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Commit9640728

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Top K frequent elements
1 parente937012 commit9640728

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packagemedium;
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importjava.util.ArrayList;
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importjava.util.Comparator;
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importjava.util.HashMap;
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importjava.util.List;
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importjava.util.Map;
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importjava.util.Map.Entry;
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importjava.util.PriorityQueue;
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importjava.util.Queue;
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publicclassTopKFrequentElements {
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// Approach 1: use buckets to hold numbers of the same frequency
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/**Attn: we must use a simple array to solve this problem, instead of using List<List<Integer>>,
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* we have to use List<Integer>[], otherwise, cases like this one: [-1,-1]
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* 1 will fail due to the fact that ArrayList.get(i),
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* this i must be a non-negative number, however, in simple arrays, the index could be negative.
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* Although in this question, frequency will be at least 1, but still in problems like this where bucket sort
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* works the best, you should use List<Integer>[], this will simplify the code.*/
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publicList<Integer>topKFrequent_using_bucket(int[]nums,intk) {
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Map<Integer,Integer>map =newHashMap();
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for(inti :nums){
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map.put(i,map.getOrDefault(i,0)+1);
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}
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ArrayList[]bucket =newArrayList[nums.length+1];
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for(Map.Entry<Integer,Integer>e :map.entrySet()){
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intfrequency =e.getValue();
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if(bucket[frequency] ==null){
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bucket[frequency] =newArrayList<Integer>();
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}
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bucket[frequency].add(e.getKey());
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}
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List<Integer>result =newArrayList<Integer>();
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for(inti =bucket.length-1;i >=0 &&result.size() <k;i--){
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if(bucket[i] !=null)result.addAll(bucket[i]);
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}
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returnresult;
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}
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// Approach 2: use hashtable and heap
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/**
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* Bonus tips on how to write a priority queue:
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*
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* Tip1:
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* it should be like this:
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* PriorityQueue's angle brackets should be left blank, the type should be in
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* Comparator's angle brackets and the compare method should be in Comparator's
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* brackets. new PriorityQueue<>(new Comparator<int[]>(){ public int
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* compare(int[] o1, int[] o2){ } })
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*
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* Tip2:
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* if you want things in DEscending order, then if(01 > o2), it should return -1
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* if Ascending order, then if(01 > o2), it should return 1
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*/
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publicList<Integer>topKFrequent_using_heap(int[]nums,intk) {
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Map<Integer,Integer>map =newHashMap();
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Queue<Map.Entry<Integer,Integer>>heap =newPriorityQueue<>(newComparator<Map.Entry<Integer,Integer>>() {
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@Override
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publicintcompare(Entry<Integer,Integer>o1,Entry<Integer,Integer>o2) {
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if (o1.getValue() >o2.getValue())
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return -1;
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elseif (o1.getValue() <o2.getValue())
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return1;
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return0;
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}
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});
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// construct the frequency map first, and then iterate through the map
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// and put them into the heap, this is O(n)
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for (intx :nums) {
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if (map.containsKey(x))
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map.put(x,map.get(x) +1);
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else
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map.put(x,1);
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}
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// build heap, this is O(n) as well
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for (Map.Entry<Integer,Integer>entry :map.entrySet()) {
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heap.offer(entry);
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}
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List<Integer>res =newArrayList<Integer>();
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while (k-- >0) {
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res.add(heap.poll().getKey());
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}
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returnres;
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}
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publicstaticvoidmain(String[]args) {
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int[]nums =newint[] {3,0,1,0 };
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TopKFrequentElementstest =newTopKFrequentElements();
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test.topKFrequent_using_heap(nums,1);
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//test.topKFrequent_using_bucket(nums, 1);
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}
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}

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