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
import collections
import heapq
import math

Edge = collections.namedtuple('Edge', ['s', 't', 'cost'])
    
V, E = map(int, sys.stdin.readline().split())
edges = collections.defaultdict(list)
for line in sys.stdin:
    e = Edge(*map(int, line.split()))
    edges[e.s].append(e)
    edges[e.t].append(Edge(e.t, e.s, e.cost))

heap = [(e.cost, e) for e in edges[0]]
heapq.heapify(heap)
nodes = {0}
min_cost = 0
while heap:
    _, edge = heapq.heappop(heap)
    if edge.t not in nodes:
        nodes.add(edge.t)
        for e in edges[edge.t]:
            heapq.heappush(heap, (e.cost, e))
        min_cost += edge.cost
print(min_cost)