Introduction to Apache Flink: Stream Processing for Real Time and Beyond
暫譯: Apache Flink 入門:實時流處理及其應用

Ellen Friedman, Kostas Tzoumas

  • 出版商: O'Reilly
  • 出版日期: 2016-11-29
  • 定價: $825
  • 售價: 8.0$660
  • 語言: 英文
  • 頁數: 110
  • 裝訂: Paperback
  • ISBN: 1491976586
  • ISBN-13: 9781491976586
  • 相關分類: 大數據 Big-data雲端運算
  • 立即出貨 (庫存 < 3)

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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)

隨著對於如何分析大型系統中的串流數據(如網路流量、金融交易、機器日誌、工業感測器等)的興趣日益增加,進行大規模的數據串流分析一直以來都很困難,直到現在。本書提供了對 Apache Flink 的深入介紹,這是一個高度創新的開源串流處理器,具備驚人的功能範圍。

作者 Ellen Friedman 和 Kostas Tzoumas 向技術和非技術讀者展示了 Flink 如何設計以克服其他串流處理方法所面臨的重大權衡,這些權衡限制了其有效性。您還將學習 Flink 如何能夠使用一種技術同時處理串流和批次數據。

- 了解在零售和行銷、物聯網、電信以及銀行和金融領域中,未能有效進行串流處理的後果
- 探索如何設計數據架構,以從串流處理中獲得最佳優勢
- 獲得 Flink 的能力和特性的概述,以及公司如何使用 Flink 的範例,包括在生產環境中的應用
- 深入技術層面了解 Flink,學習它如何處理時間和有狀態計算
- 檢視 Flink 如何在不犧牲性能的情況下處理串流(無界)和批次(有界)數據