LeetCode – Top K Frequent Elements (Java)

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Given an array of integers, write a method to return the k most frequent elements.

Java Solution 1 – Heap

Time complexity is O(n*log(k)). Note that heap is often used to reduce time complexity from n*log(n) (see solution 3) to n*log(k).

public List<Integer> topKFrequent(int[] nums, int k) {
    //count the frequency for each element
    HashMap<Integer, Integer> map = new HashMap<>();
    for (int num : nums) {
        map.put(num, map.getOrDefault(num, 0) + 1);
    }
 
    // create a min heap
    PriorityQueue<Map.Entry<Integer, Integer>> queue 
                  = new PriorityQueue<>(Comparator.comparing(e -> e.getValue()));
 
    //maintain a heap of size k.
    for (Map.Entry<Integer, Integer> entry : map.entrySet()) {
        queue.offer(entry);
        if (queue.size() > k) {
            queue.poll();
        }
    }
 
    //get all elements from the heap
    List<Integer> result = new ArrayList<>();
    while (queue.size() > 0) {
        result.add(queue.poll().getKey());
    }
 
    //reverse the order
    Collections.reverse(result);
 
    return result;
}

Java Solution 2 – Bucket Sort

Time is O(n).

public List<Integer> topKFrequent(int[] nums, int k) {
    //count the frequency for each element
    HashMap<Integer, Integer> map = new HashMap<>();
    for(int num: nums){
        map.put(num, map.getOrDefault(num, 0) + 1);
    }
 
    //get the max frequency
    int max = 0;
    for(Map.Entry<Integer, Integer> entry: map.entrySet()){
        max = Math.max(max, entry.getValue());
    }
 
    //initialize an array of ArrayList. index is frequency, value is list of numbers
    ArrayList<Integer>[] arr = (ArrayList<Integer>[]) new ArrayList[max+1];
    for(int i=1; i<=max; i++){
        arr[i]=new ArrayList<Integer>();
    }
 
    for(Map.Entry<Integer, Integer> entry: map.entrySet()){
        int count = entry.getValue();
        int number = entry.getKey();
        arr[count].add(number);
    }
 
    List<Integer> result = new ArrayList<Integer>();
 
    //add most frequent numbers to result
    for(int j=max; j>=1; j--){
        if(arr[j].size()>0){
            for(int a: arr[j]){
                result.add(a);
                //if size==k, stop
                if(result.size()==k){
                    return result;
                }
            }
        }
    }
 
    return result;
}

9 thoughts on “LeetCode – Top K Frequent Elements (Java)”

  1. obv most important how to find K top freq after mapping symbols

    we can sort
    we can use heap (min)

    OR WE CAN use quik_select

  2. Solution 1, you can directly store Map.Entry in PriorityQueue and you don’t need to create Pair.
    PriorityQueue<Map.Entry> minHeap = new PriorityQueue(k, new comparator<Map.Entry() {//…});

  3. Shortest Java solution with good efficiency. See my solution, I have added comments. Time is O(n).


    public static int topKFrequentArray(int[] array, int k){

    /* First get element and number of occurrence using HashMap */
    Map hm = new HashMap();
    for(int i : array){
    if(hm.containsKey(i)){
    hm.put(i, hm.get(i) + 1);
    }
    else {hm.put(i, 1);}
    }

    /*Since Map does not allow dups keys, let's swap the key & value and insert into multimap. This sorts it as well */
    Multimap mp = ArrayListMultimap.create();
    for(Map.Entry m : hm.entrySet()){
    mp.put(m.getValue(),m.getKey());
    }

    /* Finally we extract all values (ordered by smallest) and load into a list */
    List ls = new ArrayList();
    Set ks = mp.keySet();
    Iterator it = ks.iterator();
    while (it.hasNext() ) {
    ls.addAll(new ArrayList(mp.get((Integer) it.next())));
    }
    /* Since the biggest is last of the list, we substract k from the List Size */
    return ls.get(ls.size()-k);
    }


  4. My slick java solution, easy to understand and very efficient. Time is O(n).

    public static int topKFrequent(int[] array, int k){
    Map hm = new HashMap();
    Multimap mp = ArrayListMultimap.create();
    List ls = new ArrayList();

    for(int i : array){
    if(hm.containsKey(i)){hm.put(i, hm.get(i) + 1); }
    else {hm.put(i, 1);}
    }

    for(Map.Entry m : hm.entrySet()){mp.put(m.getValue(),m.getKey());}

    Set ks = mp.keySet();
    Iterator it = ks.iterator();
    while (it.hasNext() ) {
    Collection val = mp.get((Integer) it.next());
    for(int i : val){ls.add(i);}
    }

    System.out.println("Print " +k+" Character");
    for(int i=ls.size()-1, cnt=1; i>=0; cnt++, i--){if(cnt == k){return ls.get(i);}}
    return 0;
    }

  6. There’s a bug in solution 2-
    //add most frequent numbers to result
    for(int j=max; j>=1; j–){
    if(arr[j].size()>0){
    for(int a: arr[j]){
    result.add(a);
    }
    }

    if(result.size()==k)
    break;
    }

    The check for result.size()==k should be inside the loop after result.add(a). This is because result.size() == k can occur when your looping each int a.

  7. Java Solution 2 – Bucket Sort has bug.
    Try this array to test:

    int a[] = {1, 2, 4, 2, 2, 5, 1, 4, 2, 1, 4, 2};
    int k=2;

    The code below:

    if (result.size() == k) {
    break;
    }

    should be changed to:

    if (result.size() >= k) {
    break;
    }

  8. Treemap code can be as concise as this:


    Map sortedMap = new TreeMap(new Comparator() {
    public int compare(Integer o1, Integer o2) {
    int diff = map.get(o2) - map.get(o1);
    return diff == 0 ? 1 : diff;
    }
    });
    sortedMap.putAll(counter);

  9. Second solution i think the code to populate result should look like this.

    for(int j=max; j>=k-1; j–){
    if(count[j].size()>0){
    for(int a: count[j]){
    result.add(a);
    }
    }
    }

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