362 Design Hit Counter

Design a hit counter which counts the number of hits received in the past 5 minutes.

Each function accepts a timestamp parameter (in seconds granularity) and you may assume that calls are being made to the system in chronological order (ie, the timestamp is monotonically increasing). You may assume that the earliest timestamp starts at 1.

It is possible that several hits arrive roughly at the same time.

Example:

HitCounter counter = new HitCounter();

// hit at timestamp 1.
counter.hit(1);

// hit at timestamp 2.
counter.hit(2);

// hit at timestamp 3.
counter.hit(3);

// get hits at timestamp 4, should return 3.
counter.getHits(4);

// hit at timestamp 300.
counter.hit(300);

// get hits at timestamp 300, should return 4.
counter.getHits(300);

// get hits at timestamp 301, should return 3.
counter.getHits(301); 
Follow up:
What if the number of hits per second could be very large? Does your design scale?

#include <iostream>
#include <queue>

using namespace std;

class HitCounter {
public:
    HitCounter() {

    }

    void hit(int timeStamp) {
        timeStamps.push(timeStamp);
    }

    int getHits(int timeStamp) {
        while (!timeStamps.empty() && timeStamp - timeStamps.front() >= 300) {
            timeStamps.pop();
        }
        return timeStamps.size();
    }


private:
    queue<int> timeStamps;

};

int main() {
    HitCounter *counter = new HitCounter();

    // hit at timestamp 1.
    counter->hit(1);

    // hit at timestamp 2.
    counter->hit(2);

    // hit at timestamp 3.
    counter->hit(3);

    // get hits at timestamp 4, should return 3.
    int test1 = counter->getHits(4);
    cout << test1 << endl;

    // hit at timestamp 300.
    counter->hit(300);

    // get hits at timestamp 300, should return 4.
    test1 = counter->getHits(300);
    cout << test1 << endl;

    // get hits at timestamp 301, should return 3.
    test1 = counter->getHits(301);
    cout << test1 << endl;
}

Python

The Idea: Keep a container of timestamps. Then iterate through the timestamps and count the ones that don't exceed the 5 minute threshold (300 seconds). Then number is with the 5 minute threshold, if when we add 300 it falls after the allotted time stamp. Since times are monotonically increasing, we can stop counting once our time stamp iterable exceeds the maximum time stamp. Possible improvement: binary search to two areas: the start and end of the 300 period, then return the distance between these two numbers.

Complexity: hit- O(1), getHits() - O(n). O(n) space total, where n is the total number of hits.

class HitCounter(object):

    def __init__(self):
        """
        Initialize your data structure here.
        """
        self.hits = []


    def hit(self, timestamp):
        """
        Record a hit.
        @param timestamp - The current timestamp (in seconds granularity).
        :type timestamp: int
        :rtype: void
        """
        self.hits.append(timestamp)


    def getHits(self, timestamp):
        """
        Return the number of hits in the past 5 minutes.
        @param timestamp - The current timestamp (in seconds granularity).
        :type timestamp: int
        :rtype: int
        """
        counter = 0
        for hit_ts in self.hits:
            if hit_ts > timestamp:
                break
            if hit_ts + 300 > timestamp:
                counter += 1
        return counter


# Your HitCounter object will be instantiated and called as such:
# obj = HitCounter()
# obj.hit(timestamp)
# param_2 = obj.getHits(timestamp)