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Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026

Summary

Interviewed for a software engineering role at OpenAI and got a problem that looked deceptively simple on the surface. Build a tiny in-memory database, one table, strings only. Spent most of the time on the SELECT sorting logic which has more edge cases than you'd expect.

Questions Asked (1)

Q1

Implement a simple in-memory database supporting SET, GET, and SELECT commands on a single table where all values are strings. SELECT must filter rows by a column value and sort results by another column lexicographically, with tie-breaking by row key.

Algorithms & Data StructuresData ModelingSystem Design
Author's notes

The SET and GET parts took maybe five minutes.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, then propose a data model using a hash map for rows and secondary indexes for efficient filtering and sorting. Outline the core operations (SET, GET, SELECT) and discuss trade-offs between simplicity and performance, mentioning how to handle sorting and tie-breaking.

Pro tip: Demonstrate awareness of real-world database internals by discussing indexing strategies and the cost of maintaining indexes on writes, and suggest a simple but extensible design that could evolve to support more complex queries.

1. Clarify Requirements

Ask questions to confirm the scope: single table, string values, exact match filtering, lexicographic sorting, and tie-breaking by row key. Clarify expected operations and any performance constraints.

2. Design Data Model

Propose storing rows in a hash map keyed by row key, with each row as a map of column names to string values. Consider secondary indexes (e.g., hash maps or sorted structures) for columns frequently used in filters or sorts.

3. Implement Core Operations

Define SET (insert or update a row), GET (retrieve a row by key), and SELECT (filter by column value, then sort by another column with tie-breaking by row key). Discuss how indexes can speed up these operations.

4. Handle Sorting and Tie-Breaking

Explain that SELECT results should be sorted lexicographically by the specified column, and when values are equal, by row key. Mention using a comparator that first compares the sort column, then the row key.

5. Discuss Trade-offs and Extensions

Talk about time/space complexity, when to use indexes, and how the design could be extended to support more columns, range queries, or persistence. Mention potential concurrency considerations if needed.

Key Points to Mention

  • Use a hash map for O(1) row lookups by key.
  • Consider secondary indexes on columns to speed up filtering and sorting.
  • Implement SELECT by scanning or using indexes, then sorting with a custom comparator.
  • Ensure tie-breaking by row key is handled in the comparator.
  • Discuss time and space complexity of operations and index maintenance.
  • Mention potential extensions like range queries, additional data types, or persistence.

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