Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, 2/e
暫譯: 設計數據密集型應用程式:可靠、可擴展和可維護系統的核心理念,第二版
Kleppmann, Martin, Riccomini, Chris
- 出版商: O'Reilly
- 出版日期: 2026-03-24
- 售價: $2,450
- 貴賓價: 9.5 折 $2,327
- 語言: 英文
- 頁數: 670
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1098119061
- ISBN-13: 9781098119065
-
相關分類:
大數據 Big-data
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商品描述
Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of tools and analytical systems, including relational databases, NoSQL datastores, plus data warehouses and data lakes. What are the right choices for your application? How do you make sense of all these buzzwords?
In this second edition, authors Martin Kleppmann and Chris Riccomini build on the foundation laid in the acclaimed first edition, integrating new technologies and emerging trends. You'll be guided through the maze of decisions and trade-offs involved in building a modern data system, from choosing the right tools like Spark and Flink to understanding the intricacies of data laws like the GDPR.
- Peer under the hood of the systems you already use, and learn to use them more effectively
- Make informed decisions by identifying the strengths and weaknesses of different tools
- Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
- Understand the distributed systems research upon which modern databases are built
- Peek behind the scenes of major online services, and learn from their architectures
商品描述(中文翻譯)
資料是當今系統設計中許多挑戰的核心。需要解決的困難問題包括可擴展性、一致性、可靠性、效率和可維護性。此外,還有各種各樣的工具和分析系統,包括關聯式資料庫、NoSQL 資料存儲、數據倉庫和數據湖。對於您的應用程式,哪些選擇是正確的?您如何理解這些流行術語?
在這第二版中,作者 Martin Kleppmann 和 Chris Riccomini 在備受讚譽的第一版基礎上進行了擴展,整合了新技術和新興趨勢。您將在構建現代數據系統的決策和權衡迷宮中獲得指導,從選擇合適的工具如 Spark 和 Flink,到理解 GDPR 等數據法規的複雜性。
- 深入了解您已經使用的系統,學會更有效地使用它們
- 通過識別不同工具的優勢和劣勢來做出明智的決策
- 瀏覽有關一致性、可擴展性、容錯性和複雜性的權衡
- 理解現代資料庫所建立的分散式系統研究
- 窺探主要在線服務的幕後,並從它們的架構中學習