Heap DataStructure

Author: spoorthi01012004m

src/main/java/com/thealgorithms/Heap/DesignTwitter.java

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+import java.util.*;
+
+class Twitter {
+    private static int timeStamp = 0;
+    private static class Tweet {
+        int id;
+        int time;
+        Tweet next;
+
+        public Tweet(int id, int time) {
+            this.id = id;
+            this.time = time;
+        }
+    }
+
+    
+    private Map<Integer, Set<Integer>> followMap;
+   
+    private Map<Integer, Tweet> tweetMap;
+
+    public Twitter() {
+        followMap = new HashMap<>();
+        tweetMap = new HashMap<>();
+    }
+
+    /** User posts a new tweet */
+    public void postTweet(int userId, int tweetId) {
+        Tweet newTweet = new Tweet(tweetId, timeStamp++);
+        if (tweetMap.containsKey(userId)) {
+            newTweet.next = tweetMap.get(userId);
+        }
+        tweetMap.put(userId, newTweet);
+    }
+
+    /** Retrieve the 10 most recent tweet ids in the user's news feed */
+    public List<Integer> getNewsFeed(int userId) {
+        List<Integer> result = new ArrayList<>();
+        // Min-heap to get most recent tweets first
+        PriorityQueue<Tweet> pq = new PriorityQueue<>((a, b) -> b.time - a.time);
+
+        // Add own tweets
+        if (tweetMap.containsKey(userId)) {
+            pq.offer(tweetMap.get(userId));
+        }
+
+        // Add followees' tweets
+        if (followMap.containsKey(userId)) {
+            for (int followee : followMap.get(userId)) {
+                if (tweetMap.containsKey(followee)) {
+                    pq.offer(tweetMap.get(followee));
+                }
+            }
+        }
+
+        // Retrieve top 10 tweets
+        while (!pq.isEmpty() && result.size() < 10) {
+            Tweet t = pq.poll();
+            result.add(t.id);
+            if (t.next != null) pq.offer(t.next);
+        }
+        return result;
+    }
+
+
+    public void follow(int followerId, int followeeId) {
+        if (followerId == followeeId) return; // can’t follow self
+        followMap.putIfAbsent(followerId, new HashSet<>());
+        followMap.get(followerId).add(followeeId);
+    }
+
+    /** Follower unfollows a followee */
+    public void unfollow(int followerId, int followeeId) {
+        if (!followMap.containsKey(followerId)) return;
+        followMap.get(followerId).remove(followeeId);
+    }
+}

src/main/java/com/thealgorithms/Heap/FindMedianfromDataStream.java

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+import java.util.*;
+
+public class MedianFinder {
+    private PriorityQueue<Integer> maxHeap; // left half (small)
+    private PriorityQueue<Integer> minHeap; // right half (larger)
+
+    public MedianFinder() {
+        // Max-heap stores the smaller half
+        maxHeap = new PriorityQueue<>(Collections.reverseOrder());
+        // Min-heap stores the larger half
+        minHeap = new PriorityQueue<>();
+    }
+
+    
+    public void addNum(int num) {
+        // Step 1: Add to maxHeap
+        maxHeap.offer(num);
+
+        // Step 2: Balance heaps (ensure all in maxHeap <= all in minHeap)
+        minHeap.offer(maxHeap.poll());
+
+        // Step 3: Maintain size property (maxHeap can be larger by 1)
+        if (maxHeap.size() < minHeap.size()) {
+            maxHeap.offer(minHeap.poll());
+        }
+    }
+
+    public double findMedian() {
+        if (maxHeap.size() == minHeap.size()) {
+            // Even number of elements → average of two middles
+            return (maxHeap.peek() + minHeap.peek()) / 2.0;
+        } else {
+            // Odd → top of maxHeap
+            return maxHeap.peek();
+        }
+    }
+
+
+    public static void main(String[] args) {
+        MedianFinder mf = new MedianFinder();
+        
+        mf.addNum(1);
+        System.out.println("After adding 1, Median = " + mf.findMedian());
+        
+        mf.addNum(2);
+        System.out.println("After adding 2, Median = " + mf.findMedian());
+        
+        mf.addNum(3);
+        System.out.println("After adding 3, Median = " + mf.findMedian());
+        
+        mf.addNum(4);
+        System.out.println("After adding 4, Median = " + mf.findMedian());
+        
+        mf.addNum(5);
+        System.out.println("After adding 5, Median = " + mf.findMedian());
+    }
+}

src/main/java/com/thealgorithms/Heap/HandOfStraights.java

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+import java.util.*;
+
+public class HandOfStraights {
+
+    public static boolean isNStraightHand(int[] hand, int groupSize) {
+        // Base check
+        if (hand.length % groupSize != 0) return false;
+
+        // Step 1: Count frequency of each card
+        TreeMap<Integer, Integer> cardCount = new TreeMap<>();
+        for (int card : hand) {
+            cardCount.put(card, cardCount.getOrDefault(card, 0) + 1);
+        }
+
+        // Step 2: Iterate over cards in sorted order
+        for (int card : cardCount.keySet()) {
+            int freq = cardCount.get(card);
+            if (freq > 0) { // If we still have cards to group
+                
+                for (int next = card; next < card + groupSize; next++) {
+                    if (cardCount.getOrDefault(next, 0) < freq) {
+                        return false; 
+                    }
+                    cardCount.put(next, cardCount.get(next) - freq);
+                }
+            }
+        }
+
+        return true; 
+    }
+
+    
+    public static void main(String[] args) {
+        int[] hand1 = {1,2,3,6,2,3,4,7,8};
+        int groupSize1 = 3;
+        System.out.println("Output 1: " + isNStraightHand(hand1, groupSize1)); // true
+
+        int[] hand2 = {1,2,3,4,5};
+        int groupSize2 = 4;
+        System.out.println("Output 2: " + isNStraightHand(hand2, groupSize2)); // false
+    }
+}

src/main/java/com/thealgorithms/Heap/IPO.java

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+import java.util.*;
+
+public class IPO {
+    public int findMaximizedCapital(int k, int w, int[] profits, int[] capital) {
+        int n = profits.length;
+        int[][] projects = new int[n][2];
+        
+        // Combine capital and profit for each project
+        for (int i = 0; i < n; i++) {
+            projects[i][0] = capital[i];
+            projects[i][1] = profits[i];
+        }
+
+        // Sort projects by required capital (ascending)
+        Arrays.sort(projects, Comparator.comparingInt(a -> a[0]));
+
+       
+        PriorityQueue<Integer> maxHeap = new PriorityQueue<>((a, b) -> b - a);
+
+        int i = 0;
+        for (int t = 0; t < k; t++) {
+            // Add all affordable projects to the heap
+            while (i < n && projects[i][0] <= w) {
+                maxHeap.offer(projects[i][1]);
+                i++;
+            }
+
+            // If no project is affordable, break early
+            if (maxHeap.isEmpty()) break;
+
+                                  
+            w += maxHeap.poll();  // Pick the most profitable project
+        }
+
+        return w;
+    }
+
+    public static void main(String[] args) {
+        IPO obj = new IPO();
+        int k = 2, w = 0;
+        int[] profits = {1, 2, 3};
+        int[] capital = {0, 1, 1};
+
+        System.out.println(obj.findMaximizedCapital(k, w, profits, capital)); // Output: 4
+    }
+}

src/main/java/com/thealgorithms/Heap/MergeKSortedList.java

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+import java.util.*;
+
+class MergeMSortedArrays {
+    static class Element {
+        int value;
+        int arrayIndex;
+        int elementIndex;
+
+        Element(int value, int arrayIndex, int elementIndex) {
+            this.value = value;
+            this.arrayIndex = arrayIndex;
+            this.elementIndex = elementIndex;
+        }
+    }
+
+    public static List<Integer> mergeSortedArrays(int[][] arrays) {
+        PriorityQueue<Element> minHeap = new PriorityQueue<>(Comparator.comparingInt(e -> e.value));
+        List<Integer> result = new ArrayList<>();
+
+        // Step 1: Push the first element of each array
+        for (int i = 0; i < arrays.length; i++) {
+            if (arrays[i].length > 0) {
+                minHeap.offer(new Element(arrays[i][0], i, 0));
+            }
+        }
+
+        // Step 2: Extract the smallest element and push the next from same array
+        while (!minHeap.isEmpty()) {
+            Element current = minHeap.poll();
+            result.add(current.value);
+
+            int nextIndex = current.elementIndex + 1;
+            if (nextIndex < arrays[current.arrayIndex].length) {
+                minHeap.offer(new Element(
+                    arrays[current.arrayIndex][nextIndex],
+                    current.arrayIndex,
+                    nextIndex
+                ));
+            }
+        }
+
+        return result;
+    }
+
+    public static void main(String[] args) {
+        int[][] arrays = {
+            {1, 4, 7},
+            {2, 5, 8},
+            {3, 6, 9}
+        };
+
+        System.out.println("Merged Sorted Array: " + mergeSortedArrays(arrays));
+    }
+}

src/main/java/com/thealgorithms/Heap/SlidingWindowMax.java

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+import java.util.*;
+
+public class SlidingWindowMaximum {
+    public static int[] maxSlidingWindow(int[] nums, int k) {
+        int n = nums.length;
+        int[] result = new int[n - k + 1];
+        PriorityQueue<int[]> maxHeap = new PriorityQueue<>((a, b) -> b[0] - a[0]); // Max heap based on value
+
+        for (int i = 0; i < n; i++) {
+            //add current
+            maxHeap.offer(new int[]{nums[i], i});
+
+            // remove elements outside the current window
+            while (maxHeap.peek()[1] <= i - k) {
+                maxHeap.poll();
+            }
+
+            // Store the max for the current window
+            if (i >= k - 1) {
+                result[i - k + 1] = maxHeap.peek()[0];
+            }
+        }
+
+        return result;
+    }
+
+    public static void main(String[] args) {
+        int[] nums = {1, 3, -1, -3, 5, 3, 6, 7};
+        int k = 3;
+        System.out.println(Arrays.toString(maxSlidingWindow(nums, k)));
+    }
+}

src/main/java/com/thealgorithms/Heap/TaskScheduler.java

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+import java.util.*;
+
+public class TaskScheduler {
+
+    public static int leastInterval(char[] tasks, int n) {
+        int[] freq = new int[26];
+        for (char c : tasks) {
+            freq[c - 'A']++;
+        }
+        
+        Arrays.sort(freq);
+        int maxFreq = freq[25];
+        int idleSlots = (maxFreq - 1) * n;
+
+        // Fill idle slots with remaining tasks
+        for (int i = 24; i >= 0 && idleSlots > 0; i--) {
+            idleSlots -= Math.min(freq[i], maxFreq - 1);
+        }
+
+        idleSlots = Math.max(0, idleSlots);
+
+        return tasks.length + idleSlots;
+    }
+
+    public static void main(String[] args) {
+        char[] tasks1 = {'A','A','A','B','B','B'};
+        int n1 = 2;
+        System.out.println("Output 1: " + leastInterval(tasks1, n1)); // 8
+
+        char[] tasks2 = {'A','C','A','B','D','B'};
+        int n2 = 1;
+        System.out.println("Output 2: " + leastInterval(tasks2, n2)); // 6
+
+        char[] tasks3 = {'A','A','A','B','B','B'};
+        int n3 = 0;
+        System.out.println("Output 3: " + leastInterval(tasks3, n3)); // 6
+    }
+}

src/main/java/com/thealgorithms/Heap/TopKFrequentElements.java

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+import java.util.*;
+
+public class TopKFrequentElements {
+
+    public static int[] topKFrequent(int[] nums, int k) {
+        // Step 1: Count frequencies
+        Map<Integer, Integer> freqMap = new HashMap<>();
+        for (int num : nums) {
+            freqMap.put(num, freqMap.getOrDefault(num, 0) + 1);
+        }
+
+        // Step 2: Use a min-heap to keep top k elements
+        PriorityQueue<Map.Entry<Integer, Integer>> minHeap =
+                new PriorityQueue<>((a, b) -> a.getValue() - b.getValue());
+
+        for (Map.Entry<Integer, Integer> entry : freqMap.entrySet()) {
+            minHeap.offer(entry);
+            if (minHeap.size() > k) {
+                minHeap.poll(); // remove least frequent element
+            }
+        }
+
+        // Step 3: Extract elements from heap
+        int[] result = new int[k];
+        for (int i = k - 1; i >= 0; i--) {
+            result[i] = minHeap.poll().getKey();
+        }
+
+        return result;
+    }
+
+    public static void main(String[] args) {
+        int[] nums = {1, 1, 1, 2, 2, 3, 3, 3, 3, 4};
+        int k = 2;
+
+        int[] res = topKFrequent(nums, k);
+        System.out.println("Top " + k + " frequent elements: " + Arrays.toString(res));
+    }
+}