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
from heapq import heappush, heappop, heapify

V, E = map(int, sys.stdin.readline().strip().split())

graph = [[] for _ in range(V)]
for _ in range(E):
	s, t, w = map(int, sys.stdin.readline().strip().split())
	graph[s].append((w, t))
	graph[t].append((w, s))
	
used = set()
q = []
for i in range(V):
    if len(graph[i]):
        for w, t in graph[i]:
            q.append((w, t))
        used.add(i)
        break
heapify(q)

ans = 0
while q:
    w, s = heappop(q)
    if s in used:
        continue
    used.add(s)
    ans += w
    for w, t in graph[s]:
        if t in used:
            continue
        heappush(q, (w, t))

print(ans)