Problem Description

You are provided with two analytics tables containing user and listening event data:

• users: Stores user metadata.
  • user_id (Primary Key)
  • country
  • signup_date
• listening_events: Records individual listening sessions.
  • event_id (Primary Key for a unique event, but can appear multiple times due to retries)
  • user_id (Foreign Key to users)
  • played_at (Timestamp of when the event occurred)
  • minutes_played (Duration of the listening event)

Note that the listening_events table may contain duplicate rows with the same event_id due to data pipeline retry mechanisms.

Task 1: SQL Query

Write a SQL query that returns, for each country, the top 3 users based on their total minutes_played within the last 30 days. The query result should include the country, user_id, total_minutes, and the user's rank within their respective country.

Task 2: Discussion Points

After presenting your SQL query, discuss the following architectural and optimization considerations:

1. Deduplication Strategy: How would you deduplicate events before they are aggregated, especially considering the potential for duplicate event_ids?
2. Query Optimization: How would you optimize the SQL query if the listening_events table is extremely large (e.g., petabytes of data)?
3. Scaling Data Storage: Explain when partitioning versus sharding would be beneficial for managing and querying such a large dataset.