Abstract Classical strategies do not aware of recovery cost, which could cause system performance degradation.   -->  a cost aware eviction strategt can obviously reduces the total recovery cost. A strategy named LCS(Least cost strategy) -->  gets t…

原文:https://www.ibm.com/developerworks/library/j-zerocopy/ <Efficient data transfer through zero copy> 本文描述通过一种叫做Zore Copy的技术来提升运行在Linux和UNIX上的Java程序的IO性能. Zero copy避免冗余的数据拷贝并减少用户态和内核态之间的上下文切换. 很多WEB应用都服务大量的静态文件,这些静态文件大多从磁盘读取并返回到socket中.这些操作需要相对较少的CP…

Efficient data transfer through zero copy https://www.ibm.com/developerworks/library/j-zerocopy/ Efficient data transfer through zero copy Zero copy, zero overhead Sathish K. Palaniappan and Pramod B. NagarajaPublished on September 02, 2008 FacebookT…

BACKGROUND A single physical platform may be segregated into a plurality of virtual networks. Here, the physical platform incorporates at least one virtual machine monitor (VMM). A conventional VMM typically runs on a computer and presents to other s…

[标题] [作者] [来源] [对本文评价] [why] 存在的问题 [how] [不足] assumption future work [相关方法或论文] [重点提示] [其它]…

此书不错,很短,且想打通PYTHON和大数据架构的关系. 先看一次,计划把这个文档作个翻译. 先来一个模拟MAPREDUCE的东东... mapper.py class Mapper: def map(self, data): returnval = [] counts = {} for line in data: words = line.split() for w in words: counts[w] = counts.get(w, 0) + 1 for w, c in counts.it…

摘要:本文则主要介绍TalkingData在大数据平台建设过程中,逐渐引入Spark,并且以Hadoop YARN和Spark为基础来构建移动大数据平台的过程. 当下,Spark已经在国内得到了广泛的认可和支持:2014年,Spark Summit China在北京召开,场面火爆:同年,Spark Meetup在北京.上海.深圳和杭州四个城市举办,其中仅北京就成功举办了5次,内容更涵盖Spark Core.Spark Streaming.Spark MLlib.Spark SQL等众多领域.而作…

前言:工欲善其事,必先利其器.倘若不懂得构建一套大数据挖掘环境,何来谈Data Mining!何来领悟“Data Mining Engineer”中的工程二字!也仅仅是在做数据分析相关的事罢了!此文来自于笔者在实践项目开发中的记录,真心希望日后成为所有进入大数据领域挖掘工程师们的良心参考资料.下面是它的一些说明: 它是部署在Windows环境,在项目的实践开发过程中,你将通过它去完成与集群的交互,测试和发布: 你可以部署成使用MapReduce框架,而本文主要优先采用Spark版本: 于你而言,…

Paper about Event Detection. #@author: gr #@date: 2014-03-15 #@email: forgerui@gmail.com 看一些相关的论文. 1. <Efficient Visual Event Detection using Volumetric Features> ICCV 2005 扩展2D box 特征到3D时空特征. 构建一个实时的检测器基于容积特征. 采用传统的兴趣点方法检测事件. 2. <ARMA-HMM: A New…

http://highlyscalable.wordpress.com/2013/08/20/in-stream-big-data-processing/   Overview In recent years, this idea got a lot of traction and a whole bunch of solutions like Twitter's Storm, Yahoo's S4, Cloudera's Impala, Apache Spark, and Apache Tez…