The join between calls and call_participants tripped me up at first because you have to be careful not to count the initiator as one of their own callees.
Start by clarifying the schema and definitions (e.g., what constitutes a completed video call, how to identify initiators, and how to exclude test accounts). Then build a query that filters calls by the 7-day window, completion status, and video type, joins to participants to count distinct callees per initiator, and finally filters initiators with more than 3 distinct callees. Use CTEs for readability and to avoid nested subqueries.
Pro tip: Mention that you would validate the results by checking edge cases like calls with the initiator also listed as a participant, and ensure the time window is inclusive/exclusive as specified. Also, discuss performance considerations such as indexing on call date and participant user IDs.
Confirm the meaning of 'completed video calls', how to identify initiators (e.g., initiator_id in calls table), and how test accounts are flagged (e.g., is_test_account boolean). Also confirm the exact 7-day window (inclusive dates).
Select calls within the specified date range, with status = 'completed' and call_type = 'video'. Exclude calls initiated by test accounts.
Join the filtered calls to the call_participants table to get all callees for each call. Exclude the initiator from the callee list to avoid self-counting.
Group by initiator_id and count distinct callee_ids. Filter to only those with COUNT(DISTINCT callee_id) > 3.
Count the number of distinct initiator_ids that satisfy the condition. This is the final answer.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the definitions of DAU, French users, and video call participation, then write a SQL query that computes the numerator (distinct French DAUs on a video call) and denominator (all French DAUs) for a given day, and finally calculate the percentage. For the version handling multiple joins, use DISTINCT or a subquery to deduplicate users who joined the same call multiple times.
Pro tip: Always clarify ambiguous terms like 'French' (based on user country or IP?) and 'video call' (any participation or only initiations?) before writing SQL, as these definitions significantly impact the metric.
Define what constitutes a French DAU (e.g., users with country='France' active on the given day) and what counts as being on a video call (e.g., any call event). Confirm the date format and time zone.
Assume tables like user_activity (user_id, date, country) for DAU and call_events (user_id, call_id, date, event_type) for video calls. Ensure you know how to join them.
Write subqueries: denominator = COUNT(DISTINCT user_id) from user_activity where date = given_date and country = 'France'; numerator = COUNT(DISTINCT user_id) from call_events where date = given_date and user_id in French DAUs.
Combine numerator and denominator in a single query, computing percentage as (numerator * 100.0 / denominator). Handle division by zero if no DAUs.
For the version with multiple joins, ensure the numerator counts distinct users who joined any call at least once, using DISTINCT or a subquery with GROUP BY user_id.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.