DoorDash·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

DoorDash software engineering interview with a system design coding problem around consistent hashing. Pretty implementation-heavy for what felt like a technical phone screen, and the complexity requirements made it clear they wanted more than just a working solution.

Questions Asked (1)

Implement a ConsistentHashRing class that distributes keys across servers using a hash ring with virtual nodes. The class needs add_server, remove_server, and get_server methods, with get_server wrapping around the ring if no node is found at or after the hashed key position.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

The virtual node part is where most people trip up and I was no exception.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then describe the data structures (sorted list of hashes and a map from hash to server) and the core algorithms for add, remove, and get. Walk through the wrap-around logic and discuss trade-offs like virtual node count and hash function choice, emphasizing how this achieves load balancing and minimal disruption.

Pro tip: Mention that virtual nodes are key to even distribution and that using a binary search on a sorted list gives O(log N) lookup; also note that consistent hashing minimizes key remapping when servers change, which is crucial for caching and sharding systems.

1. Clarify requirements and assumptions

Ask about expected scale, hash function, virtual node count, and whether thread safety is needed. Confirm that get_server should wrap around and that keys are strings.

2. Design data structures

Use a sorted list (or balanced BST) of virtual node hashes and a hash map from hash to server identifier. Explain that the sorted list enables efficient binary search for the first node >= key hash.

3. Implement add_server and remove_server

For add_server, generate virtual nodes, compute their hashes, insert into the sorted list and map. For remove_server, remove all its virtual nodes from both structures.

4. Implement get_server with wrap-around

Hash the key, binary search for the first virtual node hash >= key hash. If none found, wrap to the first node. Return the server associated with that hash.

5. Discuss trade-offs and optimizations

Talk about virtual node count (e.g., 100-200 per server) for balance, hash function choice (e.g., MD5, SHA-1, or MurmurHash), and potential improvements like replication or bounded loads.

Key Points to Mention

Virtual nodes improve load distribution and allow weighted servers by varying replica count.
Binary search on a sorted list of hashes gives O(log N) lookup, where N is total virtual nodes.
Wrap-around ensures that keys hashing beyond the last node are assigned to the first node.
Consistent hashing minimizes remapping when servers are added or removed, unlike modulo hashing.
Thread safety can be achieved with read-write locks if concurrent access is expected.
Hash collisions are rare but can be handled by chaining or using a map from hash to list of servers.

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