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median_stream.cpp
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median_stream.cpp
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/*
* Source : Leetcode, 295. Find Median from Data Stream
* Category : hard
*
* Find median from a data stream. Design a data structure that supports addNum to add a number to the stream,
* and findMedian to return the median of the current numbers seen so far. Also, if the count of numbers is
* even, return average of two middle elements, return median otherwise.
*
* In naive approach, we could maintain an internal vector and sort the array everytime median is requested,
* and return the middle element(when odd count) or mean of two middle elements (when mean count)
*
* However, this doesn't scale well as the size of the vector grows, and if 'findMedian' is accessed too
* frequently. We would want a potentially better solution which could reduce the cost of finding median,
* even though we might make add a little slow.
*
* We could use something which maintains a ordered stream of numbers, and median could be retrieved in O(1)
* time, and add could be done in O(logn) time.
*
* This could be achieved using a Self-Balanced Binary search tree, or using two heaps.
* We will currently solve with a heap approach.
*
* Why two heaps?
* We want two middle numbers (in even count case), so if we maintain two heaps, one min-heap and other
* max-heap, the max-heap will maintain the lower ordered half of the numbers while the min-heap would
* maintained the upper half of the numbers.
* Consider even number of numbers in stream so far, in that case, the top of the lower heap (max heap)
* will contain the left middle number of the stream and top of upper heap (min heap) will contain the
* right middle number of the stream. Thus we could retrive the two middle numbers in O(1) time.
*
* [1, 2, 3, 4, 5] <-- values in lower heap. (MAX heap)
* [6, 7, 8, 9, 10] <-- Values in upper heap. (MIN heap)
*
* lower.top() = 5
* upper.top() = 6
* So we will want (6+5)/2 = 5.5 as answer.
*
* Now, the algorithm:
* In order to maintain the two middle numbers of the stream on the top of the two heaps,
* we will have to balance them with each addition of new number.
*
* In case of odd numbers, the lower heap will contain 1 number extra then the upper heap.
* In case of even numbers, both the heaps will have equal numbers of elements.
*
* As we add a new number, we will add it to lower, then we will balance the heaps by transferring
* the top to upper heap, and then we will maintain the size property maintained above.
*/
#include <iostream>
#include <queue>
#include <vector>
#include <random>
#include <algorithm>
class MedianFinder {
public:
MedianFinder() {}
void addNum(int num)
{
// first add it to lower.
lower.push(num);
// balance the heaps to set the right values at the top.
upper.push(lower.top());
lower.pop();
// Maintain the size property.
if (lower.size() < upper.size()) {
lower.push(upper.top());
upper.pop();
}
}
double findMedian()
{
return (lower.size() > upper.size()) ? static_cast<double>(lower.top()) :
(static_cast<double>(lower.top() + upper.top()) / 2);
}
// utility function to print current sorted stream.
void printSortedStream()
{
std::priority_queue<int> lc{lower};
std::priority_queue<int, std::vector<int>, std::greater<int>> uc{upper};
std::vector<int> temp;
// lower half first;
while(!lc.empty()){
temp.push_back(lc.top());
lc.pop();
}
std::reverse(temp.begin(), temp.end());
for (auto n: temp) {
std::cout << n << " ";
}
while (!uc.empty()) {
std::cout << uc.top() << " ";
uc.pop();
}
std::cout << std::endl;
}
private:
// max heap maintaining the lower half of ordered stream.
std::priority_queue<int> lower;
// min heap maintaining the upper half of ordered stream.
std::priority_queue<int, std::vector<int>, std::greater<int>> upper;
};
int main()
{
std::default_random_engine generator;
std::uniform_int_distribution<int> distribution(0,20);
MedianFinder medianFinder;
for (int i=0; i<5; ++i)
{
medianFinder.addNum(distribution(generator));
}
// current state of stream
medianFinder.printSortedStream();
std::cout << "Median of current stream: " << medianFinder.findMedian()
<< std::endl;
// Add 5 more.
//
for (int i=0; i<5; ++i)
{
medianFinder.addNum(distribution(generator));
}
// current state of stream
medianFinder.printSortedStream();
std::cout << "Median of current stream: " << medianFinder.findMedian()
<< std::endl;
return 0;
}