The getRandom part is where I got tripped up.
Start by clarifying requirements and constraints, then propose a sharded architecture where each shard maintains a local multiset and a consistent hashing ring routes requests. Explain how to handle rebalancing with minimal data movement and how getRandom aggregates across shards to ensure global uniformity.
Pro tip: Emphasize the trade-offs between consistency and availability, and how you would handle failures and hot shards. Mention that you'd use a coordinator or a gossip protocol to maintain shard metadata and ensure getRandom is efficient.
Ask about scale (number of elements, QPS), consistency needs, latency requirements, and failure tolerance. Confirm that getRandom must be uniformly random over all elements.
Propose partitioning elements across shards using consistent hashing or a range-based scheme. Describe how a request router (e.g., a client library or a proxy) directs insert/remove/getRandom to the correct shard(s).
Explain how to add/remove nodes: use consistent hashing to minimize data movement, or use virtual nodes for better balance. Describe the rebalancing process: migrating data, updating routing metadata, and ensuring operations continue during migration.
Detail how to return a globally random element: either (a) pick a random shard weighted by its size, then pick a random element from that shard, or (b) have each shard return a random element and then pick one uniformly from those. Discuss maintaining accurate shard sizes.
Discuss how to keep shard sizes consistent (e.g., using a centralized counter or gossip), handle node failures (replication, retries), and ensure getRandom remains correct under concurrent updates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.