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tech-interview-handbook/contents/algorithms/heap.md

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id title description keywords sidebar_label toc_max_heading_level
heap Heap cheatsheet for coding interviews Heap study guide for coding interviews, including practice questions, techniques, time complexity, and recommended resources
heap coding interview study guide
heap tips for coding interviews
heap practice questions
heap useful techniques
heap time complexity
heap recommended study resources
Heap 2
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Introduction

A heap is a specialized tree-based data structure which is a complete tree that satisfies the heap property.

  • Max heap - In a max heap the value of a node must be greatest among the node values in its entire subtree. The same property must be recursively true for all nodes in the tree.
  • Min heap - In a min heap the value of a node must be smallest among the node values in its entire subtree. The same property must be recursively true for all nodes in the tree.

In the context of algorithm interviews, heaps and priority queues can be treated as the same data structure. A heap is a useful data structure when it is necessary to repeatedly remove the object with the highest (or lowest) priority, or when insertions need to be interspersed with removals of the root node.

Learning resources

Implementations

Language API
C++ std::priority_queue
Java java.util.PriorityQueue
Python heapq
JavaScript N/A

Time complexity

Operation Big-O
Find max/min O(1)
Insert O(log(n))
Remove O(log(n))
Heapify (create a heap out of given array of elements) O(n)

Techniques

Mention of k

If you see a top or lowest k being mentioned in the question, it is usually a signal that a heap can be used to solve the problem, such as in Top K Frequent Elements.

If you require the top k elements use a Min Heap of size k. Iterate through each element, pushing it into the heap (for python heapq, invert the value before pushing to find the max). Whenever the heap size exceeds k, remove the minimum element, that will guarantee that you have the k largest elements.

import AlgorithmCourses from '../_courses/AlgorithmCourses.md'