How do you solve Rising Temperature on LeetCode?

Rising Temperature (LeetCode #197) 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: Understanding how to use self-joins can significantly optimize queries involving comparisons.

What algorithm or data structure is used to solve Rising Temperature?

Rising Temperature uses the following concepts: Database. The recommended patterns to study are: Self-Join, Date Manipulation.

What are the interview tips for Rising Temperature?

Always clarify the requirements and constraints of the problem before jumping into coding. Think about the time and space complexity of your solution and be prepared to explain it. Practice writing SQL queries on paper or in a simple editor to get comfortable with syntax and logic.

What are common mistakes when solving Rising Temperature?

Not considering edge cases, such as the first record which has no previous day to compare. Overcomplicating the query structure when a simple join suffices.

#197

Rising Temperature

Easy

DatabaseSelf-JoinDate Manipulation

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal solution uses a self-join to efficiently compare each day's temperature with the previous day's temperature, reducing the number of comparisons needed.

⚙️

Algorithm

3 steps

1Step 1: Use a self-join on the Weather table to connect each record with its previous day's record.
2Step 2: Filter the results where the current day's temperature is greater than the previous day's temperature.
3Step 3: Select the id of the records that meet the criteria.

solution.py1 lines

1SELECT w1.id FROM Weather w1 JOIN Weather w2 ON DATE_ADD(w2.recordDate, INTERVAL 1 DAY) = w1.recordDate WHERE w1.temperature > w2.temperature;

ℹ

Complexity note: This complexity is linear because each record is processed a constant number of times, and we only store results for qualifying records.

1Understanding how to use self-joins can significantly optimize queries involving comparisons.
2Recognizing patterns in data (like daily temperatures) can help in structuring queries effectively.

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