下面论文均为大数据和分布式比较经典的论文，包括：CAP、BASE、2PC、一致性协议、一致性哈希、逻辑时钟、Leases 等。如果大家还有比较好的论文，欢迎在下面评论。

分布式理论

• Time, Clocks, and the Ordering of Events in a Distributed System
• Reaching Agreement in the Presence of Faults
• The Byzantine General Problem
• (CAP) Brewer's Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services
• (2PC) Concurrency Control and Recovery in Database Systems
• BASE: An Acid Alternative
• An Overview of Clock Synchronization
• Epidemic Algorithms for Replicated Database Maintenance
• Leases: An Efficient Fault-Tolerant Mechanism for Distributed File Cache Consistency
• Weighted Voting for Replicated Data
• A Quorum-Consensus Replication Method for Abstract Data Types
• Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web

一致性

• (Paxos) The Part-Time Parliament
• Paxos Made Simple
• Paxos Made Practical
• Paxos Made Live - An Engineering Perspective
• Revisiting the Paxos algorithm
• Distributed Snapshots: Determining Global States of Distributed Systems
• Lightweight Asynchronous Snapshots for Distributed Dataflows
• ZooKeeper's atomic broadcast protocol: Theory and practice
• (Raft) In Search of an Understandable Consensus Algorithm

Google

• The Google File System
• MapReduce: Simplified Data Processing on Large Clusters
• Bigtable: A Distributed Storage System for Structured Data
• The Chubby lock service for loosely-coupled distributed systems
• Large-scale Incremental Processing Using Distributed Transactions and Notifications
• Dremel: Interactive Analysis of Web-Scale Datasets
• Omega: flexible, scalable schedulers for large compute clusters
• MillWheel: Fault-Tolerant Stream Processing at Internet Scale
• Large-scale cluster management at Google with Borg
• Dapper, a Large-Scale Distributed Systems Tracing Infrastructure
• Percolator: Large-scale Incremental Processing Using Distributed Transactions and Notifications
• Spanner: Google's Globally-Distributed Database
• F1: A Distributed SQL Database That Scales
• Pregel: A System for Large-Scale Graph Processing
• The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing

通用计算框架

• MapReduce: Simplified Data Processing on Large Clusters
• Hive - A Warehousing Solution Over a Map-Reduce Framework
• Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing
• Spark: Cluster Computing with Working Sets

Streaming

• Storm @Twitter
• Discretized Streams: Fault-Tolerant Streaming Computation at Scale
• Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters
• Apache Flink™: Stream and Batch Processing in a Single Engine
• Twitter Heron: Stream Processing at Scale
• Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark
• S4: Distributed Stream Computing Platform

消息队列

• Kafka: a Distributed Messaging System for Log Processing

KV Database & Database

• Bigtable: A Distributed Storage System for Structured Data
• Dynamo: Amazon's Highly Available Key-value Store
• Cassandra - A Decentralized Structured Storage System
• Serving Large-scale Batch Computed Data with Project Voldemort
• Schema-Agnostic Indexing with Azure DocumentDB

Schedulers

• Column-Stores vs. Row-Stores: How Different Are They Really?
• Apache Hadoop YARN: Yet Another Resource Negotiator
• Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
• Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling

Storages

• The Google File System
• The Hadoop Distributed File System
• Column-Stores vs. Row-Stores: How Different Are They Really?
• Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks
• RCFile: A Fast and Space-efficient Data Placement Structure in MapReduce-based Warehouse Systems
• (ORC) Major Technical Advancements in Apache Hive
• Erasure Codes for Storage Systems

协调

• The Chubby lock service for loosely-coupled distributed systems
• ZooKeeper: Wait-free coordination for Internet-scale systems

其他

• GraphX: Graph Processing in a Distributed Dataflow Framework
• MLlib: Machine Learning in Apache Spark
• Shark: SQL and Rich Analytics at Scale
• Spark SQL: Relational Data Processing in Spark