Structured Streaming with Spark — Big Data Processing & Lakehouse Eng…
Treating a stream as an unbounded table
Steps in Structured Streaming with Spark
- Structured Streaming Fundamentals — beginner · Spark's model for treating a stream as an unbounded table
- Micro-Batch vs Continuous Processing — beginner · Spark's two processing modes and their trade-offs
- Windowing and Watermarks in Streaming — beginner · Handling time-based aggregation over an unbounded stream
- Stateful Stream Processing — beginner · Maintaining and updating state across a long-running stream
- Exactly-Once Semantics in Structured Streaming — beginner · How Spark provides strong processing guarantees for streams
- Combining Batch and Streaming (Lambda/Kappa Architecture) — beginner · Architectural patterns for unifying batch and real-time processing
Part of
- Big Data Processing & Lakehouse Engineering roadmap — the full learning path