< Previous
Next >
The median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value and the median is the mean of the two middle values.
- For example, for
arr = [2,3,4]
, the median is 3
.
- For example, for
arr = [2,3]
, the median is (2 + 3) / 2 = 2.5
.
Implement the MedianFinder class:
MedianFinder()
initializes the MedianFinder
object.
void addNum(int num)
adds the integer num
from the data stream to the data structure.
double findMedian()
returns the median of all elements so far. Answers within 10-5
of the actual answer will be accepted.
Example 1:
Input
["MedianFinder", "addNum", "addNum", "findMedian", "addNum", "findMedian"]
[[], [1], [2], [], [3], []]
Output
[null, null, null, 1.5, null, 2.0]
Explanation
MedianFinder medianFinder = new MedianFinder();
medianFinder.addNum(1); // arr = [1]
medianFinder.addNum(2); // arr = [1, 2]
medianFinder.findMedian(); // return 1.5 (i.e., (1 + 2) / 2)
medianFinder.addNum(3); // arr[1, 2, 3]
medianFinder.findMedian(); // return 2.0
Constraints:
-105 <= num <= 105
- There will be at least one element in the data structure before calling
findMedian
.
- At most
5 * 104
calls will be made to addNum
and findMedian
.
Follow up:
- If all integer numbers from the stream are in the range
[0, 100]
, how would you optimize your solution?
- If
99%
of all integer numbers from the stream are in the range [0, 100]
, how would you optimize your solution?
[Heap]
[Design]
Similar Questions
- Sliding Window Median (Hard)