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Indexes on user_id and purchase_date significantly improve performance. They help the database engine efficiently group and sort purchases per user when performing joins or window function operations.
Yes, similar SQL interview questions are common in FAANG and other tech company interviews. They test your understanding of joins, window functions, date comparisons, and how to analyze user activity over time.
A common optimal approach is to use SQL window functions such as LAG() to compare each purchase with the previous purchase for the same user. This avoids expensive pairwise comparisons and keeps the logic clean and efficient after sorting by user and date.
Developers often use either a self-join or window functions. A self-join compares purchases from the same user directly, while window functions like LAG() allow you to compute date differences between consecutive purchases more efficiently.