How do you solve Not Boring Movies on LeetCode?

Not Boring Movies (LeetCode #620) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n log n) time complexity and O(n) space complexity. Key insight: Filtering based on conditions (odd ID and non-boring description) is crucial for the solution.

What is the time complexity of Not Boring Movies?

The optimal solution for Not Boring Movies runs in O(n log n) time and uses O(n) space. The time complexity is O(n log n) due to the sorting operation, while the space complexity remains O(n) for storing the results.

What is the brute force solution for Not Boring Movies?

The brute force approach for Not Boring Movies is Brute Force, with O(n) time complexity and O(n) space complexity. In the brute force approach, we will iterate through each movie in the Cinema table and check if the ID is odd and if the description is not 'boring'. If both conditions are met, we will add the movie to our results. This method is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Not Boring Movies?

Not Boring Movies uses the following concepts: Database. The recommended patterns to study are: Filtering with WHERE clause, Sorting results with ORDER BY.

What are the interview tips for Not Boring Movies?

Always clarify the problem requirements and constraints before jumping into coding. Think about edge cases, such as all movies being boring or no odd IDs. Practice writing SQL queries on paper or a whiteboard to get comfortable with syntax.

What are common mistakes when solving Not Boring Movies?

Not applying the correct filtering conditions in the WHERE clause. Forgetting to sort the results before returning them.

#620

Not Boring Movies

Easy

DatabaseFiltering with WHERE clauseSorting results with ORDER BY

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n log n)Space O(n)

The optimal solution leverages SQL's filtering and sorting capabilities directly. By using a single query that checks for odd IDs and non-boring descriptions, we can efficiently retrieve and sort the desired results in one go.

⚙️

Algorithm

3 steps

1Step 1: Use a SELECT statement to get the required columns from the Cinema table.
2Step 2: Apply a WHERE clause to filter for odd IDs and descriptions that are not 'boring'.
3Step 3: Use ORDER BY to sort the results by rating in descending order.

solution.py1 lines

1SELECT id, movie, description, rating FROM Cinema WHERE id % 2 = 1 AND description != 'boring' ORDER BY rating DESC;

ℹ

Complexity note: The time complexity is O(n log n) due to the sorting operation, while the space complexity remains O(n) for storing the results.

1Filtering based on conditions (odd ID and non-boring description) is crucial for the solution.
2Sorting the results by rating ensures we return the highest-rated movies first.

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