Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications
暫譯: 使用 Apache Flink 進行串流處理：串流應用程式的基本原理、實作與運行

Fabian Hueske, Vasiliki Kalavri

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

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商品描述

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

商品描述(中文翻譯)

開始使用 Apache Flink，這是一個開源框架，讓您能夠即時處理串流數據——例如用戶互動、感測器數據和機器日誌——隨著數據的到來。通過這本實用指南，您將學會如何使用 Apache Flink 的串流處理 API 來實現、持續運行和維護現實世界的應用程序。

作者 Fabian Hueske，Flink 的創建者之一，以及 Vasia Kalavri，Flink 的圖形處理 API (Gelly) 的核心貢獻者，解釋了並行串流處理的基本概念，並展示了串流分析與傳統批量數據分析的不同之處。軟體工程師、數據工程師和系統管理員將學習 Flink 的 DataStream API 的基礎知識，包括常見 Flink 串流應用程序的結構和組件。

- 使用 Apache Flink 的 DataStream API 解決現實世界的問題
- 設置開發 Flink 串流處理應用程序的環境
- 設計串流應用程序並將定期批量工作負載遷移到持續串流工作負載
- 了解處理記錄組的窗口操作
- 將數據流引入 DataStream 應用程序並將結果流發送到不同的存儲系統
- 實現串流處理應用程序中常見的有狀態和自定義運算子
- 操作、維護和更新持續運行的 Flink 串流應用程序
- 探索多種部署選項，包括高可用性安裝的設置

作者簡介

Fabian Hueske is a committer to and PMC member of the Apache Flink project and has been contributing to Flink since its earliest days. Fabian is cofounder, software engineer, and community evangelist at data Artisans (now Ververica), a Berlin-based startup that fosters Flink and its community. He holds a PhD in computer science from TU Berlin.

Vasiliki (Vasia) Kalavri is a postdoctoral fellow in the Systems Group at ETH Zurich, where she uses Apache Flink extensively for streaming systems research and teaching. Vasia is a PMC member of the Apache Flink project. An early contributor to Flink, she has worked on its graph processing library, Gelly, and on early versions of the Table API and streaming SQL.

作者簡介(中文翻譯)

Fabian Hueske 是 Apache Flink 專案的委員和 PMC 成員，自專案初期以來一直在貢獻 Flink。Fabian 是 data Artisans（現為 Ververica）的共同創辦人、軟體工程師和社群推廣者，這是一家位於柏林的初創公司，致力於推動 Flink 及其社群。他擁有德國柏林工業大學的計算機科學博士學位。

Vasiliki (Vasia) Kalavri 是蘇黎世聯邦理工學院系統組的博士後研究員，她在流式系統研究和教學中廣泛使用 Apache Flink。Vasia 是 Apache Flink 專案的 PMC 成員。作為 Flink 的早期貢獻者，她曾參與其圖形處理庫 Gelly 的開發，以及早期版本的 Table API 和流式 SQL。

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