2011 – 2012
- ??2012?–?Twitter?– The Unified Logging Infrastructure for Data Analytics at Twitter.?(Twitter数据分析的统一日志基础结构)
- ??2012?–?AMPLab?–Blink and It’s Done: Interactive Queries on Very Large Data.?(Blink及其完成:超大规模数据的交互式查询)
- ??2012?–?AMPLab?–Fast and Interactive Analytics over Hadoop Data with Spark.?(Spark上?Hadoop数据的快速交互式分析)
- ??2012?–?AMPLab?–Shark: Fast Data Analysis Using Coarse-grained Distributed Memory.?(Shark:使用粗粒度的分布式内存快速数据分析)
- ??2012?–?Microsoft?–Paxos Replicated State Machines as the Basis of a High-Performance Data Store.?(Paxos的复制状态机——高性能数据存储的基础)
- ??2012?–?Microsoft?–Paxos Made Parallel.?(Paxos算法实现并行)
- ??2012?–?AMPLab?– BlinkDB:BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data.(超大规模数据中有限误差与有界响应时间的查询)
- ??2012?–?Google?–Processing a trillion cells per mouse click.(每次点击处理一兆个单元格)
- ??2012?–?Google?–Spanner: Google’s Globally-Distributed Database.(Spanner:谷歌的全球分布式数据库)
- ??2011?–?AMPLab?–Scarlett: Coping with Skewed Popularity Content in MapReduce Clusters.(Scarlett:应对MapReduce集群中的偏向性内容)
- ??2011?–?AMPLab?–Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center.(Mesos:数据中心中细粒度资源共享的平台)
- ??2011?–?Google?–Megastore: Providing Scalable,Highly Available Storage for Interactive Services.(Megastore:为交互式服务提供可扩展,高度可用的存储)
2001 – 2010
- ??2010?–?Facebook?–?Finding a needle in Haystack: Facebook’s photo storage.(探究Haystack中的细微之处:?Facebook图片存储)
- ??2010?–?AMPLab?–?Spark: Cluster Computing with Working Sets.(Spark:工作组上的集群计算)
- ??2010?–?Google?– Storage Architecture and Challenges.(存储架构与挑战)
- ??2010?–?Google?– Pregel: A System for Large-Scale Graph Processing.(Pregel: 一种大型图形处理系统)
- ??2010?–?Google?– Large-scale Incremental Processing Using Distributed Transactions and Noti?cations base of Percolator and Caffeine.(使用基于Percolator 和?Caffeine平台分布式事务和通知的大规模增量处理)
- ??2010?–?Google?– Dremel: Interactive Analysis of Web-Scale Datasets.(Dremel: Web规模数据集的交互分析)
- ??2010?–?Yahoo?–?S4: Distributed Stream Computing Platform.(S4:分布式流计算平台)
- ??2009?– HadoopDB:An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads.(混合MapReduce和DBMS技术用于分析工作负载的的架构)
- ??2008?–?AMPLab?– Chukwa: A large-scale monitoring system.(Chukwa: 大型监控系统)
- ??2007?–?Amazon?– Dynamo: Amazon’s Highly Available Key-value Store.(Dynamo: 亚马逊的高可用的关键价值存储)
- ??2006?–?Google?– The Chubby lock service for loosely-coupled distributed systems.(面向松散耦合的分布式系统的锁服务)
- ??2006?–?Google?– Bigtable: A Distributed Storage System for Structured Data.(Bigtable: 结构化数据的分布式存储系统)
- ??2004?–?Google?– MapReduce: Simplied Data Processing on Large Clusters.(MapReduce: 大型集群上简化数据处理)
- ??2003?–?Google?– The Google File System.(谷歌文件系统)
视频
数据可视化
- ??数据可视化之美
- ??Noah Iliinsky的数据可视化设计
- ??Hans Rosling’s 200 Countries,200 Years,4 Minutes
- ??冰桶挑战的数据可视化
(编辑:ASP站长网)
|