What is real-time feature computation with stateful stream processing?

Stateful stream processing computes features continuously while maintaining historical context.

Stateful stream processing systems like Flink or Spark Streaming maintain intermediate state across events to compute rolling aggregates, session-based features, and temporal patterns. This enables real-time ML inference with up-to-date features. Challenges include state consistency, fault recovery, and checkpointing.