Design Search Autocomplete System.java

H
1533426244
tags: Design, Trie, Hash Table, MinHeap, PriorityQueue
time: input: O(x), where x = possible words, constructor: O(mn) m = max length, n = # of words
space: O(n^2), n = # of possible words, n = # of trie levels; mainlay saving the `Map<S, freq>`

Description is long, but in short: 做 search auto complete. 

Best problem to review Trie (prefix search), Top K frequent elements (Hash Map), and MinHeap (PriorityQueue)

Easier to revisit https://leetcode.com/problems/design-search-autocomplete-system/description/

#### 思考方向
- 做text的search, 毋庸置疑要用Prefix tree, trie.

##### Find all possible word/leaf, 两种方案:
- Trie造好之后, 做prefix search, 然后DFS/BFS return all leaf items. [high runtime complexity]
- 在TrieNode里面存所有的possible words. [high space usage]
- in memory space 应该不是大问题, 所以我们可以选择 store all possible words

##### Given k words, find top k frequent items. 肯定用MinHeap, 但也有两种方案:
- Store MinHeap with TrieNode: 因为会不断搜索新此条, 同样的prefix (尤其是在higher level), 会被多次搜索.
- [complexity: need to update heaps across all visited TrieNodes once new sentence is completed]
- Compute MinHeap on the fly: 当然我们不能每次都来一个DFS不然会很慢, 所以就必须要store list of possible candidates in TrieNode.
- 这里就用到了`Top K Frequent Words` 里面的 `Map<String, freq>`, 这样O(m) 构建 min-heap其实很方便.

##### Train the system
- 每次 `#` 后 标记一个词条被add进search history. 那么就要 `insert it into trie`.
- 这一条在最后遇到`#`再做就可以了, 非常简洁

#### Trie, PriorityQueue, HashMap
- Trie Prefix Search + maintain top k frequent items
- 

```
/*
LeetCode. 
https://leetcode.com/problems/design-search-autocomplete-system/description/

Design a search autocomplete system for a search engine. 
Users may input a sentence (at least one word and end with a special character '#'). 
For each character they type except '#', you need to return the top 3 historical hot sentences 
that have prefix the same as the part of sentence already typed. 

Here are the specific rules:

The hot degree for a sentence is defined as the number of times a user typed the exactly same sentence before.

The returned top 3 hot sentences should be sorted by hot degree (The first is the hottest one). 
If several sentences have the same degree of hot, you need to use ASCII-code order (smaller one appears first).

If less than 3 hot sentences exist, then just return as many as you can.

When the input is a special character, it means the sentence ends, and in this case, you need to return an empty list.

Your job is to implement the following functions:

The constructor function:

- AutocompleteSystem(String[] sentences, int[] times): This is the constructor. 
The input is historical data. Sentences is a string array consists of previously typed sentences. 
Times is the corresponding times a sentence has been typed. Your system should record these historical data.

- Now, the user wants to input a new sentence. The following function will provide the next character the user types:

List<String> input(char c): The input c is the next character typed by the user. 
The character will only be lower-case letters ('a' to 'z'), blank space (' ') or a special character ('#'). 
Also, the previously typed sentence should be recorded in your system. 
The output will be the top 3 historical hot sentences that have prefix the same as the part of sentence already typed.


Example:
Operation: AutocompleteSystem(["i love you", "island","ironman", "i love leetcode"], [5,3,2,2]) 
The system have already tracked down the following sentences and their corresponding times: 
"i love you" : 5 times 
"island" : 3 times 
"ironman" : 2 times 
"i love leetcode" : 2 times 
Now, the user begins another search: 

Operation: input('i') 
Output: ["i love you", "island","i love leetcode"] 
Explanation: 
There are four sentences that have prefix "i". Among them, "ironman" and "i love leetcode" have same hot degree. 
Since ' ' has ASCII code 32 and 'r' has ASCII code 114, "i love leetcode" should be in front of "ironman".
Also we only need to output top 3 hot sentences, so "ironman" will be ignored. 

Operation: input(' ') 
Output: ["i love you","i love leetcode"] 
Explanation: 
There are only two sentences that have prefix "i ". 

Operation: input('a') 
Output: [] 
Explanation: 
There are no sentences that have prefix "i a". 

Operation: input('#') 
Output: [] 
Explanation: 
The user finished the input, the sentence "i a" should be saved as a historical sentence in system. 
And the following input will be counted as a new search. 

Note:
The input sentence will always start with a letter and end with '#', and only one blank space will exist between two words.
The number of complete sentences that to be searched won't exceed 100. The length of each sentence including those in the historical data won't exceed 100.
Please use double-quote instead of single-quote when you write test cases even for a character input.
Please remember to RESET your class variables declared in class AutocompleteSystem, as static/class variables are persisted across multiple test cases. Please see here for more details.
*/

class AutocompleteSystem {
    class TrieNode {
        public boolean isEnd;
        public Map<String, Integer> freq;
        public Map<Character, TrieNode> children; // Map is more applicable to all chars, not limited to 256 ASCII
        public TrieNode() {
            this.freq = new HashMap<>();
            this.children = new HashMap<>();
        }
    }
    class Pair {
        String s;
        int count;
        public Pair(String s, int count) {
            this.s = s;
            this.count = count;
        }
    }
    TrieNode root, curr;
    StringBuffer sb;
    public AutocompleteSystem(String[] sentences, int[] times) {
        if (sentences == null || times == null || sentences.length != times.length) return;
        reset();
        root = new TrieNode();
        for (int i = 0; i < times.length; i++) {
            insert(sentences[i], times[i]);
        }
    }
    
    public List<String> input(char c) {
        List<String> rst = new ArrayList<>();
        if (curr == null) curr = root;
        if (c == '#') { // save sentence and reset state
            insert(sb.toString(), 1);
            reset();
            return rst;
        }
        
        // Update global variable (curr TrieNode and string buffer); or append new character if not exist.
        sb.append(c);
        curr.children.putIfAbsent(c, new TrieNode());
        curr = curr.children.get(c);

        // MinHeap to find top 3.
        rst.addAll(findTopK(curr, 3));
        
        return rst;
    }
    
    private List<String> findTopK(TrieNode node, int k) {
        List<String> rst = new ArrayList<>();
        if (node.freq.isEmpty()) return rst;
        PriorityQueue<Pair> queue = new PriorityQueue<>(
            (a, b) -> a.count == b.count ? b.s.compareTo(a.s) : a.count - b.count);
        for (Map.Entry<String, Integer> entry : node.freq.entrySet()) {
            if (queue.size() < 3 || entry.getValue() >= queue.peek().count) {
                queue.offer(new Pair(entry.getKey(), entry.getValue()));
            }
            if (queue.size() > 3) queue.poll();
        }
        
        while (!queue.isEmpty()) {
            rst.add(0, queue.poll().s);
        }
        
        return rst;
    }
    
    private void reset() {
        curr = null;
        sb = new StringBuffer();
    }
    
    private void insert(String sentence, int count) {
        if (sentence == null || sentence.length() == 0) return;
        TrieNode node = root;
        for (char c : sentence.toCharArray()) {
            node.children.putIfAbsent(c, new TrieNode());
            node = node.children.get(c);
            node.freq.put(sentence, node.freq.getOrDefault(sentence, 0) + count);
        }
        node.isEnd = true; // can set word to node as well, if needed
    }
}

/**
 * Your AutocompleteSystem object will be instantiated and called as such:
 * AutocompleteSystem obj = new AutocompleteSystem(sentences, times);
 * List<String> param_1 = obj.input(c);
 */

```