95Build an in-memory key-value database, then extend it across stages: TTL, transactions, snapshots.▼hardAnthropicOpenAIGoogle1 replies◆ premiumThe classic multi-round build screen: a plain key-value store that gains new requirements at each stage (TTL, transactions, scans). The signal is not stage 1, it is whether your code takes on stage 4 without a rewrite. Here is how to design for it.Open full answer →
97Implement an in-memory key-value store with transactions: begin, commit, rollback, and nesting.▼hardAnthropicOpenAIGoogle2 replies◆ premiumA classic build screen: a key-value store whose writes inside a transaction can be committed or discarded, with transactions that nest. The trap is mutating the base store directly. Here is the overlay-stack design that keeps rollback O(1).Open full answer →
49How does a Kafka stream-processing pipeline achieve exactly-once semantics end to end?▼expertDatabricksSnowflakeGoogle1 replies◆ premiumAt-least-once creates duplicates and at-most-once drops data; everyone asks for exactly-once yet few can explain how Kafka provides it. The signal is idempotent producers, transactional read-process-write, and the read-committed isolation that binds them together.Open full answer →