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Java JobConf.setMaxMapAttempts方法代碼示例

本文整理匯總了Java中org.apache.hadoop.mapred.JobConf.setMaxMapAttempts方法的典型用法代碼示例。如果您正苦於以下問題:Java JobConf.setMaxMapAttempts方法的具體用法?Java JobConf.setMaxMapAttempts怎麽用?Java JobConf.setMaxMapAttempts使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在org.apache.hadoop.mapred.JobConf的用法示例。


在下文中一共展示了JobConf.setMaxMapAttempts方法的3個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: runTests

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
/**
 * Run the test
 * 
 * @throws IOException on error
 */
public static void runTests() throws IOException {
  config.setLong("io.bytes.per.checksum", bytesPerChecksum);
  
  JobConf job = new JobConf(config, NNBench.class);

  job.setJobName("NNBench-" + operation);
  FileInputFormat.setInputPaths(job, new Path(baseDir, CONTROL_DIR_NAME));
  job.setInputFormat(SequenceFileInputFormat.class);
  
  // Explicitly set number of max map attempts to 1.
  job.setMaxMapAttempts(1);
  
  // Explicitly turn off speculative execution
  job.setSpeculativeExecution(false);

  job.setMapperClass(NNBenchMapper.class);
  job.setReducerClass(NNBenchReducer.class);

  FileOutputFormat.setOutputPath(job, new Path(baseDir, OUTPUT_DIR_NAME));
  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(Text.class);
  job.setNumReduceTasks((int) numberOfReduces);
  JobClient.runJob(job);
}
 
開發者ID:naver,項目名稱:hadoop,代碼行數:30,代碼來源:NNBench.java

示例2: runJobFail

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
public static void runJobFail(JobConf conf, Path inDir, Path outDir)
       throws IOException, InterruptedException {
  conf.setJobName("test-job-fail");
  conf.setMapperClass(FailMapper.class);
  conf.setJarByClass(FailMapper.class);
  conf.setReducerClass(IdentityReducer.class);
  conf.setMaxMapAttempts(1);
  
  boolean success = runJob(conf, inDir, outDir, 1, 0);
  Assert.assertFalse("Job expected to fail succeeded", success);
}
 
開發者ID:naver,項目名稱:hadoop,代碼行數:12,代碼來源:TestMROldApiJobs.java

示例3: submitAsMapReduce

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
/**
 * Based on args we submit the LoadGenerator as MR job.
 * Number of MapTasks is numMapTasks
 * @return exitCode for job submission
 */
private int submitAsMapReduce() {
  
  System.out.println("Running as a MapReduce job with " + 
      numMapTasks + " mapTasks;  Output to file " + mrOutDir);


  Configuration conf = new Configuration(getConf());
  
  // First set all the args of LoadGenerator as Conf vars to pass to MR tasks

  conf.set(LG_ROOT , root.toString());
  conf.setInt(LG_MAXDELAYBETWEENOPS, maxDelayBetweenOps);
  conf.setInt(LG_NUMOFTHREADS, numOfThreads);
  conf.set(LG_READPR, readProbs[0]+""); //Pass Double as string
  conf.set(LG_WRITEPR, writeProbs[0]+""); //Pass Double as string
  conf.setLong(LG_SEED, seed); //No idea what this is
  conf.setInt(LG_NUMMAPTASKS, numMapTasks);
  if (scriptFile == null && durations[0] <=0) {
    System.err.println("When run as a MapReduce job, elapsed Time or ScriptFile must be specified");
    System.exit(-1);
  }
  conf.setLong(LG_ELAPSEDTIME, durations[0]);
  conf.setLong(LG_STARTTIME, startTime); 
  if (scriptFile != null) {
    conf.set(LG_SCRIPTFILE , scriptFile);
  }
  conf.set(LG_FLAGFILE, flagFile.toString());
  
  // Now set the necessary conf variables that apply to run MR itself.
  JobConf jobConf = new JobConf(conf, LoadGenerator.class);
  jobConf.setJobName("NNLoadGeneratorViaMR");
  jobConf.setNumMapTasks(numMapTasks);
  jobConf.setNumReduceTasks(1); // 1 reducer to collect the results

  jobConf.setOutputKeyClass(Text.class);
  jobConf.setOutputValueClass(IntWritable.class);

  jobConf.setMapperClass(MapperThatRunsNNLoadGenerator.class);
  jobConf.setReducerClass(ReducerThatCollectsLGdata.class);

  jobConf.setInputFormat(DummyInputFormat.class);
  jobConf.setOutputFormat(TextOutputFormat.class);
  
  // Explicitly set number of max map attempts to 1.
  jobConf.setMaxMapAttempts(1);
  // Explicitly turn off speculative execution
  jobConf.setSpeculativeExecution(false);

  // This mapReduce job has no input but has output
  FileOutputFormat.setOutputPath(jobConf, new Path(mrOutDir));

  try {
    JobClient.runJob(jobConf);
  } catch (IOException e) {
    System.err.println("Failed to run job: " + e.getMessage());
    return -1;
  }
  return 0;
  
}
 
開發者ID:naver,項目名稱:hadoop,代碼行數:66,代碼來源:LoadGeneratorMR.java


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