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Pinduoduo·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

SQL interview for a data engineering role at Pinduoduo. One question, no written spec, just a verbal description and a blank canvas. Pretty low-key but the schema discussion added some back-and-forth I wasn't expecting.

Questions Asked (1)

Q1

Write a query to find users who have logged in on at least two distinct days.

Data ModelingAlgorithms & Data StructuresProduct Analytics & Metrics
Author's notes

The actual SQL part wasn't bad.

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AI HintsAI Generated

Suggested Approach

Clarify the schema and edge cases, then propose an efficient SQL solution using GROUP BY and HAVING COUNT(DISTINCT date) >= 2. Discuss indexing and alternative approaches like self-join or window functions, and analyze the query's performance.

Pro tip: Mention that using COUNT(DISTINCT date) is the most straightforward and efficient method, but also consider how you would handle large datasets with partitioning or indexing to avoid full table scans.

1. Clarify requirements and schema

Ask about the table structure (e.g., user_id, login_date), data types, and whether 'distinct days' means calendar days or 24-hour periods. Confirm if multiple logins per day are possible.

2. Outline the core SQL logic

Explain that you would group by user_id and filter with HAVING COUNT(DISTINCT login_date) >= 2. Write the query clearly, using aliases and proper formatting.

3. Discuss alternative approaches

Mention other methods like self-join on user_id and date difference, or using window functions (e.g., DENSE_RANK) to identify distinct days, and compare their pros and cons.

4. Address performance and optimization

Talk about indexing on (user_id, login_date) to speed up grouping and distinct counting. Consider partitioning for very large tables and explain how the query scales.

5. Handle edge cases and validate

Discuss handling NULLs, time zones, and users with exactly two logins on the same day. Suggest testing with sample data to ensure correctness.

Key Points to Mention

  • Use of GROUP BY with HAVING COUNT(DISTINCT date) >= 2
  • Indexing strategy on (user_id, login_date) for performance
  • Alternative solutions: self-join, window functions, or subqueries
  • Handling time zones and date truncation if timestamps are used
  • Scalability considerations for large datasets (partitioning, distributed processing)
  • Edge cases: NULL user_ids, duplicate logins, and users with exactly two distinct days

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