hadoop jobs salary

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parameters following jar are shown here; RunJar: the function of this class is relatively simple. Extract the jar file"Hadoop. tmp. dir"Directory, and then execute the class we specified.Myorg. WordCount For a complete analysis of p.s. hadoop scripts, see After RunJar executes WordCount, it enters our program. You need to configure mapper, reducer, and output path, and finally submit this job to JobTrac

Today, some classmates asked me, how to kill the user to make all the job, there is no ready-made command? I looked at the prompt for the Hadoop job command, and there was no such command.In fact, the implementation of the kill specified user's job is also very simple, the Hadoop job command itself has a lot of practical job management functions.List all the jobs

) ; Job.setmapoutputvalueclass (longwritable.class);//1.3 partition, the following two lines of code write and not write the same, the default settings2.1 Transfer the data to the corresponding reducer//2.2 using the custom Reducer class action//Settings Reducer class Job.setreducerclass (Jreducer.class);//Set reducer after processing The data type of the output key-value pair Job.setoutputkeyclass (text.class); Job.setoutputvalueclass (longwritable.class);//2.3 outputs the result// Fileoutputfo

configuration ();Configuration conditionalprobilityjobconf = new configuration ();Configuration predictjobconf = new configuration ();...//Set individual configurationCreate a Job object. Note that the Jobcontrol requires that the job must be encapsulated as a jobs objectJob Extractjob = new Job (extractjobconf);Job Classpriorjob = new Job (classpriorjobconf);Job Conditionalprobilityjob = new Job (conditionalprobilityjobconf);Job Predictjob = new Job

Import Java.io.ioexception;import Java.util.stringtokenizer;import Org.apache.hadoop.conf.configuration;import Org.apache.hadoop.fs.path;import Org.apache.hadoop.io.text;import Org.apache.hadoop.mapreduce.job;import Org.apache.hadoop.mapreduce.mapper;import Org.apache.hadoop.mapreduce.reducer;import Org.apache.hadoop.mapreduce.lib.input.fileinputformat;import Org.apache.hadoop.mapreduce.lib.input.FileSplit; Import Org.apache.hadoop.mapreduce.lib.output.fileoutputformat;public class Invertedindex

(Text.class); Job.setmapoutputvalueclass (Longwritable.class); Job.setreducerclass (Jreducer.class); Job.setoutputkeyclass (Text.class); Job.setoutputvalueclass ( Longwritable.class); Fileoutputformat.setoutputpath (Job, Outpath); Job.setoutputformat (textoutputformat.class);// Use Jobclient.runjob instead of job.waitForCompletionJobClient.runJob (job);}}Can seeIn fact, the old version of the API is not very different, just a few classes replaced itNote that the old version of the API class is

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