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hadoop2.4-single

2024-07-07 09:51:53   225人阅读

(1)机器免登录
ssh-keygen -t rsa
cd ~/.ssh/
cat id_rsa.pub >> authorized_keys
chmod 600 authorized_keys
[tip].ssh目录的权限必须是700
[tip].ssh/authorized_keys文件权限必须是600

(2)修改配置
cp mapred-site.xml.template mapred-site.xml
vi mapred-site.xml
    <property>
                <name>mapreduce.framework.name</name>
                <value>yarn</value>
        </property>

vi core-site.xml
    <property>
                <name>fs.default.name</name>
                <value>hdfs://localhost:9000</value>
        </property>

vi yarn-site.xml
    <property>
        <!--注意这里是中划线-->
                <name>yarn.nodemanager.aux-services</name>
        <!--注意这里是下划线,否则会报名称不符合规范-->
                <value>mapreduce_shuffle</value>                                  
        </property>

vi hdfs-site.xml
    <property>
                <name>dfs.replication</name>
                <value>1</value>
        </property>

        <property>
                <name>dfs.namenode.name.dir</name>
                <value>file:/home/hadoop/data/yarn/hdfs/namenode</value>
        </property>

        <property>
                <name>dfs.datanode.data.dir</name>
                <value>file:/home/hadoop/data/yarn/hdfs/datanode</value>
        </property>


vi ~/.bashrc
#Hadoop2
export HADOOP_HOME=/home/hadoop/soft/hadoop-2.4.0
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export PATH=$PATH:$HADOOP_HOME/bin

source ~/.bashrc

(3)启动
hadoop namenode -format
sh sbin/start-all.sh

[查看节点]
http://localhost:50070/
[查看任务]
http://localhost:8088/

(4)运行示例

在示例的源码包里有一个类叫

hadoop-2.4.0-src/hadoop-mapreduce-project/hadoop-mapreduce-examples/src/main/java/org/apache/hadoop/examples/ExampleDriver.java

它是程序的入口

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/**
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 
package org.apache.hadoop.examples;
 
import org.apache.hadoop.examples.dancing.DistributedPentomino;
import org.apache.hadoop.examples.dancing.Sudoku;
import org.apache.hadoop.examples.pi.DistBbp;
import org.apache.hadoop.examples.terasort.TeraGen;
import org.apache.hadoop.examples.terasort.TeraSort;
import org.apache.hadoop.examples.terasort.TeraValidate;
import org.apache.hadoop.util.ProgramDriver;
 
/**
 * A description of an example program based on its class and a
 * human-readable description.
 */
public class ExampleDriver {
   
  public static void main(String argv[]){
    int exitCode = -1;
    ProgramDriver pgd = new ProgramDriver();
    try {
      pgd.addClass("wordcount", WordCount.class,
                   "A map/reduce program that counts the words in the input files.");
      pgd.addClass("wordmean", WordMean.class,
                   "A map/reduce program that counts the average length of the words in the input files.");
      pgd.addClass("wordmedian", WordMedian.class,
                   "A map/reduce program that counts the median length of the words in the input files.");
      pgd.addClass("wordstandarddeviation", WordStandardDeviation.class,
                   "A map/reduce program that counts the standard deviation of the length of the words in the input files.");
      pgd.addClass("aggregatewordcount", AggregateWordCount.class,
                   "An Aggregate based map/reduce program that counts the words in the input files.");
      pgd.addClass("aggregatewordhist", AggregateWordHistogram.class,
                   "An Aggregate based map/reduce program that computes the histogram of the words in the input files.");
      pgd.addClass("grep", Grep.class,
                   "A map/reduce program that counts the matches of a regex in the input.");
      pgd.addClass("randomwriter", RandomWriter.class,
                   "A map/reduce program that writes 10GB of random data per node.");
      pgd.addClass("randomtextwriter", RandomTextWriter.class,
      "A map/reduce program that writes 10GB of random textual data per node.");
      pgd.addClass("sort", Sort.class, "A map/reduce program that sorts the data written by the random writer.");
 
      pgd.addClass("pi", QuasiMonteCarlo.class, QuasiMonteCarlo.DESCRIPTION);
      pgd.addClass("bbp", BaileyBorweinPlouffe.class, BaileyBorweinPlouffe.DESCRIPTION);
      pgd.addClass("distbbp", DistBbp.class, DistBbp.DESCRIPTION);
 
      pgd.addClass("pentomino", DistributedPentomino.class,
      "A map/reduce tile laying program to find solutions to pentomino problems.");
      pgd.addClass("secondarysort", SecondarySort.class,
                   "An example defining a secondary sort to the reduce.");
      pgd.addClass("sudoku", Sudoku.class, "A sudoku solver.");
      pgd.addClass("join", Join.class, "A job that effects a join over sorted, equally partitioned datasets");
      pgd.addClass("multifilewc", MultiFileWordCount.class, "A job that counts words from several files.");
      pgd.addClass("dbcount", DBCountPageView.class, "An example job that count the pageview counts from a database.");
      pgd.addClass("teragen", TeraGen.class, "Generate data for the terasort");
      pgd.addClass("terasort", TeraSort.class, "Run the terasort");
      pgd.addClass("teravalidate", TeraValidate.class, "Checking results of terasort");
      exitCode = pgd.run(argv);
    }
    catch(Throwable e){
      e.printStackTrace();
    }
     
    System.exit(exitCode);
  }
}

hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.4.0.jar pi 5 10

[默认配置的话运行输出会有这么一句]
running in uber mode : false 

运行分本地模式 uber mode  和 no-uber mode  
uber mode对于小作业共享container - MapTask,ReduceTask会使用MRAppMaster所在的container

 


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