Time Complexity: O(n log n), where n is the number of elements in the array. This is due to the sorting step, which is the most time-consuming operation in this approach.

Space Complexity: O(1), as we are using only a constant amount of extra space.

Optimal Approach

Algorithm

We will use two variables: cnt to store the length of the current sequence and longest to store the maximum length found.
First, place all the array elements into a set data structure to allow efficient lookups for consecutive numbers.
For each element x that can start a sequence (i.e., x - 1 does not exist in the set), we follow these steps:

Initialize cnt to 1, indicating the starting element of a new sequence.
Use the set to search for consecutive elements such as x + 1, x + 2, and so on, to determine the maximum possible length of the current sequence. Update cnt accordingly.

Compare cnt with longest and update longest to hold the maximum value: longest = max(longest, cnt).
Finally, longest will contain the length of the longest consecutive sequence found in the array.