stream-processing

Design a real-time data stream processing system by selecting appropriate stream processing frameworks, state backends, and fault-tolerance mechanisms to handle continuous data ingestion and analysis efficiently.

Windowing and watermarking in stream processing are techniques for managing time-based data segments and event-time processing, allowing systems to handle continuous data streams and calculate metrics over rolling windows.

Handle late data and event-time in distributed streaming architectures by implementing watermarking strategies and robust state management to ensure accurate processing of continuous data streams.

Process live IoT sensor data over rolling windows by designing a real-time stream processing system that calculates average readings, such as temperature over 5-minute windows, to detect anomalies continuously.

Manage state and fault tolerance in continuous data streams by selecting appropriate state backends and fault-tolerance mechanisms tailored for distributed streaming architectures during the system design phase.