Hard
You are given two integers, m
and k
, and a stream of integers. You are tasked to implement a data structure that calculates the MKAverage for the stream.
The MKAverage can be calculated using these steps:
m
you should consider the MKAverage to be -1
. Otherwise, copy the last m
elements of the stream to a separate container.k
elements and the largest k
elements from the container.Implement the MKAverage
class:
MKAverage(int m, int k)
Initializes the MKAverage object with an empty stream and the two integers m
and k
.void addElement(int num)
Inserts a new element num
into the stream.int calculateMKAverage()
Calculates and returns the MKAverage for the current stream rounded down to the nearest integer.Example 1:
Input [“MKAverage”, “addElement”, “addElement”, “calculateMKAverage”, “addElement”, “calculateMKAverage”, “addElement”, “addElement”, “addElement”, “calculateMKAverage”] [[3, 1], [3], [1], [], [10], [], [5], [5], [5], []]
Output: [null, null, null, -1, null, 3, null, null, null, 5]
Explanation: MKAverage obj = new MKAverage(3, 1); obj.addElement(3); // current elements are [3] obj.addElement(1); // current elements are [3,1] obj.calculateMKAverage(); // return -1, because m = 3 and only 2 elements exist. obj.addElement(10); // current elements are [3,1,10] obj.calculateMKAverage(); // The last 3 elements are [3,1,10]. // After removing smallest and largest 1 element the container will be [3]. // The average of [3] equals 3/1 = 3, return 3 obj.addElement(5); // current elements are [3,1,10,5] obj.addElement(5); // current elements are [3,1,10,5,5] obj.addElement(5); // current elements are [3,1,10,5,5,5] obj.calculateMKAverage(); // The last 3 elements are [5,5,5]. // After removing smallest and largest 1 element the container will be `[5]. // The average of [5] equals 5/1 = 5, return 5`
Constraints:
3 <= m <= 105
1 <= k*2 < m
1 <= num <= 105
105
calls will be made to addElement
and calculateMKAverage
.import java.util.ArrayDeque;
import java.util.Deque;
import java.util.TreeMap;
@SuppressWarnings("java:S2184")
public class MKAverage {
private final double m;
private final double k;
private final double c;
private double avg;
private final Bst middle;
private final Bst min;
private final Bst max;
private final Deque<Integer> q;
public MKAverage(int m, int k) {
this.m = m;
this.k = k;
this.c = m - k * 2;
this.avg = 0;
this.middle = new Bst();
this.min = new Bst();
this.max = new Bst();
this.q = new ArrayDeque<>();
}
public void addElement(int num) {
if (min.size < k) {
min.add(num);
q.offer(num);
return;
}
if (max.size < k) {
min.add(num);
max.add(min.removeMax());
q.offer(num);
return;
}
if (num >= min.lastKey() && num <= max.firstKey()) {
middle.add(num);
avg += num / c;
} else if (num < min.lastKey()) {
min.add(num);
int val = min.removeMax();
middle.add(val);
avg += val / c;
} else if (num > max.firstKey()) {
max.add(num);
int val = max.removeMin();
middle.add(val);
avg += val / c;
}
q.offer(num);
if (q.size() > m) {
num = q.poll();
if (middle.containsKey(num)) {
avg -= num / c;
middle.remove(num);
} else if (min.containsKey(num)) {
min.remove(num);
int val = middle.removeMin();
avg -= val / c;
min.add(val);
} else if (max.containsKey(num)) {
max.remove(num);
int val = middle.removeMax();
avg -= val / c;
max.add(val);
}
}
}
public int calculateMKAverage() {
if (q.size() < m) {
return -1;
}
return (int) avg;
}
static class Bst {
TreeMap<Integer, Integer> map;
int size;
public Bst() {
this.map = new TreeMap<>();
this.size = 0;
}
void add(int num) {
int count = map.getOrDefault(num, 0) + 1;
map.put(num, count);
size++;
}
void remove(int num) {
int count = map.getOrDefault(num, 1) - 1;
if (count > 0) {
map.put(num, count);
} else {
map.remove(num);
}
size--;
}
int removeMin() {
int key = map.firstKey();
remove(key);
return key;
}
int removeMax() {
int key = map.lastKey();
remove(key);
return key;
}
boolean containsKey(int key) {
return map.containsKey(key);
}
int firstKey() {
return map.firstKey();
}
int lastKey() {
return map.lastKey();
}
}
}