分布式系统领域经典论文翻译集

一．google论文系列

1. google系列论文译序

2. The anatomy of a large-scale hypertextual Web search engine (译 zz)

3. web search for a planet :the google cluster architecture(译)

4. GFS：google文件系统 (译)

5. MapReduce: Simplied Data Processing on Large Clusters (译)

6. Bigtable: A Distributed Storage System for Structured Data (译)

7. Chubby: The Chubby lock service for loosely-coupled distributed systems (译)

8. Sawzall:Interpreting the Data–Parallel Analysis with Sawzall (译 zz)

9. Pregel: A System for Large-Scale Graph Processing (译)

10. Dremel: Interactive Analysis of WebScale Datasets(译zz)

11. Percolator: Large-scale Incremental Processing Using Distributed Transactions and Notifications(译zz)

12. MegaStore: Providing Scalable, Highly Available Storage for Interactive Services(译zz)

13. Case Study GFS: Evolution on Fast-forward (译)

14. Google File System II: Dawn of the Multiplying Master Nodes

15. Tenzing – A SQL Implementation on the MapReduce Framework (译)

16. F1-The Fault-Tolerant Distributed RDBMS Supporting Google’s Ad Business

17. Elmo: Building a Globally Distributed, Highly Available Database

18. PowerDrill：Processing a Trillion Cells per Mouse Click

19. Google-Wide Profiling:A Continuous Profiling Infrastructure for Data Centers

20. Spanner: Google’s Globally-Distributed Database(译zz)

21. Dapper, a Large-Scale Distributed Systems Tracing Infrastructure(笔记)

22. Omega: flexible, scalable schedulers for large compute clusters

23. CPI2: CPU performance isolation for shared compute clusters

24. Photon: Fault-tolerant and Scalable Joining of Continuous Data Streams(译)

25. F1: A Distributed SQL Database That Scales

26. MillWheel: Fault-Tolerant Stream Processing at Internet Scale(译)

27. B4: Experience with a Globally-Deployed Software Defined WAN

28. The Datacenter as a Computer

29. Google brain-Building High-level Features Using Large Scale Unsupervised Learning

30. Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing(译zz)

31. Large-scale cluster management at Google with Borg

google系列论文翻译集(合集)

二．分布式理论系列

00. Appraising Two Decades of Distributed Computing Theory Research

0.
分布式理论系列译序

1. A brief history of Consensus_ 2PC and Transaction Commit (译)

2. 拜占庭将军问题 (译) –Leslie Lamport

3. Impossibility of distributed consensus with one faulty process (译)

4. Leases：租约机制 (译)

5. Time Clocks and the Ordering of Events in a Distributed System(译) –Leslie Lamport

6. 关于Paxos的历史

7. The Part Time Parliament (译 zz) –Leslie Lamport

8.
How to Build a Highly Available System Using Consensus(译)

9. Paxos Made Simple (译) —Leslie Lamport

10. Paxos Made Live – An Engineering Perspective(译)

11.
2 Phase Commit(译)

12.
Consensus on Transaction Commit(译)
–Jim Gray & Leslie Lamport

13.
Why Do Computers Stop and What Can Be Done About It?(译)

–Jim Gray

14.
On Designing and Deploying Internet-Scale Services(译) –James Hamilton

15.
Single-Message Communication(译)

16. Implementing fault-tolerant services using the state machine approach

17. Problems, Unsolved Problems and Problems in Concurrency

18. Hints for Computer System Design

19. Self-stabilizing systems in spite of distributed control

20. Wait-Free Synchronization

21. White Paper Introduction to IEEE 1588 & Transparent Clocks

22. Unreliable Failure Detectors for Reliable Distributed Systems

23.
Life beyond Distributed Transactions:an Apostate’s Opinion(译zz)

24. Distributed Snapshots: Determining Global States of a Distributed System –Leslie Lamport

25. Virtual Time and Global States of Distributed Systems

26. Timestamps in Message-Passing Systems That Preserve the Partial Ordering

27. Fundamentals of Distributed Computing:A Practical Tour of Vector Clock Systems

28. Knowledge and Common Knowledge in a Distributed Environment

29. Understanding Failures in Petascale Computers

30. Why Do Internet services fail, and What Can Be Done About It?

31. End-To-End Arguments in System Design

32. Rethinking the Design of the Internet: The End-to-End Arguments vs. the Brave New World

33.
The Design Philosophy of the DARPA Internet Protocols(译zz)

34. Uniform consensus is harder than consensus

35.
Paxos made code –
Implementing a high throughput Atomic Broadcast

36.
RAFT:In Search of an Understandable Consensus Algorithm

分布式理论系列论文翻译集(合集)

三．数据库理论系列

0. A Relational Model of Data for Large Shared Data Banks –E.F.Codd 1970

1. SEQUEL：A Structured English Query Language 1974

2. Implentation of a Structured English Query Language 1975

3. A System R: Relational Approach to Database Management 1976

4. Granularity of Locks and Degrees of Consistency in a Shared DataBase –Jim Gray 1976

5. Access Path Selection in a RDBMS 1979

6. The Transaction Concept:Virtues and Limitations –Jim Gray

7. 2pc-2阶段提交：Notes on Data Base Operating Systems –Jim Gray

8. 3pc-3阶段提交：NONBLOCKING COMMIT PROTOCOLS

9. MVCC：Multiversion Concurrency Control-Theory and Algorithms –1983

10.
ARIES:

A

Transaction

Recovery

Method

Supporting

Fine-Granularity

Locking

and
Partial Rollbacks Using Write-Ahead Logging-1992

11. A Comparison of the Byzantine Agreement Problem and the Transaction Commit Problem –Jim Gray

12.
A Formal Model of Crash Recovery in a Distributed System – Skeen, D. Stonebraker

13. What Goes Around Comes Around – Michael Stonebraker, Joseph M. Hellerstein

14. Anatomy of a Database System -Joseph M. Hellerstein, Michael Stonebraker

15.
Architecture of a Database System(译zz)
-Joseph M. Hellerstein, Michael Stonebraker, James Hamilton

四．大规模存储与计算(NoSql理论系列)

0. Towards Robust Distributed Systems：Brewer’s 2000 PODC key notes

1. CAP理论

2. Harvest, Yield, and Scalable Tolerant Systems

3. 关于CAP

4. BASE模型：BASE an Acid Alternative

9. scalability-availability-stability-patterns

10. The 5 Minute Rule and the 5 Byte Rule (译)

11.
The Five-Minute Rule Ten Years Later and Other Computer Storage Rules of Thumb

12. The Five-Minute Rule 20 Years Later(and How Flash Memory Changes the Rules)

13. 关于MapReduce的争论

14. MapReduce：一个巨大的倒退

15. MapReduce：一个巨大的倒退(II)

16. MapReduce和并行数据库，朋友还是敌人？(zz)

17. MapReduce and Parallel DBMSs-Friends or Foes (译)

18. MapReduce:A Flexible Data Processing Tool (译)

19. A Comparision of Approaches to Large-Scale Data Analysis (译)

20. MapReduce Hold不住？(zz)

21. Beyond MapReduce：图计算概览

22. Map-Reduce-Merge: simplified relational data processing on large clusters

23. MapReduce Online

24. Graph Twiddling in a MapReduce World

25. Spark: Cluster Computing with Working Sets

26. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing

27. Big Data Lambda Architecture

28. The 8 Requirements of Real-Time Stream Processing

29. The Log: What every software engineer should know about real-time data’s unifying abstraction

30. Lessons from Giant-Scale Services

五．基本算法和数据结构

1. 大数据量，海量数据处理方法总结

2. 大数据量，海量数据处理方法总结(续)

3. Consistent Hashing And Random Trees

4. Merkle Trees

5. Scalable Bloom Filters

6. Introduction to Distributed Hash Tables

7. B-Trees and Relational Database Systems

8. The log-structured merge-tree (译)

9. lock free data structure

10. Data Structures for Spatial Database

11. Gossip

12. lock free algorithm

13. The Graph Traversal Pattern

六．基本系统和实践经验

1. MySQL索引背后的数据结构及算法原理

2. Dynamo: Amazon’s Highly Available Key-value Store (译zz)

3. Cassandra – A Decentralized Structured Storage System (译zz)

4. PNUTS: Yahoo!’s Hosted Data Serving Platform (译zz)

5. Yahoo!的分布式数据平台PNUTS简介及感悟(zz)

6. LevelDB：一个快速轻量级的key-value存储库(译)

7. LevelDB理论基础

8. LevelDB：实现(译)

9. LevelDB SSTable格式详解

10. LevelDB Bloom Filter实现

11. Sawzall原理与应用

12. Storm原理与实现

13. Designs, Lessons and Advice from Building Large Distributed Systems –Jeff Dean

14. Challenges in Building Large-Scale Information Retrieval Systems –Jeff Dean

15. Experiences with MapReduce, an Abstraction for Large-Scale Computation –Jeff Dean

16. Taming Service Variability,Building Worldwide Systems,and Scaling Deep Learning –Jeff Dean

17. Large-Scale Data and Computation:Challenges and Opportunitis –Jeff Dean

18. Achieving Rapid Response Times in Large Online Services –Jeff Dean

19. The Tail at Scale(译) –Jeff Dean & Luiz André Barroso

20. How To Design A Good API and Why it Matters

21. Event-Based Systems:Architect’s Dream or Developer’s Nightmare?

22. Autopilot: Automatic Data Center Management

七．其他辅助系统

1. The ganglia distributed monitoring system:design, implementation, and experience

2. Chukwa: A large-scale monitoring system

3. Scribe : a way to aggregate data and why not, to directly fill the HDFS?

4. Benchmarking Cloud Serving Systems with YCSB

5. Dynamo Dremel ZooKeeper Hive 简述

八. Hadoop相关

0. Hadoop Reading List

1. The Hadoop Distributed File System(译)

2. HDFS scalability:the limits to growth(译)

3. Name-node memory size estimates and optimization proposal.

4. HBase Architecture(译)

5. HFile：A Block-Indexed File Format to Store Sorted Key-Value Pairs

6. HFile V2

7. Hive – A Warehousing Solution Over a Map-Reduce Framework

8. Hive – A Petabyte Scale Data Warehouse Using Hadoop

9. HIVE RCFile高效存储结构

10. ZooKeeper: Wait-free coordination for Internet-scale systems

11. The life and times of a zookeeper

12. Avro: 大数据的数据格式(zz)

13. Apache Hadoop Goes Realtime at Facebook (译)

14. Hadoop平台优化综述(zz)

15. The Anatomy of Hadoop I/O Pipeline (译)

16. Hadoop公平调度器指南(zz)

17. 下一代Apache Hadoop MapReduce

18. Apache Hadoop 0.23

九．深入理解计算机系统

十．其他

On Computable Numbers with an Application to the Entscheidungsproblem-1936.5.28-A.M.Turing

The First Draft Report on the EDVAC-1945.6.30-John von Neumann

Reflections on Trusting Trust –Ken Thompson

Who Needs an Architect?

Go To statements considered harmfull –Edsger W.Dijkstra

No Silver Bullet Essence and Accidents of Software Engineering –Frederick P. Brooks

转载请注明作者：phylips@bmy 2011-4-30

出处：http://duanple.blog.163.com/blog/static/709717672011330101333271/

再推荐一个相关文章：http://blog.nosqlfan.com/html/1647.html

列举的大部分论文都是相同的，不过也有一些是各自独有的。

分布式系统阅读清单

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分布式系统领域经典论文翻译集

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