# LeetCode 23. Merge k Sorted Lists(java)

Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity.

Solution 1: use heap to do it. First, put the first element of K lists into heap. After each poll, put it into the next element of the poll until the heap is empty. The time complexity is O (mklogk), and the space complexity is O (k)

``````public ListNode mergeKLists(ListNode[] lists) {
if (lists == null || lists.length == 0) return null;
if (lists.length == 1) return lists[0];
PriorityQueue<ListNode> queue = new PriorityQueue<>(new Comparator<ListNode>() {
public int compare(ListNode o1, ListNode o2) {
return o1.val - o2.val;
}
});
for (int i = 0; i < lists.length; i++) {
}
ListNode dummy = new ListNode(-1), cur = dummy;
while (!queue.isEmpty()) {
ListNode temp = queue.poll();
cur.next = temp;
cur = temp;
}
return dummy.next;
}``````

Solution 2: the idea of merge sort is better than solution 1. List merges in pairs each time, until the merges into a list, the time complexity is O ((M / 2) (K / 2 + K / 4 + K / 8 +…) ）It is O (kmlogk), but it has a constant number of optimizations than method one. The space complexity is O (1)

``````public ListNode mergeKLists(ListNode[] lists) {
if (lists == null || lists.length == 0) return null;
int begin = 0, end = lists.length - 1;
while (begin < end) {
int mid = (begin + end - 1) / 2;
for (int i = 0; i <= mid; i++) {
lists[i] = merge2list(lists[i], lists[end - i]);
}
end = (begin + end) / 2;
}
return lists[0];
}
public ListNode merge2list(ListNode l1, ListNode l2) {
if (l1 == null && l2 == null) return null;
if (l1 == null) return l2;
if (l2 == null) return l1;
ListNode dummy = new ListNode(-1), cur = dummy;
while (l1 != null && l2 != null) {
if (l1.val < l2.val) {
cur.next = l1;
cur = l1;
l1 = l1.next;
} else {
cur.next = l2;
cur = l2;
l2 = l2.next;
}
}
if (l1 != null) cur.next = l1;
if (l2 != null) cur.next = l2;
return dummy.next;
}``````