分布式系统论文

https://cs.stanford.edu/~matei/courses/2015/6.S897/

http://blog.fnil.net/blog/ac1fa10ff9b2404ed0b91bdfaf76a87d/

http://pages.cs.wisc.edu/~remzi/Classes/739/Papers/paxos.pdf

https://www8.cs.umu.se/kurser/5DV131/VT15/handouts/L7_dm.pdf

http://lamport.azurewebsites.net/pubs/lamport-paxos.pdf

如何浅显易懂地解说 Paxos 的算法?

Paxos理论介绍(1): 朴素Paxos算法理论推导

Paxos理论介绍(2): Multi-Paxos与Leader

Paxos理论介绍(3): Master选举

Paxos理论介绍(4): 动态成员变更

分布式存储中,怎样使用paxos算法保证数据的一致性?

微信自研生产级paxos类库PhxPaxos实现原理介绍

http://mp.weixin.qq.com/s?__biz=MzI4NDMyNTU2Mw==&mid=2247483695&idx=1&sn=91ea422913fc62579e020e941d1d059e#rd

如果优化multi-paxos?

《Paxos Made Simple》

《Paxos Made live》

《The Chubby lock service for loosely-coupled distributed systems》

《The Chubby lock service for loosely-coupled distributed systems》

Paxos Made Practical

https://zhuanlan.zhihu.com/p/21438357?refer=lynncui

https://docs.google.com/viewer?url=https%3A%2F%2Fraft.github.io%2Fraft.pdf

https://ramcloud.stanford.edu/~ongaro/thesis.pdf

Paxos 我还着重推荐阅读微信后端团队写的系列博客,包括他们开源的 phxpaxos 实现,基本上将所有问题都讨论到了,并且通俗易懂。

但是 Raft 真的好理解多了,我读的是《In Search of an Understandable Consensus Algorithm》,论文写到这么详细的步骤,你不想理解都难。毕竟 Raft 号称就是一个 Understandable Consensus Algorithm。无论从任何角度,都推荐阅读这一篇论文。

首先能理解 paxos 的一些难点,其次是了解 Raft 的实现,加深对 Etcd 等系统的理解。这篇论文还有一个 250 多页的加强版《CONSENSUS: BRIDGING THEORY AND PRACTICE》,教你一行一行写出一个 Raft 实现,

最后,我还读了《Building Consistent Transactions with Inconsistent Replication》,包括作者的演讲,作者也开放了源码

关于 TAPIR 的解读推荐两篇博客:Building Consistent Transactions with Inconsistent ReplicationPaper review: Building Consistent Transactions with Inconsistent Replication (SOSP’15)。 TAPIR 的源码只包含了 normal case 的处理,恢复之类的过程都是没有的,对于 recovery 的一些疑问,可以参考 A FEW WORDS ABOUT INCONSISTENT REPLICATION (IR)

 

A Distributed Systems Reading List

 

Introduction

 

I often argue that the toughest thing about distributed systems is changing the way you think. The below is a collection of material I've found useful for motivating these changes.

Thought Provokers

Ramblings that make you think about the way you design. Not everything can be solved with big servers, databases and transactions.

Latency

Amazon

Somewhat about the technology but more interesting is the culture and organization they've created to work with it.

Google

Current "rocket science" in distributed systems.

Consistency Models

Key to building systems that suit their environments is finding the right tradeoff between consistency and availability.

Theory

Papers that describe various important elements of distributed systems design.

Languages and Tools

Issues of distributed systems construction with specific technologies.

Infrastructure

Storage

Paxos Consensus

Understanding this algorithm is the challenge. I would suggest reading "Paxos Made Simple" before the other papers and again afterward.

Other Consensus Papers

Gossip Protocols (Epidemic Behaviours)

P2P

  • Chord: A Scalable Peer-to-peer Lookup Protocol for Internet Applications
  • Kademlia: A Peer-to-peer Information System Based on the XOR Metric
  • Pastry: Scalable, decentralized object location and routing for large-scale peer-to-peer systems
  • PAST: A large-scale, persistent peer-to-peer storage utility - storage system atop Pastry
  • SCRIBE: A large-scale and decentralised application-level multicast infrastructure - wide area messaging atop Pastry

============

Distributed Systems

External Papers

Other Hosted Papers

Topics

Datastores

Physics

Testing, Verification, and Correctness

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