346. Moving Average from Data Stream 🔒

March 20, 2025 · View on GitHub

Description

Given a stream of integers and a window size, calculate the moving average of all integers in the sliding window.

Implement the MovingAverage class:

MovingAverage(int size) Initializes the object with the size of the window size.
double next(int val) Returns the moving average of the last size values of the stream.

Example 1:

Input
["MovingAverage", "next", "next", "next", "next"]
[[3], [1], [10], [3], [5]]
Output
[null, 1.0, 5.5, 4.66667, 6.0]

Explanation
MovingAverage movingAverage = new MovingAverage(3);
movingAverage.next(1); // return 1.0 = 1 / 1
movingAverage.next(10); // return 5.5 = (1 + 10) / 2
movingAverage.next(3); // return 4.66667 = (1 + 10 + 3) / 3
movingAverage.next(5); // return 6.0 = (10 + 3 + 5) / 3

Constraints:

1 <= size <= 1000
-10⁵ <= val <= 10⁵
At most 10⁴ calls will be made to next.

We define a variable $\textit{s}$ to calculate the sum of the last $\textit{size}$ elements, and a variable $\textit{cnt}$ to record the total number of current elements. Additionally, we use an array $\textit{data}$ of length $\textit{size}$ to record the value of each element at each position.

When calling the $\textit{next}$ function, we first calculate the index $i$ where $\textit{val}$ should be stored, then update the sum $s$ , set the value at index $i$ to $\textit{val}$ , and increment the element count by one. Finally, we return the value of $\frac{s}{\min(\textit{cnt}, \textit{size})}$ .

The time complexity is $O(1)$ , and the space complexity is $O(n)$ , where $n$ is the integer $\textit{size}$ given in the problem.

Python3

class MovingAverage:

    def __init__(self, size: int):
        self.s = 0
        self.data = [0] * size
        self.cnt = 0

    def next(self, val: int) -> float:
        i = self.cnt % len(self.data)
        self.s += val - self.data[i]
        self.data[i] = val
        self.cnt += 1
        return self.s / min(self.cnt, len(self.data))


# Your MovingAverage object will be instantiated and called as such:
# obj = MovingAverage(size)
# param_1 = obj.next(val)

Java

class MovingAverage {
    private int s;
    private int cnt;
    private int[] data;

    public MovingAverage(int size) {
        data = new int[size];
    }

    public double next(int val) {
        int i = cnt % data.length;
        s += val - data[i];
        data[i] = val;
        ++cnt;
        return s * 1.0 / Math.min(cnt, data.length);
    }
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * MovingAverage obj = new MovingAverage(size);
 * double param_1 = obj.next(val);
 */

C++

class MovingAverage {
public:
    MovingAverage(int size) {
        data.resize(size);
    }

    double next(int val) {
        int i = cnt % data.size();
        s += val - data[i];
        data[i] = val;
        ++cnt;
        return s * 1.0 / min(cnt, (int) data.size());
    }

private:
    int s = 0;
    int cnt = 0;
    vector<int> data;
};

/**
 * Your MovingAverage object will be instantiated and called as such:
 * MovingAverage* obj = new MovingAverage(size);
 * double param_1 = obj->next(val);
 */

Go

type MovingAverage struct {
	s    int
	cnt  int
	data []int
}

func Constructor(size int) MovingAverage {
	return MovingAverage{
		data: make([]int, size),
	}
}

func (this *MovingAverage) Next(val int) float64 {
	i := this.cnt % len(this.data)
	this.s += val - this.data[i]
	this.data[i] = val
	this.cnt++
	return float64(this.s) / float64(min(this.cnt, len(this.data)))
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * obj := Constructor(size);
 * param_1 := obj.Next(val);
 */

TypeScript

class MovingAverage {
    private s: number = 0;
    private cnt: number = 0;
    private data: number[];

    constructor(size: number) {
        this.data = Array(size).fill(0);
    }

    next(val: number): number {
        const i = this.cnt % this.data.length;
        this.s += val - this.data[i];
        this.data[i] = val;
        this.cnt++;
        return this.s / Math.min(this.cnt, this.data.length);
    }
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * var obj = new MovingAverage(size)
 * var param_1 = obj.next(val)
 */

Solution 2: Queue

We can use a queue $\textit{q}$ to store the last $\textit{size}$ elements, and a variable $\textit{s}$ to record the sum of these $\textit{size}$ elements.

When calling the $\textit{next}$ function, we first check if the length of the queue $\textit{q}$ is equal to $\textit{size}$ . If it is, we dequeue the front element of the queue $\textit{q}$ and update the value of $\textit{s}$ . Then we enqueue $\textit{val}$ and update the value of $\textit{s}$ . Finally, we return the value of $\frac{s}{\text{len}(q)}$ .

The time complexity is $O(1)$ , and the space complexity is $O(n)$ , where $n$ is the integer $\textit{size}$ given in the problem.

Python3

class MovingAverage:
    def __init__(self, size: int):
        self.n = size
        self.s = 0
        self.q = deque()

    def next(self, val: int) -> float:
        if len(self.q) == self.n:
            self.s -= self.q.popleft()
        self.q.append(val)
        self.s += val
        return self.s / len(self.q)


# Your MovingAverage object will be instantiated and called as such:
# obj = MovingAverage(size)
# param_1 = obj.next(val)

Java

class MovingAverage {
    private Deque<Integer> q = new ArrayDeque<>();
    private int n;
    private int s;

    public MovingAverage(int size) {
        n = size;
    }

    public double next(int val) {
        if (q.size() == n) {
            s -= q.pollFirst();
        }
        q.offer(val);
        s += val;
        return s * 1.0 / q.size();
    }
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * MovingAverage obj = new MovingAverage(size);
 * double param_1 = obj.next(val);
 */

C++

class MovingAverage {
public:
    MovingAverage(int size) {
        n = size;
    }

    double next(int val) {
        if (q.size() == n) {
            s -= q.front();
            q.pop();
        }
        q.push(val);
        s += val;
        return (double) s / q.size();
    }

private:
    queue<int> q;
    int s = 0;
    int n;
};

/**
 * Your MovingAverage object will be instantiated and called as such:
 * MovingAverage* obj = new MovingAverage(size);
 * double param_1 = obj->next(val);
 */

Go

type MovingAverage struct {
	q []int
	s int
	n int
}

func Constructor(size int) MovingAverage {
	return MovingAverage{n: size}
}

func (this *MovingAverage) Next(val int) float64 {
	if len(this.q) == this.n {
		this.s -= this.q[0]
		this.q = this.q[1:]
	}
	this.q = append(this.q, val)
	this.s += val
	return float64(this.s) / float64(len(this.q))
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * obj := Constructor(size);
 * param_1 := obj.Next(val);
 */

TypeScript

class MovingAverage {
    private q: number[] = [];
    private s: number = 0;
    private n: number;

    constructor(size: number) {
        this.n = size;
    }

    next(val: number): number {
        if (this.q.length === this.n) {
            this.s -= this.q.shift()!;
        }
        this.q.push(val);
        this.s += val;
        return this.s / this.q.length;
    }
}

/**
 * Your MovingAverage object will be instantiated and called as such:
 * var obj = new MovingAverage(size)
 * var param_1 = obj.next(val)
 */

346. Moving Average from Data Stream 🔒

Description

Solutions

Solution 1: Circular Array

Python3

Java

C++

Go

TypeScript

Solution 2: Queue

Python3

Java

C++

Go

TypeScript