a44ffcc0be
git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/trunk@1161736 13f79535-47bb-0310-9956-ffa450edef68
99 lines
3.6 KiB
Plaintext
99 lines
3.6 KiB
Plaintext
To compile Hadoop Mapreduce next following, do the following:
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Step 1) Install dependencies for yarn
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See http://svn.apache.org/repos/asf/hadoop/common/trunk/hadoop-mapreduce/hadoop-yarn/README
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Make sure protbuf library is in your library path or set: export LD_LIBRARY_PATH=/usr/local/lib
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Step 2) Checkout
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svn checkout http://svn.apache.org/repos/asf/hadoop/common/trunk
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Step 3) Build common
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Go to common directory - choose your regular common build command
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Example: mvn clean install package -Pbintar -DskipTests
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Step 4) Build HDFS
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Go to hdfs directory
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ant veryclean mvn-install -Dresolvers=internal
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Step 5) Build yarn and mapreduce
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Go to mapreduce directory
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export MAVEN_OPTS=-Xmx512m
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mvn clean install assembly:assembly -DskipTests
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Copy in build.properties if appropriate - make sure eclipse.home not set
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ant veryclean tar -Dresolvers=internal
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You will see a tarball in
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ls target/hadoop-mapreduce-0.24.0-SNAPSHOT-all.tar.gz
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Step 6) Untar the tarball in a clean and different directory.
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say YARN_HOME.
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Make sure you aren't picking up avro-1.3.2.jar, remove:
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$HADOOP_COMMON_HOME/share/hadoop/common/lib/avro-1.3.2.jar
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$YARN_HOME/lib/avro-1.3.2.jar
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Step 7)
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Install hdfs/common and start hdfs
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To run Hadoop Mapreduce next applications:
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Step 8) export the following variables to where you have things installed:
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You probably want to export these in hadoop-env.sh and yarn-env.sh also.
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export HADOOP_MAPRED_HOME=<mapred loc>
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export HADOOP_COMMON_HOME=<common loc>
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export HADOOP_HDFS_HOME=<hdfs loc>
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export YARN_HOME=directory where you untarred yarn
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export HADOOP_CONF_DIR=<conf loc>
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export YARN_CONF_DIR=$HADOOP_CONF_DIR
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Step 9) Setup config: for running mapreduce applications, which now are in user land, you need to setup nodemanager with the following configuration in your yarn-site.xml before you start the nodemanager.
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<property>
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<name>nodemanager.auxiluary.services</name>
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<value>mapreduce.shuffle</value>
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</property>
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<property>
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<name>nodemanager.aux.service.mapreduce.shuffle.class</name>
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<value>org.apache.hadoop.mapred.ShuffleHandler</value>
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</property>
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Step 10) Modify mapred-site.xml to use yarn framework
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<property>
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<name> mapreduce.framework.name</name>
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<value>yarn</value>
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</property>
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Step 11) Create the following symlinks in $HADOOP_COMMON_HOME/share/hadoop/common/lib
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ln -s $YARN_HOME/modules/hadoop-mapreduce-client-app-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-yarn-api-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-mapreduce-client-common-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-yarn-common-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-mapreduce-client-core-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-yarn-server-common-0.24.0-SNAPSHOT.jar .
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ln -s $YARN_HOME/modules/hadoop-mapreduce-client-jobclient-0.24.0-SNAPSHOT.jar .
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Step 12) cd $YARN_HOME
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Step 13) bin/yarn-daemon.sh start resourcemanager
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Step 14) bin/yarn-daemon.sh start nodemanager
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Step 15) bin/yarn-daemon.sh start historyserver
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Step 16) You are all set, an example on how to run a mapreduce job is:
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cd $HADOOP_MAPRED_HOME
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ant examples -Dresolvers=internal
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$HADOOP_COMMON_HOME/bin/hadoop jar $HADOOP_MAPRED_HOME/build/hadoop-mapreduce-examples-0.24.0-SNAPSHOT.jar randomwriter -Dmapreduce.job.user.name=$USER -Dmapreduce.clientfactory.class.name=org.apache.hadoop.mapred.YarnClientFactory -Dmapreduce.randomwriter.bytespermap=10000 -Ddfs.blocksize=536870912 -Ddfs.block.size=536870912 -libjars $YARN_HOME/modules/hadoop-mapreduce-client-jobclient-0.24.0-SNAPSHOT.jar output
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The output on the command line should be almost similar to what you see in the JT/TT setup (Hadoop 0.20/0.21)
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