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Introduction to Top K Elements

Explore the top K elements pattern to efficiently identify a specific number of largest, smallest, or most frequent elements from an unsorted dataset. Understand how using min and max heaps reduces sorting time complexity and apply this pattern to real-world problems like ride-sharing and social media trend analysis.

About the pattern

The top k elements pattern is an important technique in coding that helps us efficiently find a specific number of elements, known as kk, from a set of data. This is particularly useful when we’re tasked with identifying the largest, smallest, or most/least frequent elements within an unsorted collection.

To solve tasks like these, one might think to sort the entire collection first, which takes O(nlog(n))O(n \log(n)) time, and then select the top k elements, taking additional O(k)O(k) time. However, the top k elements pattern bypasses the need for full sorting, reducing the time complexity to O(nlogk)O(n \log k) by managing which elements we compare and keep track of.

Which data structure can we use to solve such problems? A heap is the best data structure to keep track of the smallest or largest k ...