How do you solve Find Consecutive Integers from a Data Stream on LeetCode?

Find Consecutive Integers from a Data Stream (LeetCode #2526) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: Using a counter for consecutive values can significantly reduce time complexity.

What is the brute force solution for Find Consecutive Integers from a Data Stream?

The brute force approach for Find Consecutive Integers from a Data Stream is Brute Force, with O(n²) time complexity and O(n) space complexity. The brute-force approach checks the last k integers every time a new integer is added. This means we will repeatedly scan the last k integers to see if they all match the specified value. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find Consecutive Integers from a Data Stream?

Find Consecutive Integers from a Data Stream uses the following concepts: Hash Table, Design, Queue, Counting, Data Stream. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Find Consecutive Integers from a Data Stream?

Think about how to optimize the solution before coding. Always consider edge cases, such as when fewer than k integers have been added. Explain your thought process clearly while coding.

What are common mistakes when solving Find Consecutive Integers from a Data Stream?

Not resetting the count when a different number is encountered. Failing to check if the total count is at least k before returning true.

#2526

Find Consecutive Integers from a Data Stream

Medium

Hash TableDesignQueueCountingData StreamHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(1)

Instead of storing all integers, we can maintain a count of consecutive integers equal to the specified value. This allows us to check the condition in constant time.

⚙️

Algorithm

4 steps

1Step 1: Initialize a counter for consecutive values and a variable to track the total number of integers added.
2Step 2: For each new integer, check if it equals the specified value.
3Step 3: If it does, increment the counter; if not, reset the counter to zero.
4Step 4: If the total count of integers is at least k and the counter equals k, return true; otherwise, return false.

solution.py14 lines

1class DataStream:
2    def __init__(self, value: int, k: int):
3        self.value = value
4        self.k = k
5        self.count = 0
6        self.total = 0
7
8    def consec(self, num: int) -> bool:
9        self.total += 1
10        if num == self.value:
11            self.count += 1
12        else:
13            self.count = 0
14        return self.count == self.k and self.total >= self.k

ℹ

Complexity note: The time complexity is O(n) because we process each integer once, and the space complexity is O(1) since we only use a few variables to keep track of counts.

1Using a counter for consecutive values can significantly reduce time complexity.
2Maintaining a total count helps in determining if we have enough integers to check against k.

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