Easy Heap Question 49 of 224

How do you find the kth largest element in an array using a heap?

DSA interview set · Speak this in 60–90 seconds · Faridabad & Delhi NCR

01234

Index starts at 0. Scan once for max — O(n).

Keep a min-heap of size k: push each number and pop when the heap grows past k so the root is the kth largest.

Why interviewers care about Heap:

This is a process

question about Heap.

Panels listen for order,

trade-offs, and what you would actually do on a DSA project - not buzzwords.

Stay structured

Name the idea, why it exists, then one short example.

Close cleanly

End with when you use it and one common pitfall.

Before you speak the answer, walk the interviewer through these steps:

1
Keep a min-heap of
size k: push each number and pop when the heap grows past k so the root is the kth largest.
2
Time is O(n log
k) and space is O(k).
3
A max-heap of the
whole array is O(n + k log n) after heapify, worse when k is much smaller than n.
4
Give an example
One tiny concrete case you can say aloud.
5
Common mistake
What juniors usually get wrong.
6
Close
When you pick this over the alternative.

Here's a short line you can speak, broken into clear beats:

Say this line

“Time is O(n log k) and space is O(k).”

Break into beats

TimeisOnlogk

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

Keep a min-heap of size k: push each number and pop when the heap grows past k so the root is the kth largest. Time is O(n log k) and space is O(k).