Introduction to Apache Flink: Stream Processing for Real Time and Beyond

Ellen Friedman, Kostas Tzoumas

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商品描述

There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well—until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You’ll also learn how Flink has the ability to handle both stream and batch data processing with one technology.

  • Learn the consequences of not doing streaming well—in retail and marketing, IoT, telecom, and banking and finance
  • Explore how to design data architecture to gain the best advantage from stream processing
  • Get an overview of Flink’s capabilities and features, along with examples of how companies use Flink, including in production
  • Take a technical dive into Flink, and learn how it handles time and stateful computation
  • Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance

商品描述(中文翻譯)

越來越多人對於學習如何分析大規模系統中的流式數據(例如網路流量、金融交易、機器日誌、工業感應器等)表現出興趣。然而,在大規模數據流分析方面一直以來都很難做得好,直到現在。這本實用書籍深入介紹了 Apache Flink,這是一個高度創新的開源流處理器,具有出人意料的多樣能力。

作者 Ellen Friedman 和 Kostas Tzoumas 向技術和非技術讀者展示了 Flink 是如何設計來克服其他流處理方法所面臨的重大折衷,並提升效能。您還將了解到 Flink 具有同時處理流式和批次數據的能力,並使用同一項技術。

本書內容包括:
- 瞭解不善處理流式數據的後果,包括在零售和營銷、物聯網、電信以及銀行和金融領域的影響。
- 探索如何設計數據架構以充分利用流處理的優勢。
- 概述 Flink 的能力和特點,並提供公司在生產環境中使用 Flink 的實際案例。
- 深入研究 Flink,了解它如何處理時間和有狀態的計算。
- 檢視 Flink 如何在不影響性能的情況下處理流式(無界)和批次(有界)數據。

這本書對於想要深入了解 Apache Flink 的人來說是一個很好的參考資料,無論是技術人員還是非技術人員都能從中受益。