Introduction to Top K Elements
Explore the Top K Elements pattern to efficiently identify a subset of largest, smallest, or most frequent elements in an unsorted list. Learn how to use min and max heaps in C++ to maintain and retrieve these elements, improving time complexity from full sorting to O(n log k). Understand applications of this pattern in real-world problems like ride-sharing, finance, and social media analysis, and practice implementing it with clear examples.
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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 , 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 time, and then select the top k elements, taking additional time. However, the top k elements pattern bypasses the need for full sorting, reducing the time complexity to 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 ...