Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
Peer under the hood of the systems you already use, and learn how to use and operate 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
Martin is a researcher in distributed systems at the University of Cambridge. Previously he was a software engineer and entrepreneur at Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure. In the process he learned a few things the hard way, and he hopes this book will save you from repeating the same mistakes.
Martin is a regular conference speaker, blogger, and open source contributor. He believes that profound technical ideas should be accessible to everyone, and that deeper understanding will help us develop better software.
1.事务及隔离级别 1.1.Read Committed 定义 一个事务只能看到其它事务已经提交的修改,不能看到其它事务进行中产生的修改。 实现方法 对任一事务修改的数据,在事务提交前均同时记录新值和旧值。其它事务读到此数据时,使用旧值;本事务读取时,使用新值。 一致性缺陷:不可重复...
评分本书开头提到“当今很多新型应用都属于数据密集型(data-intensive)而不是计算密集型(compute-intensive)” 当今机器学习越来越普及的情况下其实用户应用后面基础件层的compute-intensive应用越来越多了。“很可惜,让鄙人日常头秃都是 compute-intensive的,啥时候有一本De...
评分本书开头提到“当今很多新型应用都属于数据密集型(data-intensive)而不是计算密集型(compute-intensive)” 当今机器学习越来越普及的情况下其实用户应用后面基础件层的compute-intensive应用越来越多了。“很可惜,让鄙人日常头秃都是 compute-intensive的,啥时候有一本De...
评分 评分版权归作者所有,任何形式转载请联系作者。 作者:荒城梦(来自豆瓣) 来源:https://www.douban.com/note/725242700/ 陆陆续续有几个月过去了,终于把这本“鸿篇巨制”读完了。本书在计算机类著作里并不算特别厚,说鸿篇巨制是因为随着越往后读越发觉得此书内容之广度与深度已...
挺适合准备系统设计面试的,twitter的pull, push模型,database sharding 和 replication都讲得比较清楚
评分结构很好的一本书。能把一些听起来玄乎的概念(特别是一些翻译成中文后,更加让人困惑的东西)讲得比较清楚,这大概和作者的日常知识积累是分不开的吧。
评分http://martin.kleppmann.com/
评分主要看了前两部分,我觉得是最好的数据库/分布式存储的入门扫盲书,每章后面引用的paper可以让你更深入。
评分蛮好的,大数据、分布式系统的基础书,都琢磨透了架构师妥妥的 线性一致性这章需要深入研究一下。 准备再读一遍
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