Topic
Stream Processing
Learn Stream Processing as a connected topic across chapters, concepts, simulations, and interview reasoning.
10 Concepts4 Articles1h 9m
Overview
Learn Stream Processing as a connected topic across chapters, concepts, simulations, and interview reasoning.
How this topic helps
Data Engineering
Architecture
Big Data
System Design
Learning Path in this Topic
Series that contain articles from Stream Processing. Select a path to filter the article list.
Articles
4 matched articles
Article 1Stream Processing Pipeline Pattern: Stateful Real-Time Data ProductsTLDR: Stream pipelines succeed when event-time semantics, state management, and replay strategy are designed together — and Kafka Streams lets you build all three directly inside your Spring Boot serv15 min
Article 2Kappa Architecture: Streaming-First Data PipelinesTLDR: Kappa architecture replaces Lambda's batch + speed dual codebases with a single streaming pipeline backed by a replayable Kafka log. Reprocessing becomes replaying from offset 0. One codebase, n21 min
Article 3Apache Spark for Data Engineers: RDDs, DataFrames, and Structured StreamingTLDR: Apache Spark distributes Python DataFrame jobs across a cluster of executors, using lazy evaluation and the Catalyst query optimizer to process terabytes with the same code that works on gigabyt19 minArticle 4Lambda Architecture Pattern: Balancing Batch Accuracy with Streaming FreshnessTLDR: Lambda architecture is justified when replay correctness and sub-minute freshness are both non-negotiable despite dual-path complexity.
TLDR: Lambda architecture is a fit only when you need bo14 min