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:
class UnionFind:
    def __init__(self, n):
        self.p = [i for i in range(n)]
        self.rank = [1]*n
    
    def root(self, x):
        if x == self.p[x]:
            return x
        self.p[x] = y = self.root(self.p[x])
        return y
    
    def unite(self, x, y):
        px = self.root(x); py = self.root(y)
        if px == py:
            return 0
        rx = self.rank[px]; ry = self.rank[py]
        if ry < rx:
            self.p[py] = px
        elif rx < ry:
            self.p[px] = py
        else:
            self.p[py] = px
            self.rank[px] += 1
        return 1

    def same(self, x, y):
        px = self.root(x); py = self.root(y)
        return px == py

V,E = list(map(int,input().split()))
STW = sorted([list(map(int,input().split())) for _ in range(E)],key=lambda x: x[2])

union_find = UnionFind(V+1)
ans = 0
for s,t,w in STW:
    if not union_find.same(s,t):
        ans += w
        union_find.unite(s,t)

print(ans)