Quick Overview

This question evaluates proficiency in SQL time-series and event-stream manipulation, focusing on window-function techniques for sessionization, timestamp arithmetic, and aggregation to produce session-level metrics, targeting Data Manipulation (SQL/Python) competencies relevant to data scientist roles.

Detect sessions and gaps using SQL LEAD

Company: Apple

Role: Data Scientist

Category: Data Manipulation (SQL/Python)

Difficulty: medium

Interview Round: Technical Screen

Write a single ANSI-SQL query that (a) assigns per-user session_ids when the gap between consecutive events exceeds 30 minutes, (b) computes session_start, session_end, event_count, session_length_seconds, and next_session_gap_seconds (time from this session_end to the next session_start for the same user), and (c) uses window functions including LEAD at least once. Schema: - events(user_id INT, ts TIMESTAMP, action VARCHAR) Sample data: +---------+---------------------+---------+ | user_id | ts | action | +---------+---------------------+---------+ | 1 | 2025-08-01 09:00:00 | view | | 1 | 2025-08-01 09:10:00 | click | | 1 | 2025-08-01 10:00:00 | view | | 2 | 2025-08-01 12:00:00 | view | | 2 | 2025-08-01 12:20:00 | click | | 2 | 2025-08-01 12:45:00 | purchase| | 2 | 2025-08-01 14:00:00 | view | +---------+---------------------+---------+ Requirements: - Use LAG to detect new sessions and a running SUM to form session_ids per user. - Use LEAD(ts) to compute next_event_ts and derive next_session_gap_seconds. - Return columns: user_id, session_id, session_start, session_end, event_count, session_length_seconds, next_session_gap_seconds (NULL if no next session).

Overview: This question evaluates proficiency in SQL time-series and event-stream manipulation, focusing on window-function techniques for sessionization, timestamp arithmetic, and aggregation to produce session-level metrics, targeting Data Manipulation (SQL/Python) competencies relevant to data scientist roles.

Using PostgreSQL, assign each user's events to sessions. A new session begins only when the gap from the preceding event is greater than 30 minutes; a gap of exactly 30 minutes stays in the same session. Return user_id, a 1-based session_id, session_start, session_end, event_count, session_length_seconds, and next_session_gap_seconds (the seconds from this session's final event to the next session's first event, or NULL for the user's last session). Use LAG to identify session boundaries, a running SUM to form session IDs, and LEAD(ts) to identify the next event. Order by user_id and session_id.

Tables

events(user_id INTEGER, ts TIMESTAMP, action TEXT)

Hints

  1. Compute previous and next timestamps at event grain before assigning sessions.
  2. A strict gap greater than 30 minutes starts a new session; exactly 30 minutes does not.

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