Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing

Tyler Akidau, Slava Chernyak, Reuven Lax

  • 出版商: O'Reilly
  • 出版日期: 2018-08-28
  • 定價: $2,800
  • 售價: 9.0$2,520
  • 語言: 英文
  • 頁數: 352
  • 裝訂: Paperback
  • ISBN: 1491983876
  • ISBN-13: 9781491983874
  • 相關分類: 分散式架構
  • 立即出貨 (庫存 < 3)

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商品描述

Streaming data is a big deal in big data these days, and for good reason. Businesses crave ever more timely data, and streaming is a good way to achieve lower latency. Plus, streaming is a much easier way to tame the massive, unbounded data sets that are increasingly common today.

Expanded from co-author Tyler Akidau’s popular series of blog posts "Streaming 101" and "Streaming 102", this practical book shows data engineers, data scientists, and developers how to work with streaming or event-time data in a conceptual and platform-agnostic way. You’ll go from "101"-level understanding of stream processing to a nuanced grasp of the what, where, when, and how of processing real-time data streams.

Dive deep into topics including watermarks and windowing, as well as state and timers in the context of stream processing. Although the book uses Apache Beam code snippets to make examples concrete, it presents a general and broad explanation of streaming that's not tied to a specific framework.

商品描述(中文翻譯)

流式數據在大數據領域中變得非常重要,並且有很好的原因。企業渴望更及時的數據,而流式數據是實現低延遲的好方法。此外,流式數據是一種更容易應對當今越來越常見的大型、無邊界數據集的方式。

本實用書籍是根據合著者Tyler Akidau的熱門博客系列文章《流式數據101》和《流式數據102》擴展而來,向數據工程師、數據科學家和開發人員展示了如何以概念性和平台無關的方式處理流式或事件時間數據。您將從對流式處理的「101」級別理解,進一步深入了解處理實時數據流的「什麼、在哪裡、何時以及如何」。

深入探討包括水印和窗口化在內的主題,以及在流式處理上下文中的狀態和計時器。儘管本書使用Apache Beam代碼片段來具體說明示例,但它提供了一個通用且廣泛的流式解釋,不依賴於特定的框架。