Heaps and Priority Queue

A heap is the right data structure when you repeatedly need the largest or smallest element from a changing collection. The problems in this stage cover three heap patterns: top-k elements (maintain a heap of size k), two heaps (split a dataset into two halves to track the median), and k-way merge (combine multiple sorted sequences using a single heap). If you find yourself wanting to sort something repeatedly as new elements arrive, a heap is almost always the better choice. Getting comfortable with heap operations and knowing which variant to reach for is the main skill this stage develops.