本文(OSDI 18')主要介绍一种新的副本复制协议:SAUCR(场景可感知的更新与故障恢复).它是一种混合的协议: 在一定场景(正常情况)下:副本复制的数据缓存在内存中. 故障发生时(多个节点挂掉,处于系统无法正常运行的边缘):副本复制的数据缓存同步刷入磁盘. 该协议在保证高性能的同时,保证了很强的持久性和可用性. Introduction 分布式存储系统通常通过维护多个副本来进行容错,这些协议都是基于Majority Based 复制协议进行的,例如raft,Paxos协议.这些Majori…

Working with State 本文翻译自Streaming Guide/ Fault Tolerance / Working with State ---------------------------------------------------------------------------------------- Flink中所有transformation可能都看上去像是方法(在functional processing术语中),但事实上它们都是有状态的Operator.你可…

false false false false EN-US ZH-CN X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:普通表格; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt…

 ——本文讲解了Storm故障容忍性(Fault-Tolerance)的设计细节:当Worker.节点.Nimbus或者Supervisor出现故障时是如何实现故障容忍性,以及Nimbus是否存在单点故障问题. 当一个Worker挂了会怎样? When a worker dies, the supervisor will restart it. If it continuously fails on startup and is unable to heartbeat to Nimbus, Ni…

State Backends 本文翻译自文档Streaming Guide / Fault Tolerance / StateBackend ----------------------------------------------------------------------------------------- 使用Data Stream API编写的程序通常以多种形式维护状态: ·  窗口将收集element或在它被触发后聚合element ·  Transformation方法可能会…

                                                            VMware vSphere服务器虚拟化实验十一高可用性之三Fault Tolerance Fault Tolerance(FT)即容错双机热备,通过创建与主实例保持虚拟同步的虚拟机实时影子实例,使应用在服务器发生故障的情况下也能够持续可用.通过在发生硬件故障时在两个实例之间进行即时故障切换,FT 完全消除了数据丢失或中断的风险确保业务连续性.Fault Tolerance 使…

VMware Fault Tolerance - 为您的应用程序提供全天候可用性 通过为虚拟机启用 VMware Fault Tolerance,最大限度地延长数据中心的正常运行时间,减少停机管理成本.基于 vLockstep 技术的 VMware Fault Tolerance 可使应用程序实现零停机.零数据丢失,同时消除了传统硬件或软件集群解决方案的成本和复杂性. 1.消除因硬件故障造成的停机VMware Fault Tolerance 是一项前沿技术,它通过创建实际上与主实例保持同步的虚拟…

Problem describe:https://leetcode.com/problems/linked-list-cycle/ Given a linked list, determine if it has a cycle in it. To represent a cycle -indexed) , then there is no cycle in the linked list. Example : Input: head = [,,,-], pos = Output: true E…

郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! 1 DeepMind, London, UK2 University College London, London, UK3 Princeton University, Princeton, NJ, USA*Correspondence: botvinick@google.com (M. Botvinick). Trends in Cognitive Sciences, May 2019, Vol. 23, No. 5 https:/…

跨时钟域设计中,对快时钟域的Trigger信号同步到慢时钟域,可以采用上面的电路实现,Verilog HDL设计如下:   // Trigger signal sync, Fast clock domain to slow domainmodule Trig_CrossDomain_F2S ( input clkB, input rst_n, input TrigIn_clkA,  output  reg TrigOut_clkB );  reg Q1,Q2,nQ2;  always @(pos…

本文介绍Storm容错的设计细节. 1.当一个worker进程死了会发生什么? 当worker死了,supervisor会重启它.如果它尝试开启多次失败并且不能与nimbus发送心跳,Nimbus会重新设计worker到另外一台机器上. 2.一个结点死了会发生什么? 分派到这台机器上的任务将会超时并且Nimbus会重新分派这些任务到另外一台机器上. 3.如果Nimbus或者Supervisor daemons死了会发生什么? Nimbus和Supervisor daemons必须在监控下运行,如…

摘要 这是一个关于ZooKeeper正在使用的全序广播协议(Zab)的简短概述.它在概念上很容易理解,也很容易实现,并且提供很高的性能.在这篇文章里,我们会呈现ZooKeeper在Zab上的需求,也会展示这个协议该如何使用,然后我们总体概述一下这个协议是如何工作的. 1. 简介 在雅虎(Yahoo!),我们开发了一款叫做ZooKeeper[9]的高性能高可用的协作服务,它允许大规模的应用群执行协作任务,比如Leader选举.状态传播和会合(rendezvous).该服务实现了一个层级的数据结点空…

通过状态快照进行容错 状态后台 Flink管理的键控状态是一种碎片化的.键/值存储,每项键控状态的工作副本都被保存在负责该键的任务管理员的本地某处.操作员的状态也被保存在需要它的机器的本地.Flink会定期对所有状态进行持久化快照,并将这些快照复制到某个更持久的地方,比如分布式文件系统. 在发生故障的情况下,Flink可以恢复你的应用程序的完整状态,并恢复处理,就像什么都没有发生过一样. Flink管理的这种状态被存储在状态后端中.状态后端有两种实现--一种是基于RocksDB的,它是一个嵌入式…

This article is from blog of Amazon CTO Werner Vogels. -------------------- Today is a very exciting day as we release Amazon DynamoDB, a fast, highly reliable and cost-effective NoSQL database service designed for internet scale applications. Dynamo…

https://spark.apache.org/sql/ Performance & Scalability Spark SQL includes a cost-based optimizer, columnar storage and code generation to make queries fast. At the same time, it scales to thousands of nodes and multi hour queries using the Spark eng…

by Henry Robinson, April 26, 2010 The 'CAP' theorem is a hot topic in the design of distributed data storage systems. However, it's often widely misused. In this post I hope to highlight why the common 'consistency, availability and partition toleran…

You're trying to set the record on your favorite video game. The game consists of N levels, which must be completed sequentially in order to beat the game. You usually complete each level as fast as possible, but sometimes finish a level slower. Spec…

在CAP理论中, 对partition tolerance分区容错性的解释一般指的是分布式网络中部分网络不可用时, 系统依然正常对外提供服务, 而传统的系统设计中往往将这个放在最后一位. 这篇文章对这个此进行了分析和重新定义, 并说明了在不同规模分布式系统中的重要性. The ‘CAP’ theorem is a hot topic in the design of distributed data storage systems. However, it’s often widely misu…

目录 vmware HA介绍 服务器添加存储,将存储挂载到服务器上 vcenter安装配置 群集配置 故障迁移测试 下载地址:百度云 参考文档: vmware HA介绍 vmware vm高可用至少需要两台服务器,一台存储,一台交换机,逻辑结构如下图:本篇采用vSphere HA和Fault Tolerance技术实现无间隔故障转移. 服务器添加存储,将存储挂载到服务器上 查看存储的数据传输ip ESXi中添加存储 存储系统里添加主机 将服务器加入群集 等待数分钟后,ESXI中发现数据存储 Vc…

状态和容错 在本节中,您将了解Flink为编写有状态程序提供的API.请看一下Stateful Stream Processing来了解有状态流处理背后的概念. 下一步去哪里? Working with State: Shows how to use state in a Flink application and explains the different kinds of state. The Broadcast State Pattern: Explains how to connect…

系统设计Design For Failure思想 Complex systems fail in spectacular ways. Failure isn't a question of if, but when. Resilient systems recover from failure; robust systems resist failure. Avoid single points of failure. Accept the fact that you have to build…

https://github.com/cloudera/flume/blob/master/flume-docs/src/docs/UserGuide/Introduction === Reliability       Reliability, the ability to continue delivering events in the face of   failures without losing data, is a vital feature of Flume. Large  …

Open source software has become a fundamental building block for some of the biggest websites. And as those websites have grown, best practices and guiding principles around their architectures have emerged. This chapter seeks to cover some of the ke…

转自:http://aosabook.org/en/distsys.html Scalable Web Architecture and Distributed Systems Kate Matsudaira Open source software has become a fundamental building block for someof the biggest websites. And as those websites have grown,best practices and…

A novel massively parallel supercomputer of hundreds of teraOPS-scale includes node architectures based upon System-On-a-Chip technology, i.e., each processing node comprises a single Application Specific Integrated Circuit (ASIC). Within each ASIC n…

http://www.onjava.com/pub/a/onjava/2001/05/30/optimization.htmlComparing the performance of LinkedLists and ArrayLists (and Vectors) (Page last updated May 2001, Added 2001-06-18, Author Jack Shirazi, Publisher OnJava). Tips: ArrayList is faster than…

backup of a database is a very important thing. If no backup, meet the following situation goes crazy: UPDATE or DELETE whitout where… table was DROPPed accidentally… INNODB was corrupt… entire datacenter loses power… Data from the safety point of vi…

https://msdn.microsoft.com/en-us/library/ff647787.aspx Retired Content This content is outdated and is no longer being maintained. It is provided as a courtesy for individuals who are still using these technologies. This page may contain URLs that we…

could accomplish with Flink back at Twitter. I had an application in mind that I knew I could make more efficient by a huge factor if I could use the stateful processing guarantees available in Flink so I set out to build a prototype to do exactly th…

A brief tour of some of the important components of a Google Datacenter.   A photo of the interior of a real Google Datacenter in North Carolina. Seen here are rows of racks containing machines. I am a Site Reliability Engineer at Google, annotating…