• Home
• com.github.javadev
• leetcode-in-kotlin
• 1.20
• source code
• readme.md

×

Project download

Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance.
Project price only 1 $

You can buy this project and download/modify it how often you want.

g0201_0300.s0295_find_median_from_data_stream.readme.md Maven / Gradle / Ivy

295\. Find Median from Data Stream

Hard

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?