In a social media network of n users, labeled from 0 to n - 1, you are given a list of logs where logs[i]=[timestamp_i, x_i , y_i] represents the moment when x_i and y_i become friends at time timestamp_i.

Friendship is bidirectional, meaning if user a is friends with user b, then user b is also friends with user a. Additionally, user a is considered connected to user b if there is a chain of friendships linking a to b, either directly or through other users.

Return the earliest time when every user in the social media network becomes connected to every other user directly or indirectly. If no such time exists, return -1.

Example 1:

Input: logs = [[1,0,2], [2,2,3], [5,3,4], [7,0,3], [8,1,4]],  n = 5
Output: 8
Explanation:
Initial Groups:
Every person starts as their own group (n = 5): [0], [1], [2], [3], [4].

First Event (timestamp = 1, friendship between 0 and 2):
After 0 and 2 become friends, the groups are: [0,2], [1], [3], [4].

Second Event (timestamp = 2, friendship between 2 and 3):
After 2 and 3 become friends, the groups are: [0,2,3], [1], [4].

Third Event (timestamp = 5, friendship between 3 and 4):
After 3 and 4 become friends, the groups are: [0,2,3,4], [1].

Fourth Event (timestamp = 7, friendship between 0 and 3):
Since 0 and 3 are already in the same group, no changes occur.

Fifth Event (timestamp = 8, friendship between 1 and 4):
After 1 and 4 become friends, everyone is now in one group: [0,1,2,3,4].

Example 2:

Input: logs = [[20230101, 0, 1], [20230103, 2, 3], [20230106, 4, 5], [20230108, 0, 2], [20230205, 1, 4], [20230212, 3, 5], [20230301, 1, 3], [20230315, 0, 5]],
n = 6

Output: 20230205

Initial Groups:
Everyone starts in their own group: [0], [1], [2], [3], [4], [5].

First Event (timestamp = 20230101, friendship between 0 and 1):
After 0 and 1 become friends, the groups are: [0, 1], [2], [3], [4], [5].

Second Event (timestamp = 20230103, friendship between 2 and 3):
After 2 and 3 become friends, the groups are: [0, 1], [2, 3], [4], [5].

Third Event (timestamp = 20230106, friendship between 4 and 5):
After 4 and 5 become friends, the groups are: [0, 1], [2, 3], [4, 5].

Fourth Event (timestamp = 20230108, friendship between 0 and 2):
After 0 and 2 become friends, the groups are: [0, 1, 2, 3], [4, 5].

Fifth Event (timestamp = 20230205, friendship between 1 and 4):
After 1 and 4 become friends, the groups are: [0, 1, 2, 3, 4, 5].

Example 3:

Input: logs = [[1,0,1], [3,2,3]], n = 4

Output: -1

Explanation:
After all friendship logs are processed, users 0 and 1 are connected, and users 2 and 3 are connected. However, these two groups never merge into one connected network, so return -1.

Constraints

2 <= n <= 100
1 <= logs.length <= min(10⁴, n × (n - 1) / 2)
logs[i].length == 3
0 <= timestamp_i <= 10⁹
0 <= x_i < n and 0 <= y_i < n
x_i != y_i
All the values timestamp_i are unique.
All the unordered friendship pair (x_i, y_i) appears at most one time in the input.

86. Earliest Time Everyone Becomes Connected