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Pinduoduo·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Short SQL/analytics question for a Data Engineer role at Pinduoduo. Just the one problem, nothing behavioral, felt more like a screening exercise than a full round.

Questions Asked (1)

Q1

Given a table of user login records, write a query to find the longest consecutive daily login streak for each user.

Algorithms & Data StructuresData Modeling
Author's notes

Classic gaps-and-islands problem.

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AI HintsAI Generated

Suggested Approach

Use a window function to group consecutive login dates by subtracting a row number from the date, then count the size of each group and take the maximum per user. This approach efficiently handles gaps and works in most SQL dialects.

Pro tip: Mention that you would first clarify whether the table has one row per user per day (deduplicated) and whether the streak should be based on calendar days or 24-hour periods, as this affects the solution.

1. Understand the data and requirements

Confirm the table schema, ensure one row per user per login day, and clarify if consecutive means calendar days or exact 24-hour intervals.

2. Identify consecutive sequences

Use ROW_NUMBER() partitioned by user and ordered by login date, then subtract the row number from the date to create a group identifier for consecutive days.

3. Group and count streaks

Group by user and the group identifier, count the number of rows in each group to get streak lengths.

4. Find the longest streak per user

Use MAX() on the streak lengths grouped by user, or use ROW_NUMBER() to pick the longest streak if you need the actual dates.

5. Handle edge cases and optimize

Consider users with no consecutive days, ties for longest streak, and performance implications for large datasets.

Key Points to Mention

  • Use of window functions like ROW_NUMBER() to identify consecutive sequences.
  • The technique of subtracting row number from date to create a constant group key for consecutive days.
  • Handling duplicates by ensuring one row per user per day (e.g., using DISTINCT or GROUP BY).
  • Considering time zones and date truncation if timestamps are involved.
  • Performance considerations: indexing on (user_id, login_date) and avoiding unnecessary sorting.
  • Edge cases: users with only one login, non-consecutive logins, and ties for longest streak.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.