95Build an in-memory key-value database, then extend it across stages: TTL, transactions, snapshots.▼hardAnthropicOpenAIGoogle1 replies◆ premiumThe canonical multi-round build screen: a simple key-value store that grows new requirements every stage (TTL, transactions, scans). The signal is not stage 1, it is whether your code absorbs 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 where writes inside a transaction can be committed or thrown away, and transactions nest. The trap is mutating the base store directly. Here is the overlay-stack design that makes 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 duplicates and at-most-once loses data; everyone wants exactly-once and few can explain how Kafka delivers it. The signal is idempotent producers plus transactional read-process-write plus the read-committed isolation that ties them together.Open full answer →