YARN-3169. Drop YARN's overview document. Contributed by Brahma Reddy Battula.
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</menu>
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<menu name="YARN" inherit="top">
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<item name="Overview" href="hadoop-yarn/hadoop-yarn-site/index.html"/>
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<item name="YARN Architecture" href="hadoop-yarn/hadoop-yarn-site/YARN.html"/>
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<item name="Capacity Scheduler" href="hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html"/>
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<item name="Fair Scheduler" href="hadoop-yarn/hadoop-yarn-site/FairScheduler.html"/>
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@ -189,6 +189,8 @@ Release 2.8.0 - UNRELEASED
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YARN-3523. Cleanup ResourceManagerAdministrationProtocol interface audience.
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(Naganarasimha G R via junping_du)
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YARN-3169. Drop YARN's overview document. (Brahma Reddy Battula via ozawa)
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OPTIMIZATIONS
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YARN-3339. TestDockerContainerExecutor should pull a single image and not
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@ -1,75 +0,0 @@
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<!---
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. See accompanying LICENSE file.
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-->
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MapReduce NextGen aka YARN aka MRv2
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===================================
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The new architecture introduced in hadoop-0.23, divides the two major functions of the JobTracker: resource management and job life-cycle management into separate components.
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The new ResourceManager manages the global assignment of compute resources to applications and the per-application ApplicationMaster manages the application’s scheduling and coordination.
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An application is either a single job in the sense of classic MapReduce jobs or a DAG of such jobs.
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The ResourceManager and per-machine NodeManager daemon, which manages the user processes on that machine, form the computation fabric.
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The per-application ApplicationMaster is, in effect, a framework specific library and is tasked with negotiating resources from the ResourceManager and working with the NodeManager(s) to execute and monitor the tasks.
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More details are available in the [Architecture](./YARN.html) document.
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Documentation Index
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===================
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YARN
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----
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* [YARN Architecture](./YARN.html)
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* [Capacity Scheduler](./CapacityScheduler.html)
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* [Fair Scheduler](./FairScheduler.html)
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* [ResourceManager Restart](./ResourceManagerRestart.htaml)
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* [ResourceManager HA](./ResourceManagerHA.html)
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* [Web Application Proxy](./WebApplicationProxy.html)
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* [YARN Timeline Server](./TimelineServer.html)
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* [Writing YARN Applications](./WritingYarnApplications.html)
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* [YARN Commands](./YarnCommands.html)
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* [Scheduler Load Simulator](#hadoop-slsSchedulerLoadSimulator.html)
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* [NodeManager Restart](./NodeManagerRestart.html)
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* [DockerContainerExecutor](./DockerContainerExecutor.html)
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* [Using CGroups](./NodeManagerCGroups.html)
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* [Secure Containers](./SecureContainer.html)
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* [Registry](./registry/index.html)
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YARN REST APIs
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--------------
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* [Introduction](./WebServicesIntro.html)
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* [Resource Manager](./ResourceManagerRest.html)
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* [Node Manager](./NodeManagerRest.html)
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