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Stream Processing with Apache Flink (Fundamentals, Implementation, and Operation of Streaming Applications)

List Price: $79.99
SKU:
9781491974292
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  • Product Details

    Author:
    Fabian Hueske, Vasiliki Kalavri
    Format:
    Paperback
    Pages:
    308
    Publisher:
    O'Reilly Media (May 21, 2019)
    Language:
    English
    ISBN-13:
    9781491974292
    ISBN-10:
    149197429X
    Dimensions:
    7" x 9.19"
    Case Pack:
    13
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20251022163324-20251022.xml
    Folder:
    TWO RIVERS
    List Price:
    $79.99
    As low as:
    $68.79
    Publisher Identifier:
    P-PER
    Discount Code:
    C
    Country of Origin:
    United States
    Pub Discount:
    60
    Weight:
    16oz
    Imprint:
    O'Reilly Media
  • Overview

    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 creators, and Vasia Kalavri, a core contributor to Flink’s graph processing API (Gelly), explains 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