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

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---
id: heap
title: Heap
---
## Study links
- [Learning to Love Heaps](https://medium.com/basecs/learning-to-love-heaps-cef2b273a238)
## Notes
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](https://leetcode.com/problems/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. Whenever the heap size exceeds _k_, remove the minimum element, that will guarantee that you have the _k_ largest elements.
## Recommended LeetCode questions
- [Merge K Sorted Lists](https://leetcode.com/problems/merge-k-sorted-lists/)
- [Top K Frequent Elements](https://leetcode.com/problems/top-k-frequent-elements/)
- [Find Median from Data Stream](https://leetcode.com/problems/find-median-from-data-stream/)
## Recommended courses
import AlgorithmCourses from '../\_courses/AlgorithmCourses.md'
<AlgorithmCourses />