Librería Portfolio

Get started with Apache Flink, the open source framework that powers some of the world's largest stream processing applications. With this practical book, you'll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing.

Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink's DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them.

Learn concepts and challenges of distributed stateful stream processing
Explore Flink's system architecture, including its event-time processing mode and fault-tolerance model
Understand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperators
Read data from and write data to external systems with exactly-once consistency
Deploy and configure Flink clusters
Operate continuously running streaming applications



Table of Contents
Chapter 1 Introduction into Data Stream Processing
Chapter 2 Stream Processing Fundamentals
Chapter 3 The System Architecture of Apache Flink
Chapter 4 Setting up a development environment for Apache Flink
Chapter 5 The DataStream API (v1.2.0)
Chapter 6 Windowed operations and Time
Chapter 7 Reading and writing data streams
Chapter 8 Stateful and Custom Operators
Chapter 9 Setting up Flink for Streaming Applications
Chapter 10 Operating Flink Streaming Applications