How do you solve Design an Ordered Stream on LeetCode?

Design an Ordered Stream (LeetCode #1656) 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 a pointer to track the next expected index allows for efficient retrieval of contiguous values.

What is the brute force solution for Design an Ordered Stream?

The brute force approach for Design an Ordered Stream is Brute Force, with O(n²) time complexity and O(1) space complexity. In the brute-force approach, we maintain an array to store the values at their respective indices. Each time we insert a new value, we check the entire array to see if we can return any values in order. This is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Design an Ordered Stream?

Design an Ordered Stream uses the following concepts: Array, Hash Table, Design, Data Stream. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Design an Ordered Stream?

Always clarify the constraints and requirements of the problem before jumping into coding. Think about how you can optimize your solution after writing the brute-force version. Practice explaining your thought process clearly, as communication is key in interviews.

What are common mistakes when solving Design an Ordered Stream?

Not maintaining the pointer correctly, which can lead to missing values or incorrect outputs. Overcomplicating the solution by trying to sort or rearrange values instead of using a direct index-based approach.

#1656

Design an Ordered Stream

Easy

ArrayHash TableDesignData StreamHash MapArray

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 approach uses a pointer to track the next expected index to return values. This allows us to efficiently collect all contiguous values in a single pass without needing to check the entire array each time.

⚙️

Algorithm

3 steps

1Step 1: Initialize an array of size n to store values and a pointer to track the next expected index.
2Step 2: For each insert, place the value in the array at the index idKey - 1.
3Step 3: Use the pointer to return the largest possible chunk of contiguous values starting from the pointer.

solution.py12 lines

1class OrderedStream:
2    def __init__(self, n: int):
3        self.stream = [None] * n
4        self.ptr = 0
5
6    def insert(self, idKey: int, value: str):
7        self.stream[idKey - 1] = value
8        result = []
9        while self.ptr < len(self.stream) and self.stream[self.ptr] is not None:
10            result.append(self.stream[self.ptr])
11            self.ptr += 1
12        return result

ℹ

Complexity note: The time complexity is O(n) because each insertion can potentially lead to a single traversal of the array, but each element is only processed once. The space complexity is O(n) due to the storage of the values.

1Using a pointer to track the next expected index allows for efficient retrieval of contiguous values.
2The problem can be solved using a simple array since the ids are guaranteed to be between 1 and n.

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