distributed computing software

Two . Distributed Computing ( Map/reduce )Distributed computing, too, is a broad concept, where it narrowly refers to a distributed framework designed by the Google Map/reduce framework. In Hadoop, distributed file systems, to a l

I have been engaged in distributed computing research and development, iveely computing is my work in the outside of the distributed computing framework, for large-scale cluster server, easy to use, pure Java development. Includes at least the following features:

1 , Parallel computingParallel computing or parallel computing is relative to serial computing. It is an algorithm that can execute multiple instructions at once to improve the computational speed and solve large and complex computational problems by enlarging the problem solving scale the so-called parallel computing

WordCount is the most commonly used example of distributed computing, such as Hadoop, storm,iveely computing, and so on. Understand the WordCount on the iveely computing on the operating principle, it is easy to write a new distributed program. I already know how to deploy i

Two. Distributed Computing (Map/reduce) Distributed computing is also a broad concept, where it is narrowly referred to as a distributed framework designed by the Google Map/reduce framework. In Hadoop, distributed file systems a

Improve system scalability through dynamic configuration and Reconfiguration Improve system performance and price ratio through Resource Sharing E. (potential) problems: Software requirements: suitable operating systems, distributed computing environments, programming languages, and Application Design Methods Communication Network: information loss, recove

Wang Jialin's in-depth case-driven practice of cloud computing distributed Big Data hadoop in July 6-7 in Shanghai Wang Jialin Lecture 4HadoopGraphic and text training course: Build a true practiceHadoopDistributed Cluster EnvironmentHadoopThe specific solution steps are as follows: Step 1: QueryHadoopTo see the cause of the error; Step 2: Stop the cluster; Step 3: Solve the Problem Based on the reas

When it comes to high concurrency, a lot of people think about distribution, so what's the difference? Concurrency and distribution are completely different concepts. Concurrency is reflected in the amount of time, such as video online live site, there may be tens of thousands of people need to access the server at the same time, this is concurrency. Distribution is to distribute tasks to different points, and distributed

ja16-large distributed integrated project combat Spring+zookeeper+mycat+storm+kafka+nio+netty distributed storage Cloud computing Video CourseThe beginning of the new year, learning to be early, drip records, learning is progress!Do not look everywhere, seize the promotion of their own.For learning difficulties do not know how to improve themselves can be added:

serverQueuemanger.register ("Get_result") Manger=queuemanger (address= ("192.168.112.11", 8848), authkey="123456") Manger.connect ()#Linked servertask=manger.get_task () result=manger.get_result ()#Tasks, Results # + #10 Processes #100 Threads #1000 x co-process forIinchRange (10): Cubelist= []#[[ [1],[2] ] forJinchRange (10): Arealist= [] forKinchRange (10): LineList= [] forLinchRange (10): Data=Task.get () linelist.append (data) arealist.app

/garvin/log.txt -Dflume.root.logger=INFO,consoleRecommend a few useful things:An example of a code implementation: Https://github.com/waqulianjie/odps_sinkDeveloper Document:http://flume.apache.org/flumeuserguide.htmlA more complete introduction: http://www.aboutyun.com/thread-8917-1-1.html This article comes from the blog "Bo Li Garvin"Reprint please indicate source: Http://blog.csdn.net/buptgshengod] Copyright NOTICE: This article for Bo Master original article, without Bo Maste