奥
      • 理想国
      • 贫穷的本质
Powered by GitBook
On this page
  • Problem
  • Problem Description
  • Solution
  • Complexity Analysis
  • Code

Was this helpful?

  1. Leetcode
  2. May2020Challenge

implement-trie

Previousflood-fillNextjewels-and-stones

Last updated 4 years ago

Was this helpful?

Problem

Problem Description

Implement a trie with insert, search, and startsWith methods.

Example:

Trie trie = new Trie();

trie.insert("apple");
trie.search("apple");   // returns true
trie.search("app");     // returns false
trie.startsWith("app"); // returns true
trie.insert("app");   
trie.search("app");     // returns true
Note:

You may assume that all inputs are consist of lowercase letters a-z.
All inputs are guaranteed to be non-empty strings.

Solution

Now define TrieNode with char, isWord, children. 1. do insert:

  • iterate through each char in word, check whether current char ch in current node's children. if not, create new TrieNode(ch), put into current node children, other wise do nothing

  • then reset current node as curr.children.get(ch).

  • after word, set current node isWord = true.

    1. do search:

  • iterate through each char in word, for each ch:

    • if ch is in current node children, continue, if not in current node's children, return false. terminate early.

    • reset current node as curr.children.get(ch), (go next level)

    • until at last char, check current node isWord is true or not, if isWord = true, return true. otherwise no word in trie.

      1. do prefix search:

  • same search steps as search word.

  • at last step, return true (meaning it has prefix, do need to check isWord).

For example:

Complexity Analysis

insert(word): O(n) -- n is the length of word

search(word): O(n) -- n is the length of word

Code

class Trie {
    TrieNode root;
    /** Initialize your data structure here. */
   public Trie() {
        root = new TrieNode();
   }

   /** Inserts a word into the trie. */
   public void insert(String word) {
       TrieNode curr = root;
       for (char ch : word.toCharArray()) {
            if (!curr.children.containsKey(ch)) {
                 curr.children.put(ch, new TrieNode(ch));

            }
            curr = curr.children.get(ch);

       }
       curr.isWord = true;
   }

   /** Returns if the word is in the trie. */
   public boolean search(String word) {
       return isWordOrPrefix(word, true);
   }

   /** Returns if there is any word in the trie that starts with the given prefix. */
   public boolean startsWith(String prefix) {
       return isWordOrPrefix(prefix, false);
   }

   private boolean isWordOrPrefix(String prefix, boolean isWord) {
       TrieNode curr = root;
       for (char ch : prefix.toCharArray()) {
           if (!curr.children.containsKey(ch)) return false;
               curr = curr.children.get(ch);
       }
       return isWord ? curr.isWord : true; 
   }

}

class TrieNode {
    char ch;
    boolean isWord;
    Map<Character, TrieNode> children;
    public TrieNode(char ch) {
        this.ch = ch;
        isWord = false;
        children = new HashMap<>();
    }
    public TrieNode() {
       isWord = false;
       children = new HashMap<>();
    }
}

/**
 * Your Trie object will be instantiated and called as such:
 * Trie obj = new Trie();
 * obj.insert(word);
 * boolean param_2 = obj.search(word);
 * boolean param_3 = obj.startsWith(prefix);
 */

First understand what is trie, please read .

Implement Trie(prefix Tree)
Trie (Wiki)
Implement Trie