Calculate Average Session Length and Compare App Performance

Q: How do I practice SQL interview questions?

PracHub provides an interactive SQL console where you can write and test queries against real database schemas. Get instant feedback and compare your solution with the expected output.

Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Onsite rounds at Meta.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Meta during technical interviews.

Question

user_sessions

+---------+------------+------------+---------------------+---------------------+
| user_id | session_id | app        | session_start       | session_end         |
+---------+------------+------------+---------------------+---------------------+
| 101     | s1         | Instagram  | 2023-07-10 10:00:00 | 2023-07-10 10:15:00 |
| 101     | s2         | Facebook   | 2023-07-10 10:20:00 | 2023-07-10 10:35:00 |
| 102     | s3         | Messenger  | 2023-07-10 11:00:00 | 2023-07-10 11:05:00 |
| 103     | s4         | Instagram  | 2023-07-10 12:00:00 | 2023-07-10 12:45:00 |
+---------+------------+------------+---------------------+---------------------+

##### Scenario

Analyzing cross-app user session logs to measure engagement and switching behavior.

##### Question

For yesterday, calculate the average session length (session_end − session_start) for each app. Propose and compute a metric to compare daily app performance, explaining why your chosen denominator makes sense. Compute each app's daily bounce rate: users who switch to another app and then return to the first app within the same day.

##### Hints

Use DATE filters, window/aggregate functions, define metrics clearly.

PracHub · Accepted Answer

This question evaluates sessionization, time-based aggregation, and metric design competencies using SQL and Python, testing a data scientist's ability to process timestamped logs, compute engagement metrics, and interpret user-switching behavior within the Data Manipulation domain.

Quick Overview

Quick Overview