Oozie調度MapReduce任務

1. 在/usr/local/module/oozie-4.0.0-cdh5.3.6/oozie-apps目錄下創建map-reduce目錄
    
2. /usr/local/module/oozie-4.0.0-cdh5.3.6/oozie-apps/map-reduce下創建job.properties,workflow.xml文件，
   以及lib文件夾
   
3. 將/usr/local/module/hadoop-cdh5.3.6/hadoop-2.5.0-cdh5.3.6/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.5.0-cdh5.3.6.jar拷貝到lib目錄下
    
4. 配置workflow.xml文件
    

   <!--
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     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
     
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   -->
   <workflow-app xmlns="uri:oozie:workflow:0.2" name="map-reduce-wf">
       <start to="mr-node"/>
       <action name="mr-node">
           <map-reduce>
               <job-tracker>${jobTracker}</job-tracker>
               <name-node>${nameNode}</name-node>
               <prepare>
   				<!--對應的是hdfs上/output1目錄,存在的話要先刪除-->
                   <delete path="${nameNode}/output1"/>
               </prepare>
               <configuration>
                   <property>
                       <name>mapred.job.queue.name</name>
                       <value>${queueName}</value>
                   </property>
   				<!-- 配置調度MR任務時，使用新的API -->
                   <property>
                       <name>mapred.mapper.new-api</name>
                       <value>true</value>
                   </property>
   
                   <property>
                       <name>mapred.reducer.new-api</name>
                       <value>true</value>
                   </property>
   
   				<!-- 指定Map類 -->
                   <property>
                       <name>mapreduce.job.map.class</name>
                       <value>org.apache.hadoop.examples.WordCount$TokenizerMapper</value>
                   </property>
   				 <!-- 指定Reduce類 -->
                   <property>
                       <name>mapreduce.job.reduce.class</name>
                       <value>org.apache.hadoop.examples.WordCount$IntSumReducer</value>
                   </property>
   				 <!-- 指定Job Key輸出類型 -->
                   <property>
                       <name>mapreduce.job.output.key.class</name>
                       <value>org.apache.hadoop.io.Text</value>
                   </property>
   
                   <!-- 指定Job Value輸出類型 -->
                   <property>
                       <name>mapreduce.job.output.value.class</name>
                       <value>org.apache.hadoop.io.IntWritable</value>
                   </property>
   
                   <property>
                       <name>mapred.map.tasks</name>
                       <value>1</value>
                   </property>
   				<!-- 指定輸入輸出路徑 -->
                   <property>
                       <name>mapreduce.input.fileinputformat.inputdir</name>
                       <value>/input1</value>
                   </property>
                   <property>
                       <name>mapreduce.output.fileoutputformat.outputdir</name>
                       <value>/output1</value>
                   </property>
               </configuration>
           </map-reduce>
           <ok to="end"/>
           <error to="fail"/>
       </action>
       <kill name="fail">
           <message>Map/Reduce failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
       </kill>
       <end name="end"/>
   </workflow-app>
   

    

5. 修改job.properties文件
    

   nameNode=hdfs://hadoop111:8020
   jobTracker=hadoop112:8032
   queueName=default
   examplesRoot=oozie-apps
   oozie.wf.application.path=${nameNode}/user/${user.name}/${examplesRoot}/map-reduce/workflow.xml
   
   

    

6. 將文件上傳到HDFS上
    
7. 執行
    
8. 效果
    
    
9. 查看HDFS上輸入和生成的輸出文件