Leetcode Find Median from Data Stream

Median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle value.
Examples: 

[2,3,4]

 , the median is 

3

[2,3]

, the median is 

(2
+ 3) / 2 = 2.5

Design a data structure that supports the following two operations:
void addNum(int num) - Add a integer number from the data stream to the data structure.
double findMedian() - Return the median of all elements so far.

For example:

add(1)
add(2)
findMedian() -> 1.5
add(3)
findMedian() -> 2

Difficulty: Hard

Solution 1: sort a ArrayList, nlogn, TLE:

public class MedianFinder {
int med = 0, left = 0, right = 0;
List<Integer> list = new ArrayList<Integer>();
boolean isFirst = true, isEven = true;

// Adds a number into the data structure.
public void addNum(int num) {
list.add(num);
if(isFirst){
left = 0;
right = 0;
med = num + num;
isFirst = false;
isEven = false;
}
else if(isEven){
isEven = (!isEven);
left++;
Collections.sort(list);
med = list.get(left) + list.get(right);
}
else{
isEven = (!isEven);
right++;
Collections.sort(list);
med = list.get(left) + list.get(right);
}
}

// Returns the median of current data stream
public double findMedian() {
return (((double)(med)) / 2);
}
};

// Your MedianFinder object will be instantiated and called as such:
// MedianFinder mf = new MedianFinder();
// mf.addNum(1);
// mf.findMedian();

Solution 2: Double Linked List (n), TLE:
class Node{
int val;
Node pre;
Node next;
public Node(int value){
val = value;
pre = null;
next = null;
}
}

public class MedianFinder {
Node root = null;
Node tail = null;
Node left = null;
Node right = null;
int len = 0;
// Adds a number into the data structure.

public void addNode(int num){
Node curr = new Node(num);
if(num >= tail.val){
tail.next = curr;
curr.pre = tail;
tail = curr;
if(len%2 == 1) right = right.next;
else left = left.next;
}
else if(num <= root.val){
root.pre = curr;
curr.next = root;
root = curr;
if(len%2 == 1) left = left.pre;
else right = right.pre;
}
else if(num < right.val && num > left.val){
right.pre = curr;
left.next = curr;
curr.next = right;
curr.pre = left;
right = curr; left = curr;
}
else if(num == right.val){
curr.next = right.next;
curr.pre = right;
right.next.pre = curr;
right.next = curr;
if(len%2 == 1) right = right.next;
else left = left.next;
}
else if(num == left.val){
curr.next = left;
curr.pre = left.pre;
left.pre.next = curr;
left.pre = curr;
if(len%2 == 1) left = left.pre;
else right = right.pre;
}
else{
Node temp;
if(num < left.val)
temp = root;
else
temp = right;
while(temp.val < num){
temp = temp.next;
}
curr.next = temp;
curr.pre = temp.pre;
temp.pre.next = curr;
temp.pre = curr;
if(num > right.val){
if(len%2 == 1) right = right.next;
else left = left.next;
}
else{
if(len%2 == 1) left = left.pre;
else right = right.pre;
}
}
}

public void addNum(int num) {
if(len == 0){
root = new Node(num);
tail = root;
left = root;
right = root;
len++;
}
else{
addNode(num);
len++;
}
}

// Returns the median of current data stream
public double findMedian() {
return (left.val + right.val) / 2.0;
}
};

// Your MedianFinder object will be instantiated and called as such:
// MedianFinder mf = new MedianFinder();
// mf.addNum(1);
// mf.findMedian();

Solution 3: Priority Queue(logn):

public class MedianFinder {
Queue<Integer> large = new PriorityQueue<Integer>();
Queue<Integer> small = new PriorityQueue<Integer>();
// Adds a number into the data structure.
public void addNum(int num) {
large.add(num);
small.add(-large.poll());
if(large.size() != small.size()){
large.add(-small.poll());
}

}

// Returns the median of current data stream
public double findMedian() {
if((large.size() + small.size()) % 2 == 1){
return large.peek();
}
else{
return (large.peek() - small.peek()) / 2.0;
}
}
};

// Your MedianFinder object will be instantiated and called as such:
// MedianFinder mf = new MedianFinder();
// mf.addNum(1);
// mf.findMedian();