1、将mapred-site.xml文件拷贝一份到项目中
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<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapred.child.java.opts</name> <value>-Xmx800m -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=y,address=8000</value> </property> <property> <name>mapreduce.jobtracker.staging.root.dir</name> <value>/tmp</value> </property> <property> <name>yarn.app.mapreduce.am.staging-dir</name> <value>/tmp</value> </property> <property> <name>mapreduce.framework.name</name> <value>local</value> </property> <property> <name>mapreduce.jobtracker.address</name> <value>local</value> </property><property><name>mapred.job.tracker</name><value>local</value></property></configuration> |
2、在项目中加入本地mapred-site.xml配置，从本地项目中读取配置文件运行，在reduce中debug
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Job job = new Job(conf, "word count"); conf.addResource("classpath:/Hadoop01/mapred-site.xml"); conf.set("fs.defaultFS", "hdfs://192.168.1.10:9008"); conf.set("mapreduce.framework.name", "yarn"); conf.set("yarn.resourcemanager.address", "192.168.1.10:8032"); conf.set("mapred.remote.os", "Linux"); conf.set("hadoop.job.ugi", "hadoop,hadoop"); |