org.apache.avro.mapred.AvroJob Java Examples

The following examples show how to use org.apache.avro.mapred.AvroJob. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example #1
Source File: AvroAsJsonOutputFormat.java    From iow-hadoop-streaming with Apache License 2.0 6 votes vote down vote up
static <K> void configureDataFileWriter(DataFileWriter<K> writer,
    JobConf job) throws UnsupportedEncodingException {

    if (FileOutputFormat.getCompressOutput(job)) {
        int level = job.getInt(org.apache.avro.mapred.AvroOutputFormat.DEFLATE_LEVEL_KEY,
                org.apache.avro.mapred.AvroOutputFormat.DEFAULT_DEFLATE_LEVEL);
        String codecName = job.get(AvroJob.OUTPUT_CODEC, DEFLATE_CODEC);
        CodecFactory factory = codecName.equals(DEFLATE_CODEC) ?
            CodecFactory.deflateCodec(level) : CodecFactory.fromString(codecName);
        writer.setCodec(factory);
    }

    writer.setSyncInterval(job.getInt(org.apache.avro.mapred.AvroOutputFormat.SYNC_INTERVAL_KEY,
            DEFAULT_SYNC_INTERVAL));

    // copy metadata from job
    for (Map.Entry<String,String> e : job) {
        if (e.getKey().startsWith(AvroJob.TEXT_PREFIX))
            writer.setMeta(e.getKey().substring(AvroJob.TEXT_PREFIX.length()),e.getValue());
        if (e.getKey().startsWith(AvroJob.BINARY_PREFIX))
            writer.setMeta(e.getKey().substring(AvroJob.BINARY_PREFIX.length()),
                   URLDecoder.decode(e.getValue(), "ISO-8859-1")
                   .getBytes("ISO-8859-1"));
    }
}
 
Example #2
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
/**
 * Creates a JobConf for a map-reduce job. Loads the input schema from the input files.
 * 
 * @param mapperClass AvroMapper subclass for the mapper.
 * @param reducerClass AvroReducer subclass for the reducer.
 * @param mapperOutputSchema Mapper output schema. Must be an instance of org.apache.avro.mapred.Pair
 * @param outputSchema Reducer output schema
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                             Class<? extends AvroReducer> reducerClass,
                             Schema mapperOutputSchema,
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();

  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);

  AvroJob.setMapOutputSchema(conf, mapperOutputSchema);
  AvroJob.setOutputSchema(conf, outputSchema);

  return conf;
}
 
Example #3
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
/**
 * Creates a JobConf for a map-reduce job that uses a combiner. Loads the input schema from the
 * input files.
 * 
 * @param mapperClass AvroMapper subclass for the mapper.
 * @param reducerClass AvroReducer subclass for the reducer.
 * @param combinerClass AvroReducer subclass for the combiner.
 * @param mapperOutputSchema Mapper output schema. Must be an instance of org.apache.avro.mapred.Pair
 * @param outputSchema Reducer output schema
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                             Class<? extends AvroReducer> reducerClass,
                             Class<? extends AvroReducer> combinerClass,
                             Schema mapperOutputSchema,
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();
  
  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);
  AvroJob.setCombinerClass(conf, combinerClass);
  
  AvroJob.setMapOutputSchema(conf, mapperOutputSchema);
  AvroJob.setOutputSchema(conf, outputSchema);
  
  return conf;
}
 
Example #4
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
/**
 * Creates a JobConf for a map-only job with an explicitly set input Schema.
 * 
 * @param mapperClass AvroMapper subclass implementing the map phase
 * @param inputSchema Schema of the input data.
 * @param outputSchema Schema of the mapper output
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass, 
                             Schema inputSchema, 
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();

  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, AvroReducer.class);
  
  AvroJob.setInputSchema(conf, inputSchema);
  AvroJob.setOutputSchema(conf, outputSchema);
  
  conf.setNumReduceTasks(0);

  return conf;
}
 
Example #5
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
/**
 * Creates a JobConf for a map-reducer job with an explicitly set input schema.
 * 
 * @param mapperClass AvroMapper subclass for the mapper.
 * @param reducerClass AvroReducer subclass for the reducer.
 * @param inputSchema Schema of the input data.
 * @param mapperOutputSchema Mapper output schema. Must be an instance of org.apache.avro.mapred.Pair
 * @param outputSchema Reducer output schema
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                             Class<? extends AvroReducer> reducerClass,
                             Schema inputSchema,
                             Schema mapperOutputSchema,
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();
  
  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);
  
  AvroJob.setInputSchema(conf, inputSchema);
  AvroJob.setMapOutputSchema(conf, mapperOutputSchema);
  AvroJob.setOutputSchema(conf, outputSchema);

  return conf;
}
 
Example #6
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
/**
 * Creates a JobConf for a map-reduce job that uses a combiner and has an explicitly set input schema.
 * 
 * @param mapperClass AvroMapper subclass for the mapper.
 * @param reducerClass AvroReducer subclass for the reducer.
 * @param combinerClass AvroReducer subclass for the combiner.
 * @param inputSchema Schema of the input data.
 * @param mapperOutputSchema Mapper output schema. Must be an instance of org.apache.avro.mapred.Pair
 * @param outputSchema Reducer output schema
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                             Class<? extends AvroReducer> reducerClass,
                             Class<? extends AvroReducer> combinerClass,
                             Schema inputSchema,
                             Schema mapperOutputSchema,
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();
  
  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);
  AvroJob.setCombinerClass(conf, combinerClass);
  
  AvroJob.setInputSchema(conf, inputSchema);
  AvroJob.setMapOutputSchema(conf, mapperOutputSchema);
  AvroJob.setOutputSchema(conf, outputSchema);

  return conf;
}
 
Example #7
Source File: RegressionTest.java    From ml-ease with Apache License 2.0 6 votes vote down vote up
@Override
public void setConf(Configuration conf)
{
  super.setConf(conf);
  if (conf == null)
  {
    return;
  }
  _outputSchema = AvroJob.getOutputSchema(conf);
  AvroDistributedCacheFileReader modelReader =
      new AvroDistributedCacheFileReader(new JobConf(conf));
  try
  {
    modelReader.build(conf.get(MODEL_PATH), _modelConsumer);
    _modelConsumer.done();
  }
  catch (IOException e)
  {
    e.printStackTrace();
  }
  _lambda = conf.getFloat(LAMBDA, 0);
  _ignoreValue = conf.getBoolean(BINARY_FEATURE, false);
  _logger.info("Loaded the model for test, size:" + _modelConsumer.get().size());
}
 
Example #8
Source File: ItemModelTest.java    From ml-ease with Apache License 2.0 5 votes vote down vote up
private JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                              Class<? extends AvroReducer> reducerClass) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();
  Schema inputSchema = Util.removeUnion(AvroUtils.getAvroInputSchema(conf));
  if (inputSchema == null)
  {
    throw new IllegalStateException("Input does not have schema info and/or input is missing.");
  }
  _logger.info("Input Schema=" + inputSchema.toString());
  List<Schema.Field> inputFields = inputSchema.getFields();
  Schema.Field predField =
      new Schema.Field("pred", Schema.create(Type.FLOAT), "", null);
  List<Schema.Field> outputFields = new LinkedList<Schema.Field>();
  for (Schema.Field field : inputFields)
  {
    outputFields.add(new Schema.Field(field.name(),
                                      field.schema(),
                                      field.doc(),
                                      null));
  }
  outputFields.add(predField);
  Schema outputSchema =
      Schema.createRecord("PerItemTestOutput",
                          "Test output for PerItemTest",
                          "com.linkedin.lab.regression.avro",
                          false);
  outputSchema.setFields(outputFields);
  AvroJob.setOutputSchema(conf, outputSchema);
  AvroJob.setMapOutputSchema(conf,
                             Pair.getPairSchema(Schema.create(Type.STRING), inputSchema));
  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);
  return conf;
}
 
Example #9
Source File: AvroRecordWriter.java    From spork with Apache License 2.0 5 votes vote down vote up
static void configureDataFileWriter(DataFileWriter<GenericData.Record> writer,
    JobConf job) throws UnsupportedEncodingException {
  if (FileOutputFormat.getCompressOutput(job)) {
    int level = job.getInt(DEFLATE_LEVEL_KEY,
        DEFAULT_DEFLATE_LEVEL);
    String codecName = job.get(AvroJob.OUTPUT_CODEC, DEFLATE_CODEC);
    CodecFactory factory = codecName.equals(DEFLATE_CODEC)
      ? CodecFactory.deflateCodec(level)
      : CodecFactory.fromString(codecName);
    writer.setCodec(factory);
  }

  // Do max as core-default.xml has io.file.buffer.size as 4K
  writer.setSyncInterval(job.getInt(SYNC_INTERVAL_KEY, Math.max(
          job.getInt("io.file.buffer.size", DEFAULT_SYNC_INTERVAL), DEFAULT_SYNC_INTERVAL)));

  // copy metadata from job
  for (Map.Entry<String,String> e : job) {
    if (e.getKey().startsWith(AvroJob.TEXT_PREFIX))
      writer.setMeta(e.getKey().substring(AvroJob.TEXT_PREFIX.length()),
                     e.getValue());
    if (e.getKey().startsWith(AvroJob.BINARY_PREFIX))
      writer.setMeta(e.getKey().substring(AvroJob.BINARY_PREFIX.length()),
                     URLDecoder.decode(e.getValue(), "ISO-8859-1")
                     .getBytes("ISO-8859-1"));
  }
}
 
Example #10
Source File: BloomFilterCreator.java    From hiped2 with Apache License 2.0 5 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.MrIoOpts.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path inputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.INPUT));
  Path outputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.OUTPUT));

  Configuration conf = super.getConf();

  JobConf job = new JobConf(conf);
  job.setJarByClass(BloomFilterCreator.class);

  job.set(AvroJob.OUTPUT_SCHEMA, AvroBytesRecord.SCHEMA.toString());
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setInputFormat(KeyValueTextInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);

  job.setMapperClass(Map.class);
  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(NullWritable.class);
  job.setMapOutputValueClass(BloomFilter.class);

  job.setOutputKeyClass(NullWritable.class);
  job.setOutputValueClass(BloomFilter.class);

  FileInputFormat.setInputPaths(job, inputPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  return JobClient.runJob(job).isSuccessful() ? 0 : 1;
}
 
Example #11
Source File: RegressionTest.java    From ml-ease with Apache License 2.0 5 votes vote down vote up
private JobConf createJobConf(Class<? extends AvroMapper> mapperClass,
                              Class<? extends AvroReducer> reducerClass) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();
  Schema inputSchema = Util.removeUnion(AvroUtils.getAvroInputSchema(conf));
  if (inputSchema == null)
  {
    throw new IllegalStateException("Input does not have schema info and/or input is missing.");
  }
  _logger.info("Input Schema=" + inputSchema.toString());
  List<Schema.Field> inputFields = inputSchema.getFields();
  Schema.Field predField =
      new Schema.Field("pred", Schema.create(Type.FLOAT), "", null);
  List<Schema.Field> outputFields = new LinkedList<Schema.Field>();
  for (Schema.Field field : inputFields)
  {
    outputFields.add(new Schema.Field(field.name(),
                                      field.schema(),
                                      field.doc(),
                                      null));
  }
  outputFields.add(predField);
  Schema outputSchema =
      Schema.createRecord("AdmmTestOutput",
                          "Test output for AdmmTest",
                          "com.linkedin.lab.regression.avro",
                          false);
  outputSchema.setFields(outputFields);
  AvroJob.setOutputSchema(conf, outputSchema);
  AvroJob.setMapOutputSchema(conf,
                             Pair.getPairSchema(Schema.create(Type.FLOAT), outputSchema));
  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, reducerClass);
  return conf;
}
 
Example #12
Source File: AvroFileAccessor.java    From pxf with Apache License 2.0 5 votes vote down vote up
@Override
public boolean openForRead() throws Exception {
    // Pass the schema to the AvroInputFormat
    AvroJob.setInputSchema(jobConf, schema);

    // The avroWrapper required for the iteration
    avroWrapper = new AvroWrapper<>();

    return super.openForRead();
}
 
Example #13
Source File: ItemModelTest.java    From ml-ease with Apache License 2.0 5 votes vote down vote up
@Override
public void setConf(Configuration conf)
{
  super.setConf(conf);
  if (conf == null)
  {
    return;
  }
  _outputSchema = AvroJob.getOutputSchema(conf);
  _lambda = conf.getFloat(LAMBDA, 0);
  _ignoreValue = conf.getBoolean(BINARY_FEATURE, false);
  String modelPath = conf.get(MODEL_PATH, "");
  _logger.info("Going to read model files from distributed cache at:" + modelPath);
  int reduceTaskId = conf.getInt("mapred.task.partition", -1);
  _logger.info("The reduce task id=" + reduceTaskId);
  if (reduceTaskId < 0)
  {
    throw new RuntimeException("Can't read reduce task id from mapred.task.partition!");
  }
  int nReducers = conf.getInt(NUM_REDUCERS, -1);
  String lambdaKey = String.valueOf(_lambda) + "#";
  _consumer = new ReadLinearModelConsumer(lambdaKey, reduceTaskId, nReducers);
  AvroDistributedCacheFileReader modelReader =
      new AvroDistributedCacheFileReader(new JobConf(conf));
  try
  {
    modelReader.build(modelPath, _consumer);
    _consumer.done();
  }
  catch (IOException e)
  {
    throw new RuntimeException("Can't load model, error=" + e);
  }
  _logger.info("Loaded linear models, number of models loaded="
      + _consumer.get().size());
}
 
Example #14
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 5 votes vote down vote up
/**
 * Creates a JobConf for a map-only job. Automatically loads the schema from each input file.
 * 
 * @param mapperClass AvroMapper subclass implementing the map phase
 * @param outputSchema Schema of the mapper output
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
public JobConf createJobConf(Class<? extends AvroMapper> mapperClass, 
                             Schema outputSchema) throws IOException, URISyntaxException
{
  JobConf conf = createJobConf();

  AvroJob.setMapperClass(conf, mapperClass);
  AvroJob.setReducerClass(conf, AvroReducer.class);

  AvroJob.setOutputSchema(conf, outputSchema);
  
  conf.setNumReduceTasks(0);

  return conf;
}
 
Example #15
Source File: DBImportMapReduce.java    From hiped2 with Apache License 2.0 4 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.OutputFileOption.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path output = new Path(cli.getArgValueAsString(CliCommonOpts.OutputFileOption.OUTPUT));

  Configuration conf = super.getConf();

  DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver",
      "jdbc:mysql://localhost/sqoop_test" +
          "?user=hip_sqoop_user&password=password");

  JobConf job = new JobConf(conf);
  job.setJarByClass(DBImportMapReduce.class);

  job.setInputFormat(DBInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);
  AvroJob.setOutputSchema(job, Stock.SCHEMA$);
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setMapperClass(Map.class);

  job.setNumMapTasks(4);
  job.setNumReduceTasks(0);

  job.setMapOutputKeyClass(AvroWrapper.class);
  job.setMapOutputValueClass(NullWritable.class);

  job.setOutputKeyClass(AvroWrapper.class);
  job.setOutputValueClass(NullWritable.class);

  FileOutputFormat.setOutputPath(job, output);

  DBInputFormat.setInput(
      job,
      StockDbWritable.class,
      "select * from stocks",
      "SELECT COUNT(id) FROM stocks");

  RunningJob runningJob = JobClient.runJob(job);

  return runningJob.isSuccessful() ? 0 : 1;
}
 
Example #16
Source File: AbstractAvroJob.java    From ml-ease with Apache License 2.0 4 votes vote down vote up
/**
 * Sets up various standard settings in the JobConf. You probably don't want to mess with this.
 * 
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
protected  JobConf createJobConf() throws IOException, URISyntaxException
{
  JobConf conf = new JobConf();
  
  conf.setJobName(getJobId());
  conf.setInputFormat(AvroInputFormat.class);
  conf.setOutputFormat(AvroOutputFormat.class);
  
  AvroOutputFormat.setDeflateLevel(conf, 9);
  
  String hadoop_ugi = _config.getString("hadoop.job.ugi", null);
  if (hadoop_ugi != null)
  {
      conf.set("hadoop.job.ugi", hadoop_ugi);
  }
  if (_config.getBoolean("is.local", false))
  {
    conf.set("mapred.job.tracker", "local");
    conf.set("fs.default.name", "file:///");
    conf.set("mapred.local.dir", "/tmp/map-red");

    _log.info("Running locally, no hadoop jar set.");
  }
  
  // set JVM options if present
  if (_config.containsKey("mapred.child.java.opts"))
  {
    conf.set("mapred.child.java.opts", _config.getString("mapred.child.java.opts"));
    _log.info("mapred.child.java.opts set to " + _config.getString("mapred.child.java.opts"));
  }

  if (_config.containsKey(INPUT_PATHS))
  {
    List<String> inputPathnames = _config.getStringList(INPUT_PATHS);
    for (String pathname : inputPathnames)
    {
      AvroUtils.addAllSubPaths(conf, new Path(pathname));
    }
    AvroJob.setInputSchema(conf, AvroUtils.getAvroInputSchema(conf));
  }

  if (_config.containsKey(OUTPUT_PATH))
  {
    Path path = new Path(_config.get(OUTPUT_PATH));
    AvroOutputFormat.setOutputPath(conf, path);

    if (_config.getBoolean("force.output.overwrite", false))
    {
      FileSystem fs = FileOutputFormat.getOutputPath(conf).getFileSystem(conf);
      fs.delete(FileOutputFormat.getOutputPath(conf), true);
    }
  }
  // set all hadoop configs
  for (String key : _config.keySet()) 
  {
    String lowerCase = key.toLowerCase();
    if ( lowerCase.startsWith(HADOOP_PREFIX)) 
    {
        String newKey = key.substring(HADOOP_PREFIX.length());
        conf.set(newKey, _config.get(key));
    }
  }
  return conf;
}
 
Example #17
Source File: AvroMixedMapReduce.java    From hiped2 with Apache License 2.0 3 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {


  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.MrIoOpts.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path inputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.INPUT));
  Path outputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.OUTPUT));

  Configuration conf = super.getConf();

  JobConf job = new JobConf(conf);
  job.setJarByClass(AvroMixedMapReduce.class);

  job.set(AvroJob.INPUT_SCHEMA, Stock.SCHEMA$.toString());
  job.set(AvroJob.OUTPUT_SCHEMA, StockAvg.SCHEMA$.toString());
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setInputFormat(AvroInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);

  job.setMapperClass(Map.class);
  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(Text.class);
  job.setMapOutputValueClass(DoubleWritable.class);

  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(DoubleWritable.class);

  FileInputFormat.setInputPaths(job, inputPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  return JobClient.runJob(job).isSuccessful() ? 0 : 1;
}
 
Example #18
Source File: SmallFilesMapReduce.java    From hiped2 with Apache License 2.0 3 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.MrIoOpts.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  String inputPath = cli.getArgValueAsString(CliCommonOpts.MrIoOpts.INPUT);
  Path outputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.OUTPUT));

  Configuration conf = super.getConf();

  JobConf job = new JobConf(conf);
  job.setJarByClass(SmallFilesMapReduce.class);

  job.set(AvroJob.INPUT_SCHEMA, SmallFilesWrite.SCHEMA.toString());

  job.setInputFormat(AvroInputFormat.class);

  job.setOutputFormat(TextOutputFormat.class);

  job.setMapperClass(Map.class);
  FileInputFormat.setInputPaths(job, inputPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  job.setNumReduceTasks(0);

  return JobClient.runJob(job).isSuccessful() ? 0 : 1;
}