Examples of org.apache.hadoop.mapreduce.Job.waitForCompletion()

org.apache.hadoop.mapreduce.Job.waitForCompletion()
Submit the job to the cluster and wait for it to finish. @param verbose print the progress to the user @return true if the job succeeded @throws IOException thrown if the communication with the JobTracker is lost

            // Gotcha -- this has to run before the definitions above associated with the output format because
            // this is going to be configured against the job as it stands a moment from now


            job.setOutputFormatClass(TextOutputFormat.class);


            return job.waitForCompletion(true) ? 0 : 1;
        } catch(Main.IncorrectUsageException iue) {
            return 2;
        }
    }

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            // Gotcha -- this has to run before the definitions above associated with the output format because
            // this is going to be configured against the job as it stands a moment from now


            job.setOutputFormatClass(TextOutputFormat.class);


            return job.waitForCompletion(true) ? 0 : 1;
        } catch(Main.IncorrectUsageException iue) {
            return 2;
        }
    }

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        LOG.info(MessageFormat.format("Applying patch: {0} / {1} -> {2}",
                storage.getPatchContents("*"),
                storage.getHeadContents("*"),
                getNextContents()));
        try {
            boolean succeed = job.waitForCompletion(true);
            LOG.info(MessageFormat.format("Applied patch: succeed={0}, {1} / {2} -> {3}",
                    succeed,
                    storage.getPatchContents("*"),
                    storage.getHeadContents("*"),
                    getNextContents()));

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        LOG.info(MessageFormat.format("Applying patch: {0} / (empty) -> {2}",
                storage.getPatchContents("*"),
                storage.getHeadContents("*"),
                getNextContents()));
        try {
            boolean succeed = job.waitForCompletion(true);
            LOG.info(MessageFormat.format("Applied patch: succeed={0}, {1} / (empty) -> {3}",
                    succeed,
                    storage.getPatchContents("*"),
                    storage.getHeadContents("*"),
                    getNextContents()));

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            ConfigHelper.setPartitioner(job.getConfiguration(), "org.apache.cassandra.dht.RandomPartitioner");
            ConfigHelper.setInputColumnFamily(job.getConfiguration(), KEYSPACE, COLUMN_FAMILY);
            SlicePredicate predicate = new SlicePredicate().setColumn_names(Arrays.asList(ByteBufferUtil.bytes(columnName)));
            ConfigHelper.setInputSlicePredicate(job.getConfiguration(), predicate);


            job.waitForCompletion(true);
        }
        return 0;
    }
}

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    for (int i = 0; i < otherArgs.length - 1; ++i) {
      FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
    }
    FileOutputFormat.setOutputPath(job,
      new Path(otherArgs[otherArgs.length - 1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

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    job.setInputFormatClass(TextInputFormat.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    
    // run the job
    job.waitForCompletion(true);
    
    return parseOutput(job);
  }
  
  /**

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    FileSystem dfs = FileSystem.get(outPath.toUri(), conf);
    if (dfs.exists(outPath)) {
      dfs.delete(outPath, true);
    }
    job.waitForCompletion(true);
  }
  
  /**
   * Group the given Features into g groups as defined by the numGroups parameter in params
   *

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    job.setMapperClass(ParallelCountingMapper.class);
    job.setCombinerClass(ParallelCountingReducer.class);
    job.setReducerClass(ParallelCountingReducer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    
    job.waitForCompletion(true);
    
  }
  
  /**
   * Run the Parallel FPGrowth Map/Reduce Job to calculate the Top K features of group dependent shards

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    job.setInputFormatClass(TextInputFormat.class);
    job.setMapperClass(TransactionSortingMapper.class);
    job.setReducerClass(TransactionSortingReducer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    
    job.waitForCompletion(true);
    params.set("gList", gList);
  }
  
  /**
   * Run the Parallel FPGrowth Map/Reduce Job to calculate the Top K features of group dependent shards

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