Big Data Mastery Series – Distributed Theory Foundations and Principles
This article introduces the foundational concepts and principles of distributed systems—including basic concepts, consistency models, CAP theorem, logical clocks, and advanced protocols like Paxos, Raft, and Zab—serving as the first part of a comprehensive Big Data mastery series.
This article is part of the "Big Data Mastery" series, aiming to provide a comprehensive guide with over 500 articles, currently 50+ published, on big data technologies.
It outlines the first section titled "Distributed Theory Foundations and Principles", covering essential concepts of distributed systems.
Basic concepts of distributed systems
Consistency models, 2PC and 3PC
CAP theorem and its practical implications
Logical clocks and event ordering
Advanced consensus protocols: Paxos, Raft, Zab
Leader election, quorum, and lease mechanisms
Each topic is briefly introduced, explaining its role in distributed architecture, such as how Paxos ensures agreement despite failures, and how Raft and Zab compare to Paxos.
The article also previews upcoming topics, including distributed transaction solutions, ID generation schemes, and various distributed lock implementations.
Readers are encouraged to follow the series for deeper insights into building robust big data systems.
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Big Data Technology & Architecture
Wang Zhiwu, a big data expert, dedicated to sharing big data technology.
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