Top K Elements (Selection/Frequency) — Heap (Priority Queue) Patterns
The Top K Elements (Selection/Frequency) pattern applies when you need the Top K Elements (Selection/Frequency) technique within the Heap (Priority Queue) Patterns pattern. Its time complexity is O(n log k) and space complexity O(k). It is used in 8 problems on Thita, including K Closest Points to Origin, Kth Largest Element in an Array and Kth Largest Element in a Stream. Common variations are Two Heaps for Median Finding and K-way Merge.
Find top K elements using heap. Solve kth largest, top K frequent, and k closest points problems.
Top K Elements (Selection/Frequency) is one of the 4 subpatterns of the Heap (Priority Queue) Patterns pattern, which covers top K elements, K-way merge, two heaps for median, and scheduling. The whole pattern is about 2 hours of study. This subpattern is a core technique: expect it to come up directly in interviews.
What Top K Elements (Selection/Frequency) covers
Master heap-based algorithms including top K elements, two heaps for median, K-way merge, and scheduling problems with priority queues. Problems in this subpattern are usually searched for as top k elements, kth largest, top k frequent, k closest points, heap selection, leetcode 215.
How to practise Top K Elements (Selection/Frequency) on Thita.ai
Read the theory for Top K Elements (Selection/Frequency), then work the problems attached to it in the browser editor. Your solution runs against the problem's test cases, and the AI coach offers a hint about the technique you are missing rather than a finished solution. Progress is tracked per subpattern, so the Heap (Priority Queue) Patterns tracker shows this one as covered once you have solved its problems.
Other subpatterns in Heap (Priority Queue) Patterns
- K-way Merge — Master K-way merge pattern using min heap. Merge k sorted lists and find kth smallest in matrix.
- Two Heaps for Median Finding — Master the two heaps technique to find median from data stream in O(log n) time.
- Scheduling / Minimum Cost (Greedy with Priority Queue) — Solve scheduling and optimization problems using priority queue with greedy approach.
Related DSA patterns
- String Manipulation Patterns — Palindrome checking, anagram detection, pattern matching, and string conversion.
- Tree Traversal Patterns (DFS & BFS) — Preorder, inorder, level order traversal, LCA, and serialization.
- Greedy Patterns — Interval scheduling, jump games, stock trading, and task scheduling.
- Backtracking Patterns — Subsets, permutations, combinations, N-Queens, and word search.
Where to go next
Top K Elements (Selection/Frequency) is one lesson in a 16-pattern DSA course. If you are preparing end to end, work the interview-critical patterns first and use the pattern sheet as the checklist; if you are here for one technique, the Heap (Priority Queue) Patterns guide is the shortest path back to the rest of it.