MAPREDUCE-3099. Add docs for setting up a single node MRv2 cluster. (mahadev) - Merging r1176607 from trunk
git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/branches/branch-0.23@1176610 13f79535-47bb-0310-9956-ffa450edef68
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@ -289,6 +289,9 @@ Release 0.23.0 - Unreleased
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MAPREDUCE-3092. Removed a special comparator for JobIDs in JobHistory as
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JobIDs are already comparable. (Devaraj K via vinodkv)
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MAPREDUCE-3099. Add docs for setting up a single node MRv2 cluster.
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(mahadev)
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OPTIMIZATIONS
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MAPREDUCE-2026. Make JobTracker.getJobCounters() and
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@ -0,0 +1,180 @@
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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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~~
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~~ http://www.apache.org/licenses/LICENSE-2.0
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~~
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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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Hadoop MapReduce Next Generation ${project.version} - Setting up a Single Node Cluster.
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---
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---
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${maven.build.timestamp}
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Hadoop MapReduce Next Generation - Setting up a Single Node Cluster.
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\[ {{{./index.html}Go Back}} \]
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* Mapreduce Tarball
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You should be able to obtain the MapReduce tarball from the release.
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If not, you should be able to create a tarball from the source.
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+---+
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$ mvn clean install -DskipTests
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$ cd hadoop-mapreduce-project
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$ mvn clean install assembly:assembly
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+---+
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<<NOTE:>> You will need protoc installed of version 2.4.1 or greater.
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To ignore the native builds in mapreduce you can use <<<-P-cbuild>>> argument
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for maven. The tarball should be available in <<<target/>>> directory.
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* Setting up the environment.
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Assuming you have installed hadoop-common/hadoop-hdfs and exported
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<<$HADOOP_COMMON_HOME>>/<<$HADOOP_COMMON_HOME>>, untar hadoop mapreduce
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tarball and set environment variable <<$HADOOP_MAPRED_HOME>> to the
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untarred directory. Set <<$YARN_HOME>> the same as <<$HADOOP_MAPRED_HOME>>.
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<<NOTE:>> The following instructions assume you have hdfs running.
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* Setting up Configuration.
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To start the ResourceManager and NodeManager, you will have to update the configs.
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Assuming your $HADOOP_CONF_DIR is the configuration directory and has the installed
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configs for HDFS and <<<core-site.xml>>>. There are 2 config files you will have to setup
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<<<mapred-site.xml>>> and <<<yarn-site.xml>>>.
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** Setting up <<<mapred-site.xml>>>
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Add the following configs to your <<<mapred-site.xml>>>.
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+---+
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<property>
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<name>mapreduce.cluster.temp.dir</name>
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<value></value>
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<description>No description</description>
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<final>true</final>
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</property>
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<property>
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<name>mapreduce.cluster.local.dir</name>
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<value></value>
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<description>No description</description>
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<final>true</final>
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</property>
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+---+
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** Setting up <<<yarn-site.xml>>>
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Add the following configs to your <<<yarn-site.xml>>>
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+---+
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<property>
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<name>yarn.resourcemanager.resource-tracker.address</name>
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<value>host:port</value>
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<description>host is the hostname of the resource manager and
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port is the port on which the NodeManagers contact the Resource Manager.
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</description>
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</property>
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<property>
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<name>yarn.resourcemanager.scheduler.address</name>
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<value>host:port</value>
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<description>host is the hostname of the resourcemanager and port is the port
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on which the Applications in the cluster talk to the Resource Manager.
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</description>
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</property>
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<property>
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<name>yarn.resourcemanager.scheduler.class</name>
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<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value>
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<description>In case you do not want to use the default scheduler</description>
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</property>
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<property>
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<name>yarn.resourcemanager.address</name>
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<value>host:port</value>
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<description>the host is the hostname of the ResourceManager and the port is the port on
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which the clients can talk to the Resource Manager. </description>
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</property>
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<property>
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<name>yarn.nodemanager.local-dirs</name>
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<value></value>
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<description>the local directories used by the nodemanager</description>
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</property>
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<property>
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<name>yarn.nodemanager.address</name>
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<value>0.0.0.0:port</value>
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<description>the nodemanagers bind to this port</description>
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</property>
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<property>
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<name>yarn.nodemanager.resource.memory-gb</name>
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<value>10</value>
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<description>the amount of memory on the NodeManager in GB</description>
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</property>
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<property>
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<name>yarn.nodemanager.remote-app-log-dir</name>
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<value>/app-logs</value>
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<description>directory on hdfs where the application logs are moved to </description>
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</property>
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<property>
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<name>yarn.nodemanager.log-dirs</name>
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<value></value>
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<description>the directories used by Nodemanagers as log directories</description>
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</property>
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<property>
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<name>yarn.nodemanager.aux-services</name>
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<value>mapreduce.shuffle</value>
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<description>shuffle service that needs to be set for Map Reduce to run </description>
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</property>
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+---+
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* Create Symlinks.
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You will have to create the following symlinks:
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+---+
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$ cd $HADOOP_COMMON_HOME/share/hadoop/common/lib/
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-mapreduce-client-app-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-mapreduce-client-jobclient-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-mapreduce-client-common-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-mapreduce-client-shuffle-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-mapreduce-client-core-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-yarn-common-*-SNAPSHOT.jar .
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$ ln -s $HADOOP_MAPRED_HOME/modules/hadoop-yarn-api-*-SNAPSHOT.jar .
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+---+
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* Running daemons.
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Assuming that the environment variables <<$HADOOP_COMMON_HOME>>, <<$HADOOP_HDFS_HOME>>, <<$HADOO_MAPRED_HOME>>,
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<<$YARN_HOME>>, <<$JAVA_HOME>> and <<$HADOOP_CONF_DIR>> have been set appropriately.
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Set $<<$YARN_CONF_DIR>> the same as $<<HADOOP_CONF_DIR>>
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Run ResourceManager and NodeManager as:
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+---+
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$ cd $HADOOP_MAPRED_HOME
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$ bin/yarn-daemon.sh start resourcemanager
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$ bin/yarn-daemon.sh start nodemanager
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+---+
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You should be up and running. You can run randomwriter as:
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+---+
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$ $HADOOP_COMMON_HOME/bin/hadoop jar hadoop-examples.jar randomwriter out
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+---+
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Good luck.
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@ -0,0 +1,39 @@
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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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~~
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~~ http://www.apache.org/licenses/LICENSE-2.0
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~~
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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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||||
Hadoop MapReduce Next Generation ${project.version}
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||||
---
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---
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${maven.build.timestamp}
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Hadoop MapReduce Next Generation
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* Architecture
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The new architecture introduced in 0.23, divides the two major functions
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of the JobTracker, resource management and job scheduling/monitoring, into separate
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components.
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The new ResourceManager manages the global assignment of compute resources to applications
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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 classic MapReduce jobs or a DAG of such jobs.
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The ResourceManager and per-machine NodeManager server, which manages the user processes on that
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machine, form the computation fabric. The per-application ApplicationMaster is, in effect, a
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framework specific library and is tasked with negotiating resources from the ResourceManager
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and working with the NodeManager(s) to execute and monitor the tasks.
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* User Documentation
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* {{{./SingleCluster.html}SingleCluster}}
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* {{{./apidocs/index.html}JavaDocs}}
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@ -0,0 +1,34 @@
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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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<project name="Hadoop MapReduce Next Gen">
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<version position="right"/>
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<bannerLeft>
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<name> </name>
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</bannerLeft>
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<skin>
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<groupId>org.apache.maven.skins</groupId>
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<artifactId>maven-stylus-skin</artifactId>
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<version>1.1</version>
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</skin>
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<body>
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<links>
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<item name="Apache Hadoop" href="http://hadoop.apache.org/"/>
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</links>
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</body>
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</project>
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