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Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026Remote

Summary

Databricks SWE interview with a data structures design question that had a sneaky concurrency-adjacent twist. Not the hardest problem on paper, but the snapshot semantics tripped me up more than I expected.

Questions Asked (1)

Q1

Design and implement a set data structure that supports creating snapshot iterators. The set should support add, remove, and contains operations, and an iterator() method that returns an iterator over the state of the set at the moment it was called. Subsequent mutations to the set must not affect already-created iterators.

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

My first instinct was just to copy the underlying set into a list when iterator() is called, which is correct but I second-guessed myself for a solid two minutes thinking there was some clever persistent data structure angle they wanted.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a versioned data structure (e.g., persistent set or copy-on-write) that allows O(1) snapshot creation. Discuss trade-offs between time/space complexity and concurrency, and outline how to implement add, remove, contains, and iterator with snapshot isolation.

Pro tip: Mention that snapshots can be implemented via versioning or persistent data structures, and highlight that Databricks often values scalable, concurrent solutions—so discuss thread-safety and memory overhead.

1. Clarify Requirements

Ask about expected operations, concurrency needs, memory constraints, and whether snapshots must be immutable or can share structure.

2. Choose Data Structure

Select a versioned or persistent data structure (e.g., hash array mapped trie, copy-on-write, or versioned hash map) that supports efficient snapshots.

3. Design Operations

Define how add, remove, and contains work with versioning, ensuring mutations create new versions without affecting existing iterators.

4. Implement Iterator

Implement iterator() to capture the current version and iterate over that snapshot, ignoring later changes.

5. Analyze Trade-offs

Discuss time/space complexity, concurrency, and alternatives (e.g., locking vs. lock-free), and justify your choice.

Key Points to Mention

  • Versioning or persistent data structures (e.g., HAMT, copy-on-write) for snapshots
  • Time complexity: O(1) snapshot creation, O(log n) or O(1) average for operations
  • Space complexity: structural sharing to minimize memory overhead
  • Thread-safety and concurrency considerations (e.g., atomic version updates)
  • Iterator semantics: snapshot isolation and immutability
  • Trade-offs between different approaches (e.g., locking vs. lock-free, memory vs. speed)

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