{ "data": { "question": { "questionId": "295", "questionFrontendId": "295", "boundTopicId": null, "title": "Find Median from Data Stream", "titleSlug": "find-median-from-data-stream", "content": "
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.
\n\narr = [2,3,4]
, the median is 3
.arr = [2,3]
, the median is (2 + 3) / 2 = 2.5
.Implement the MedianFinder class:
\n\nMedianFinder()
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.\n
Example 1:
\n\n\nInput\n["MedianFinder", "addNum", "addNum", "findMedian", "addNum", "findMedian"]\n[[], [1], [2], [], [3], []]\nOutput\n[null, null, null, 1.5, null, 2.0]\n\nExplanation\nMedianFinder medianFinder = new MedianFinder();\nmedianFinder.addNum(1); // arr = [1]\nmedianFinder.addNum(2); // arr = [1, 2]\nmedianFinder.findMedian(); // return 1.5 (i.e., (1 + 2) / 2)\nmedianFinder.addNum(3); // arr[1, 2, 3]\nmedianFinder.findMedian(); // return 2.0\n\n\n
\n
Constraints:
\n\n-105 <= num <= 105
findMedian
.5 * 104
calls will be made to addNum
and findMedian
.\n
Follow up:
\n\n[0, 100]
, how would you optimize your solution?99%
of all integer numbers from the stream are in the range [0, 100]
, how would you optimize your solution?Compiled with clang 11
using the latest C++ 17 standard.
Your code is compiled with level two optimization (-O2
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Most standard library headers are already included automatically for your convenience.
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