Название: Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications Автор: Fabian Hueske, Vasiliki Kalavri
Издательство: O’Reilly Media, Inc.
ISBN: 149197429X
Год: 2019
Страниц: 310
Язык: английский
Формат: epub, pdf (conv)
Размер: 14.1 MB
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.
This book will teach you everything you need to know about stream processing with Apache Flink. It consists of 11 chapters that hopefully tell a coherent story. While some chapters are descriptive and aim to introduce high-level design concepts, others are more hands-on and contain many code examples.
While we intended for the book to be read in chapter order when we were writing it, readers familiar with a chapter’s content might want to skip it. Others more interested in writing Flink code right away might want to read the practical chapters first. In the following, we briefly describe the contents of each chapter, so you can directly jump to those chapters that interest you most.
• 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
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