How do you solve Nth Highest Salary on LeetCode?

Nth Highest Salary (LeetCode #177) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Using distinct salaries is crucial to avoid duplicates affecting the nth highest calculation.

What is the time complexity of Nth Highest Salary?

The optimal solution for Nth Highest Salary runs in O(n) time and uses O(n) space. Collecting distinct salaries takes O(n) time, and maintaining a heap of size n also takes O(n) time.

What is the brute force solution for Nth Highest Salary?

The brute force approach for Nth Highest Salary is Brute Force, with O(n log n) time complexity and O(n) space complexity. The brute-force approach involves sorting all distinct salaries and then selecting the nth highest. This is straightforward but inefficient for large datasets. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Nth Highest Salary?

Nth Highest Salary uses the following concepts: Database. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Nth Highest Salary?

Always clarify the requirements, especially regarding distinct values. Discuss your thought process and reasoning for each step during the interview. Practice writing SQL queries on paper or a whiteboard to simulate the interview environment.

What are common mistakes when solving Nth Highest Salary?

Forgetting to handle cases where there are fewer than n distinct salaries. Not using DISTINCT in the SQL query, which leads to incorrect results.

#177

Nth Highest Salary

Medium

DatabaseHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n log n)	O(n)
Space	O(n)	O(n)

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Intuition

Time O(n)Space O(n)

The optimal approach uses a set to track distinct salaries and a min-heap to efficiently find the nth highest salary without sorting all salaries.

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Algorithm

4 steps

1Step 1: Use a set to collect distinct salaries from the Employee table.
2Step 2: If the size of the set is less than n, return null.
3Step 3: Convert the set to a min-heap and pop elements until only n elements remain.
4Step 4: The root of the heap will be the nth highest salary.

solution.py1 lines

1WITH distinct_salaries AS (SELECT DISTINCT salary FROM Employee) SELECT salary FROM (SELECT salary FROM distinct_salaries ORDER BY salary DESC LIMIT n) AS temp ORDER BY salary ASC LIMIT 1;

ℹ

Complexity note: Collecting distinct salaries takes O(n) time, and maintaining a heap of size n also takes O(n) time.

1Using distinct salaries is crucial to avoid duplicates affecting the nth highest calculation.
2Min-heaps are efficient for maintaining the top n elements without needing to sort all salaries.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.