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的最后一节实现状态机如何理解

《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 Replication和Paper 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.

• Harvest, Yield and Scalable Tolerant Systems - Real world applications of CAP from Brewer et al
• On Designing and Deploying Internet Scale Services - James Hamilton
• The Perils of Good Abstractions - Building the perfect API/interface is difficult
• Chaotic Perspectives - Large scale systems are everything developers dislike - unpredictable, unordered and parallel
• Data on the Outside versus Data on the Inside - Pat Helland
• Memories, Guesses and Apologies - Pat Helland
• SOA and Newton's Universe - Pat Helland
• Building on Quicksand - Pat Helland
• Why Distributed Computing? - Jim Waldo
• A Note on Distributed Computing - Waldo, Wollrath et al
• Stevey's Google Platforms Rant - Yegge's SOA platform experience

Latency

• Latency Exists, Cope! - Commentary on coping with latency and it's architectural impacts
• Latency - the new web performance bottleneck - not at all new (see Patterson), but noteworthy
• The Tail At Scale - the latencychallenges inherent of dealing with latency in large scale systems

Amazon

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

• A Conversation with Werner Vogels - Coverage of Amazon's transition to a service-based architecture
• Discipline and Focus - Additional coverage of Amazon's transition to a service-based architecture
• Vogels on Scalability
• SOA creates order out of chaos @ Amazon

Google

Current "rocket science" in distributed systems.

• MapReduce
• Chubby Lock Manager
• Google File System
• BigTable
• Data Management for Internet-Scale Single-Sign-On
• Dremel: Interactive Analysis of Web-Scale Datasets
• Large-scale Incremental Processing Using Distributed Transactions and Notifications
• Megastore: Providing Scalable, Highly Available Storage for Interactive Services - Smart design for low latency Paxos implementation across datacentres.
• Spanner - Google's scalable, multi-version, globally-distributed, and synchronously-replicated database.
• Photon - Fault-tolerant and Scalable Joining of Continuous Data Streams. Joins are tough especially with time-skew, high availability and distribution.
• Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing - Data warehousing system that stores critical measurement data related to Google's Internet advertising business.

Consistency Models

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

• CAP Conjecture - Consistency, Availability, Parition Tolerance cannot all be satisfied at once
• Consistency, Availability, and Convergence - Proves the upper bound for consistency possible in a typical system
• CAP Twelve Years Later: How the "Rules" Have Changed - Eric Brewer expands on the original tradeoff description
• Consistency and Availability - Vogels
• Eventual Consistency - Vogels
• Avoiding Two-Phase Commit - Two phase commit avoidance approaches
• 2PC or not 2PC, Wherefore Art Thou XA? - Two phase commit isn't a silver bullet
• Life Beyond Distributed Transactions - Helland
• If you have too much data, then 'good enough' is good enough - NoSQL, Future of data theory - Pat Helland
• Starbucks doesn't do two phase commit - Asynchronous mechanisms at work
• You Can't Sacrifice Partition Tolerance - Additional CAP commentary
• Optimistic Replication - Relaxed consistency approaches for data replication

Theory

Papers that describe various important elements of distributed systems design.

• Distributed Computing Economics - Jim Gray
• Rules of Thumb in Data Engineering - Jim Gray and Prashant Shenoy
• Fallacies of Distributed Computing - Peter Deutsch
• Impossibility of distributed consensus with one faulty process - also known as FLP [access requires account and/or payment, a free version can be found here]
• Unreliable Failure Detectors for Reliable Distributed Systems. A method for handling the challenges of FLP
• Lamport Clocks - How do you establish a global view of time when each computer's clock is independent
• The Byzantine Generals Problem
• Lazy Replication: Exploiting the Semantics of Distributed Services
• Scalable Agreement - Towards Ordering as a Service
• Scalable Eventually Consistent Counters over Unreliable Networks - Scalable counting is tough in an unreliable world

Languages and Tools

Issues of distributed systems construction with specific technologies.

• Programming Distributed Erlang Applications: Pitfalls and Recipes - Building reliable distributed applications isn't as simple as merely choosing Erlang and OTP.

Infrastructure

• Principles of Robust Timing over the Internet - Managing clocks is essential for even basics such as debugging

Storage

• Consistent Hashing and Random Trees
• Amazon's Dynamo Storage Service

Paxos Consensus

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

• The Part-Time Parliament - Leslie Lamport
• Paxos Made Simple - Leslie Lamport
• Paxos Made Live - An Engineering Perspective - Chandra et al
• Revisiting the Paxos Algorithm - Lynch et al
• How to build a highly available system with consensus - Butler Lampson
• Reconfiguring a State Machine - Lamport et al - changing cluster membership
• Implementing Fault-Tolerant Services Using the State Machine Approach: a Tutorial - Fred Schneider

Other Consensus Papers

• Mencius: Building Efficient Replicated State Machines for WANs - consensus algorithm for wide-area network

Gossip Protocols (Epidemic Behaviours)

• How robust are gossip-based communication protocols?
• Astrolabe: A Robust and Scalable Technology For Distributed Systems Monitoring, Management, and Data Mining
• Epidemic Computing at Cornell
• Fighting Fire With Fire: Using Randomized Gossip To Combat Stochastic Scalability Limits
• Bi-Modal Multicast
• ACM SIGOPS Operating Systems Review - Gossip-based computer networking
• SWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocol

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

• General Papers
• Topics
  • Datastores
  • Physics
  • Testing, Verification, and Correctness

External Papers

•  A Note on Distributed Computing

• A simple totally ordered broadcast protocol

• Above the Clouds: A Berkeley View of Cloud Computing

• Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications

• Kafka: a Distributed Messaging System for Log Processing

• Large-scale cluster management at Google with Borg

• Linearizability: A Correctness Condition for Concurrent Objects

• Implementing Fault-Tolerant Services Using the State Machine Approach: A Tutorial

• Hoard: A Scalable Memory Allocator for Multithreaded Applications

• MillWheel: Fault-Tolerant Stream Processing at Internet Scale

• Omega: flexible, scalable schedulers for large compute clusters

• Orleans: Distributed Virtual Actors for Programmability and Scalability

• Paxos Made Live - An Engineering Perspective

• Practical Byzantine Fault Tolerance and Proactive Recovery

• Pregel: A System for Large-Scale Graph Processing

• Replication, History, and Grafting in the Ori File System

• Resilient Overlay Networks

• Sinfonia: A New Paradigm for Building Scalable Distributed Systems

• Sparrow: Distributed, Low Latency Scheduling

• The Byzantine Generals Problem

•  The Chubby Lock Service for Loosely-Coupled Distributed Systems

•  The Join Calculus: a Language for Distributed Mobile Programming

• The Part-Time Parliament

• There Is More Consensus in Egalitarian Parliaments

• Transactional Client-Server Cache Consistency: Alternatives and Performance

• Unicorn: A System for Searching the Social Graph

• Unikernels: Library Operating Systems for the Cloud

• Untraceable Electronic Mail, Return Addresses, and Digital Pseudonyms

• Viewstamped Replication: A New Primary Copy Method to Support Highly-Available Distributed Systems

• VL2: A Scalable and Flexible Data Center Network

Other Hosted Papers

•  A History of the Virtual Synchrony Replication Model

•  A Hundred Impossibility Proofs for Distributed Systems

•  A response to Cheriton and Skeen's Criticism of Causal and Totally Ordered Communication

•  A Universal Modular ACTOR Formalism for Artificial Intelligence

•  A Versatile Scheme for Routing Highly Variable Traffic in Service Overlays and IP Backbones

•  Beehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays

•  Byzantine Chain Replication

•  A Byzantine Fault Tolerant Distributed Commit Protocol

•  Brewer’s Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services

•  Chain Replication for Supporting High Throughput and Availability

•  Commodifying Replicated State Machines with OpenReplica

•  Consensusin the Presenceof Partial Synchrony

•  Consistent Global States of Distributed Systems: Fundamental Concepts and Mechanisms

•  Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web

•  Copysets: Reducing the Frequency of Data Loss in Cloud Storage

•  Dapper, a Large-Scale Distributed Systems Tracing Infrastructure

•  Distributed Snapshots: Determining Global States of Distributed Systems

•  Eluding Carnivores: File Sharing with Strong Anonymity

•  End-to-end arguments in system design

•  Epidemic Algorithms for Replicated Database Maintenance

•  Harvest, Yield, and Scalable Tolerant Systems

•  Herbivore: A Scalable and Efficient Protocol for Anonymous Communication

•  High-Level Specifications: Lessons from Industry

•  How the Hidden Hand Shapes the Market for Software Reliability

•  Implementing the Omega failure detector in the crash-recovery failure model

•  Impossibility of Distributed Consensuswith One Faulty Process

•  In Search of an Understandable Consensus Algorithm

•  Kelips*: Building an Efficient and Stable P2P DHT Through Increased Memory and Background Overhead

•  Large-scale Incremental Processing Using Distributed Transactions and Notifications

•  Life beyond Distributed Transactions: an Apostate’s Opinion

•  MapReduce: Simplified Data Processing on Large Clusters

•  Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center

•  Oblivious routing of highly variable traffic in service overlays and IP backbones

•  On proof and progress in mathematics

•  P5: A Protocol for Scalable Anonymous Communication

•  Pastry: Scalable, decentralized object location and routing for large-scale peer-to-peer systems

•  Paxos Made Moderately Complex

•  Paxos Made Simple

•  Self-stabilizing Systems in Spite of Distributed Control

•  SIFT: Design and Analysis of a Fault-Tolerant Computer for Aircraft Control

•  Signal/Collect: Graph Algorithms for the (Semantic) Web

•  Slution of a Problem in Concurrent Programming Control

•  Sparse Partitions

•  Stronger Semantics for Low-Latency Geo-Replicated Storage

•  The Akamai Network: A Platform for High-Performance Internet Applications

•  The Dining CryptographersProblem: Unconditional Sender and Recipient Untraceability

•  Tor: The Second-Generation Onion Router

•  Towards a cloud computing research agenda

•  Understanding the Limitations of Causally and Totally Ordered Communication

•  Viewing Control Structures as Patterns of Passing Messages

•  Warp: Multi-Key Transactions for Key-Value Stores

•  Zab: High-performance broadcast for primary-backup systems

•  ZooKeeper: Wait-free coordination for Internet-scale systems

•  Tiered Replication: A Cost-effective Alternative to Full Cluster Geo-replication

Topics

Datastores

• Calvin: Fast Distributed Transactions for Partitioned Database Systems

• f4: Facebook’s Warm BLOB Storage System

• The Case for Determinism in Database Systems

• Consistency Tradeoffs in Modern Distributed Database System Design

• Modularity and Scalability in Calvin

• Lightweight Locking for Main Memory Database Systems

• Cassandra - A Decentralized Structured Storage System

• CRUSH: Controlled, Scalable, Decentralized Placement of Replicated Data

• Don’t Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPS

• Dremel: Interactive Analysis of Web-Scale Datasets

• F1: A Distributed SQL Database That Scales

• HaLoop: Efficient Iterative Data Processing on Large Clusters

• HyperDex: A Distributed, Searchable Key-Value Store

• Introduction to a System for Distributed Databases SDD-1

• Making Reliable Distributed Systems in the Presence of Software Errors

• Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System

• Map-Reduce-Merge: Simplified Relational Data Processing on Large Clusters

• MDCC: Multi-Data Center Consistency

• Optimistic replication

• The Dangers of Replication and a Solution

• Towards a Next Generation Data Center Architecture: Scalability and Commoditization

•  Bigtable: A Distributed Storage System for Structured Data

•  Database Metatheory: Asking Big Queries

•  Dynamo: Amazon’s Highly Available Key-value Store

•  Flat Datacenter Storage

•  Freenet: A Distributed Anonymous Information Storage and Retrieval System

•  Megastore: Providing Scalable, Highly Available Storage for Interactive Services

•  A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster

•  RADOS: A Scalable, Reliable Storage Service for Petabyte-scale Storage Clusters

•  Spanner: Google’s Globally-Distributed Database

•  TAO: Facebooks Distributed Data Store for the Social Graph'

•  Transactional storage for geo-replicated systems

•  Warp: Multi-Key Transactions for Key-Value Stores

•  Spartan: A distributed array framework with smart tiling

Physics

•  “On the Electrodynamics of Moving Bodies” (1905) — Einstein

  By solving the asymmetries that arise in Maxwell’s equations, Einstein’s 1905 paper set the stage for current distributed systems work by demonstrating that there is no absolute frame of reference and by providing an upper bound on the speed of communication.

Testing, Verification, and Correctness

•  Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems

•  IronFleet: Proving Practical Distributed Systems Correct