sublime yarn

HA-Federation-HDFS + Yarn cluster deployment mode After an afternoon's attempt, I finally set up the cluster, and it didn't feel much necessary to complete the setup. So I should study it and lay the foundation for building the real environment. The following is a cluster deployment of Ha-Federation-hdfs + Yarn. First, let's talk about my Configuration: The four nodes are started respectively: 1. bkjia117:

The Hadoop project that I did before was based on the 0.20.2 version, looked up the data and learned that it was the original Map/reduce model.Official Note:1.1.x-current stable version, 1.1 release1.2.x-current beta version, 1.2 release2.x.x-current Alpha version0.23.x-simmilar to 2.x.x but missing NN HA.0.22.x-does not include security0.20.203.x-old Legacy Stable Version0.20.x-old Legacy VersionDescription0.20/0.22/1.1/CDH3 Series, original Map/reduce model, stable version0.23/2.X/CDH4 series,

Learn the difference between mapreduceV1 (previous mapreduce) and mapreduceV2 (YARN) We need to understand MapreduceV1 's working mechanism and design ideas first.First, take a look at the operation diagram of the MapReduce V1The components and functions of the MapReduce V1 are:Client: Clients, responsible for writing MapReduce code and configuring and submitting jobs.Jobtracker: Is the core of the entire MapReduce framework, similar to the Dispatcher

, NodeManager:Is the framework agent on each node, primarily responsible for launching the containers required by the application, monitoring the use of resources (memory, CPU, disk, network, etc.) and reporting them to the scheduler.3, Applicaionmanager:It is primarily responsible for receiving jobs , negotiating to get the first container to perform applicationmaster and providing services to restart failed AM container.4, Applicationmaster:Responsible for all work within a job life cycle, sim

Yarn's shell operation and management 7.1 starting yarnYarn has 2 daemon threads: ResourceManager, NodeManager.[[email protected] hadoop-2.2.0] $sbin/yarn-daemon.sh start ResourceManager[[email protected] hadoop-2.2.0] $sbin/yarn-daemon.sh start NodeManager7.2YARN Web Management interfaceYarn Management Address:ResourceManager: Host name:8088 . In this environment: http://hadoop-yarn.dragon.org:8088Nameno

Configuration recommendations: 1.In MR1, The mapred. tasktracker. Map. Tasks. Maximum and mapred. tasktracker. Reduce. Tasks. Maximum properties dictated how many map and reduce slots each tasktracker had. These properties no longer exist in yarn. instead, yarn uses yarn. nodemanager. resource. memory-MB and yarn. nod

Introduced The Apache Hadoop yarn is added to the Hadoop Common (core libraries) as a subproject of Hadoop, Hadoop HDFS (storage) and Hadoop MapReduce (the MapReduce implementation), it is also the top project of Apache. In Hadoop 2.0, each client submits various MapReduce applications to the MapReduce V2 framework running on yarn. In Hadoop 1.0, each client submits a maprecude application to the MapReduc

Set up CDH and run the example program Word-count. The map 0% reduce 0% is always displayed on the console interface, and the job status is run on the web page, but the map is not executed. It seems that there is a problem with resource allocation. Then you can view the task log. 2014-07-0417:30:37,492INFO[RMCommunicatorAllocator]org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator:Recalculatingschedule,headroom=02014-07-0417:30:37,492INFO[RMCommunicatorAllocator]org.apache.hadoop.mapredu

Site:http://hadoop.apache.org/docs/r2.6.0/hadoop-yarn/hadoop-yarn-site/yarn.htmlYarn structure diagram is as follows:1. YarnThe next generation of the MapReduce system framework, also known as MRV2 (MapReduce version 2), is a generic resource management system that provides unified resource management and scheduling for upper-level applications.The basic idea of yarn