Design structure for first unique login user

You are given an online stream of user login events. Each event is a user ID (e.g., an integer or string) indicating that this user has just logged in.

You need to design a data structure that supports two operations:

1. login(userId) Record that userId has logged in one more time.

2. firstUser() Return the ID of the user who

• has logged in exactly once so far, and
• among all such users, is the earliest by login time (i.e., the one whose first login happened earliest in the stream), or return a special value (e.g., null or -1) if no such user exists.

Requirements:

• Both login and firstUser must run in O(1) worst-case time per operation.
• You can assume the number of distinct users fits in memory.
• You may choose any reasonable representation for userId (e.g., integer or string), but specify your assumptions.

Example:

Suppose the login stream is:

• login(A) // A has logged in once
• login(B) // B has logged in once; A is still first unique
• login(A) // A now has logged in twice
• login(C) // C has logged in once

Then the sequence of firstUser() calls should return:

• After login(A): firstUser() → A
• After login(B): firstUser() → A (A and B are unique, A is earlier)
• After login(A): firstUser() → B (A is no longer unique)
• After login(C): firstUser() → B (B is still the earliest unique user)

Design the data structure and its operations to meet the time complexity guarantees. You do not need to handle persistence or multi-threading; focus on the core algorithm and data organization.