Problem: Find the sum of weights of edges of the Minimum Spanning Tree for a given weighted undirected graph G = (V, E).

Constraints

* 1 ≤ |V| ≤ 10,000
* 0 ≤ |E| ≤ 100,000
* 0 ≤ wi ≤ 10,000
* The graph is connected
* There are no parallel edges
* There are no self-loops

Input


|V| |E|
s0 t0 w0
s1 t1 w1
:
s|E|-1 t|E|-1 w|E|-1


, where |V| is the number of vertices and |E| is the number of edges in the graph. The graph vertices are named with the numbers 0, 1,..., |V|-1 respectively.

si and ti represent source and target verticess of i-th edge (undirected) and wi represents the weight of the i-th edge.

Output

Print the sum of the weights of the Minimum Spanning Tree.

Examples

Input

4 6
0 1 2
1 2 1
2 3 1
3 0 1
0 2 3
1 3 5


Output

3


Input

6 9
0 1 1
0 2 3
1 2 1
1 3 7
2 4 1
1 4 3
3 4 1
3 5 1
4 5 6


Output

5

Solution (in PYTHON3):

Solution:
import sys
readline = sys.stdin.readline


class UnionFind:
    __slots__ = ["nodes"]

    def __init__(self, n: int) -> None:
        self.nodes = [-1]*n

    def get_root(self, x: int) -> int:
        if self.nodes[x] < 0:
            return x
        else:
            self.nodes[x] = self.get_root(self.nodes[x])
            return self.nodes[x]

    def unite(self, x: int, y: int) -> bool:
        root_x, root_y = self.get_root(x), self.get_root(y)
        if root_x != root_y:
            bigroot, smallroot = \
                (root_x, root_y) if self.nodes[root_x] < self.nodes[root_y] else (root_y, root_x)
            self.nodes[bigroot] += self.nodes[smallroot]
            self.nodes[smallroot] = bigroot
            return True
        else:
            return False


def kruskal(n: int, edges: list) -> int:
    edges.sort()
    tree = UnionFind(n)
    total = 0
    cnt = 0
    for w, s, t in edges:
        if tree.unite(s, t):
            cnt += 1
            total += w
            if cnt == n - 1:
                break

    return total


V, E = map(int, readline().split())
edges = []
append = edges.append
for _ in [None]*E:
    s, t, w = map(int, readline().split())
    append((w, s, t))
print(kruskal(V, edges))