eBook Excerpt

Stream Processing with Apache Flink Scala

By Toby Weston, Software Engineer, data Artisans

By Toby Weston, Software Engineer, data Artisans and Vasiliki Kalavri, PhD candidate, Fellow of the Erasmus Mundus Joint Doctorate in Distributed Computing

Note: this preview download contains chapters 2 and 3 of Stream Processing with Apache Flink

Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you’ll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications.

Authors Fabian Hueske, one of Flink’s initial authors, and post-doctoral rearcher Vasia Kalavri explain the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink’s DataStream API, including the structure and components of a common Flink streaming application.

  • Solve real-world problems with Apache Flink's DataStream API
  • Set up an environment for developing stream processing applications for Flink
  • Design streaming applications and migrate periodic batch workloads to continuous streaming workloads
  • Learn about windowed operations that process groups of records
  • Ingest data streams into a DataStream application and emit a result stream into different storage systems
  • Implement stateful and custom operators common in stream processing applications
  • Operate, maintain, and update continuously running Flink streaming applications
  • Explore several deployment options, including the setup of highly available installations

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About Author

Toby Weston, Software Engineer, data Artisans

About Authors

Toby Weston, Software Engineer, data Artisans

Vasiliki Kalavri, PhD candidate, Fellow of the Erasmus Mundus Joint Doctorate in Distributed Computing

Vasliki (Vasia) Kalavri is a PhD candidate and a fellow of the Erasmus Mundus Joint Doctorate in Distributed Computing. During her fellowship, she has been conducting research in two partner universities: KTH Royal Institute of Technology, Stockholm, and Université Catholique de Louvain, Belgium. Vasia's research focuses on distributed data ​processing, systems optimization, and large­-scale graph analysis. She is a PMC member of Apache Flink and a core developer of its graph processing API, Gelly. Vasia has a MSc in Distributed Computing from KTH, Stockholm and UPC, Barcelona, and a diploma in Electrical and Computer Engineering from NTUA, Athens. During her PhD studies, she has been a visiting researcher at the Technical University of Berlin and she has interned at Telefonica Research and data Artisans.

About Lightbend

Lightbend (Twitter: @Lightbend) is dedicated to helping developers build Reactive applications on the JVM. With the Lightbend Reactive Platform, developers can create message-driven applications that scale on multicore and cloud computing architectures by using projects like Lagom, Play Framework, Akka, Scala, Java, and Apache Spark. To help our customers succeed, Lightbend partners with technology pioneers such as Databricks, IBM, and Mesosphere.