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This approach leverages SQL aggregate functions to determine the first login date for each player. We use the MIN function to get the earliest event_date for each player_id. This is accomplished by grouping the results based on the player_id field.
Time complexity: O(n) due to a single pass through the Activity table.
Space complexity: O(k), where k is the number of unique player_ids.
1SELECT player_id, MIN(event_date) AS first_login FROM Activity GROUP BY player_id;The SQL query selects the smallest event_date for each player_id, yielding the first login date. The GROUP BY clause groups the data based on player_id, enabling the MIN function to operate within each group independently.
This approach involves loading the data into a data structure that optimizes lookup times, such as a dictionary or a map, and then iterating over the list to find the earliest event_date for each player_id. This functionally mimics the behavior of the SQL approach but executed in a programming environment rather than within a database.
Time complexity: O(n), with a single traversal of the records list.
Space complexity: O(k), where k is the number of unique player_ids.
1import java.util.*;
2
3This Java function uses a List of integer arrays to represent the Activity records, with each array holding the respective columns. A HashMap is used to track the smallest event_date for each player_id. As the records are iterated through, the event_date either initializes the value or filters through min aggregation to track the earliest date.