Example usage for org.apache.hadoop.mapreduce MRJobConfig REDUCE_CLASS

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In this page you can find the example usage for org.apache.hadoop.mapreduce MRJobConfig REDUCE_CLASS_ATTR.

Prototype

String REDUCE_CLASS_ATTR

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Usage

From source file:co.cask.cdap.internal.app.runtime.batch.MapReduceRuntimeService.java

License:Apache License

/**
 * Returns the input value type of the MR job based on the job Mapper/Reducer type.
 * It does so by inspecting the Mapper/Reducer type parameters to figure out what the input type is.
 * If the job has Mapper, then it's the Mapper IN_VALUE type, otherwise it would be the Reducer IN_VALUE type.
 * If the cannot determine the input value type, then return the given default type.
 *
 * @param hConf the Configuration to use to resolve the class TypeToken
 * @param defaultType the defaultType to return
 * @param mapperTypeToken the mapper type token for the configured input (not resolved by the job's mapper class)
 *///from  ww  w. j  a  v  a2s  .co  m
@VisibleForTesting
static Type getInputValueType(Configuration hConf, Type defaultType, @Nullable TypeToken<?> mapperTypeToken) {
    TypeToken<?> type;
    if (mapperTypeToken == null) {
        // if the input's mapper is null, first try resolving a from the job
        mapperTypeToken = resolveClass(hConf, MRJobConfig.MAP_CLASS_ATTR, Mapper.class);
    }

    if (mapperTypeToken == null) {
        // If there is no Mapper, it's a Reducer only job, hence get the value type from Reducer class
        type = resolveClass(hConf, MRJobConfig.REDUCE_CLASS_ATTR, Reducer.class);
    } else {
        type = mapperTypeToken;
    }
    Preconditions.checkArgument(type != null,
            "Neither a Mapper nor a Reducer is configured for the MapReduce job.");

    if (!(type.getType() instanceof ParameterizedType)) {
        return defaultType;
    }

    // The super type Mapper/Reducer must be a parametrized type with <IN_KEY, IN_VALUE, OUT_KEY, OUT_VALUE>
    Type inputValueType = ((ParameterizedType) type.getType()).getActualTypeArguments()[1];

    // If the concrete Mapper/Reducer class is not parameterized (meaning not extends with parameters),
    // then assume use the default type.
    // We need to check if the TypeVariable is the same as the one in the parent type.
    // This avoid the case where a subclass that has "class InvalidMapper<I, O> extends Mapper<I, O>"
    if (inputValueType instanceof TypeVariable
            && inputValueType.equals(type.getRawType().getTypeParameters()[1])) {
        inputValueType = defaultType;
    }
    return inputValueType;
}

From source file:co.cask.cdap.internal.app.runtime.batch.MapReduceRuntimeService.java

License:Apache License

/**
 * Sets the output key and value classes in the job configuration by inspecting the {@link Mapper} and {@link Reducer}
 * if it is not set by the user.//from  w  w w  .j av  a  2 s  .  co m
 *
 * @param job the MapReduce job
 * @param mapperTypeToken TypeToken of a configured mapper (may not be configured on the job). Has already been
 *                        resolved from the job's mapper class.
 */
private void setOutputClassesIfNeeded(Job job, @Nullable TypeToken<?> mapperTypeToken) {
    Configuration conf = job.getConfiguration();

    // Try to get the type from reducer
    TypeToken<?> type = resolveClass(conf, MRJobConfig.REDUCE_CLASS_ATTR, Reducer.class);

    if (type == null) {
        // Map only job
        type = mapperTypeToken;
    }

    // If not able to detect type, nothing to set
    if (type == null || !(type.getType() instanceof ParameterizedType)) {
        return;
    }

    Type[] typeArgs = ((ParameterizedType) type.getType()).getActualTypeArguments();

    // Set it only if the user didn't set it in beforeSubmit
    // The key and value type are in the 3rd and 4th type parameters
    if (!isProgrammaticConfig(conf, MRJobConfig.OUTPUT_KEY_CLASS)) {
        Class<?> cls = TypeToken.of(typeArgs[2]).getRawType();
        LOG.debug("Set output key class to {}", cls);
        job.setOutputKeyClass(cls);
    }
    if (!isProgrammaticConfig(conf, MRJobConfig.OUTPUT_VALUE_CLASS)) {
        Class<?> cls = TypeToken.of(typeArgs[3]).getRawType();
        LOG.debug("Set output value class to {}", cls);
        job.setOutputValueClass(cls);
    }
}

From source file:co.cask.cdap.internal.app.runtime.batch.MapReduceRuntimeService.java

License:Apache License

/**
 * Sets the map output key and value classes in the job configuration by inspecting the {@link Mapper}
 * if it is not set by the user.//from ww  w  .  java2s  .  c  o  m
 *
 * @param job the MapReduce job
 * @param mapperTypeToken TypeToken of a configured mapper (may not be configured on the job). Has already been
 *                        resolved from the job's mapper class.
 */
private void setMapOutputClassesIfNeeded(Job job, @Nullable TypeToken<?> mapperTypeToken) {
    Configuration conf = job.getConfiguration();

    TypeToken<?> type = mapperTypeToken;
    int keyIdx = 2;
    int valueIdx = 3;

    if (type == null) {
        // Reducer only job. Use the Reducer input types as the key/value classes.
        type = resolveClass(conf, MRJobConfig.REDUCE_CLASS_ATTR, Reducer.class);
        keyIdx = 0;
        valueIdx = 1;
    }

    // If not able to detect type, nothing to set.
    if (type == null || !(type.getType() instanceof ParameterizedType)) {
        return;
    }

    Type[] typeArgs = ((ParameterizedType) type.getType()).getActualTypeArguments();

    // Set it only if the user didn't set it in beforeSubmit
    // The key and value type are in the 3rd and 4th type parameters
    if (!isProgrammaticConfig(conf, MRJobConfig.MAP_OUTPUT_KEY_CLASS)) {
        Class<?> cls = TypeToken.of(typeArgs[keyIdx]).getRawType();
        LOG.debug("Set map output key class to {}", cls);
        job.setMapOutputKeyClass(cls);
    }
    if (!isProgrammaticConfig(conf, MRJobConfig.MAP_OUTPUT_VALUE_CLASS)) {
        Class<?> cls = TypeToken.of(typeArgs[valueIdx]).getRawType();
        LOG.debug("Set map output value class to {}", cls);
        job.setMapOutputValueClass(cls);
    }
}

From source file:co.cask.cdap.internal.app.runtime.batch.ReducerWrapper.java

License:Apache License

/**
 * Wraps the mapper defined in the job with this {@link MapperWrapper} if it is defined.
 * @param job The MapReduce job/*from w w w .j a  v  a2 s  .  c om*/
 */
public static void wrap(Job job) {
    // NOTE: we don't use job.getReducerClass() as we don't need to load user class here
    Configuration conf = job.getConfiguration();
    String reducerClass = conf.get(MRJobConfig.REDUCE_CLASS_ATTR);
    if (reducerClass != null) {
        conf.set(ReducerWrapper.ATTR_REDUCER_CLASS, reducerClass);
        job.setReducerClass(ReducerWrapper.class);
    }
}

From source file:org.apache.ignite.internal.processors.hadoop.GridHadoopUtils.java

License:Apache License

/**
 * Creates JobInfo from hadoop configuration.
 *
 * @param cfg Hadoop configuration./*from  w ww .j  a  v  a  2s.co m*/
 * @return Job info.
 * @throws IgniteCheckedException If failed.
 */
public static GridHadoopDefaultJobInfo createJobInfo(Configuration cfg) throws IgniteCheckedException {
    JobConf jobConf = new JobConf(cfg);

    boolean hasCombiner = jobConf.get("mapred.combiner.class") != null
            || jobConf.get(MRJobConfig.COMBINE_CLASS_ATTR) != null;

    int numReduces = jobConf.getNumReduceTasks();

    jobConf.setBooleanIfUnset("mapred.mapper.new-api", jobConf.get(OLD_MAP_CLASS_ATTR) == null);

    if (jobConf.getUseNewMapper()) {
        String mode = "new map API";

        ensureNotSet(jobConf, "mapred.input.format.class", mode);
        ensureNotSet(jobConf, OLD_MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, "mapred.partitioner.class", mode);
        else
            ensureNotSet(jobConf, "mapred.output.format.class", mode);
    } else {
        String mode = "map compatibility";

        ensureNotSet(jobConf, MRJobConfig.INPUT_FORMAT_CLASS_ATTR, mode);
        ensureNotSet(jobConf, MRJobConfig.MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, MRJobConfig.PARTITIONER_CLASS_ATTR, mode);
        else
            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
    }

    if (numReduces != 0) {
        jobConf.setBooleanIfUnset("mapred.reducer.new-api", jobConf.get(OLD_REDUCE_CLASS_ATTR) == null);

        if (jobConf.getUseNewReducer()) {
            String mode = "new reduce API";

            ensureNotSet(jobConf, "mapred.output.format.class", mode);
            ensureNotSet(jobConf, OLD_REDUCE_CLASS_ATTR, mode);
        } else {
            String mode = "reduce compatibility";

            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
            ensureNotSet(jobConf, MRJobConfig.REDUCE_CLASS_ATTR, mode);
        }
    }

    Map<String, String> props = new HashMap<>();

    for (Map.Entry<String, String> entry : jobConf)
        props.put(entry.getKey(), entry.getValue());

    return new GridHadoopDefaultJobInfo(jobConf.getJobName(), jobConf.getUser(), hasCombiner, numReduces,
            props);
}

From source file:org.apache.ignite.internal.processors.hadoop.HadoopUtils.java

License:Apache License

/**
 * Creates JobInfo from hadoop configuration.
 *
 * @param cfg Hadoop configuration./*from www  . j  a v a 2s  .c om*/
 * @return Job info.
 * @throws IgniteCheckedException If failed.
 */
public static HadoopDefaultJobInfo createJobInfo(Configuration cfg) throws IgniteCheckedException {
    JobConf jobConf = new JobConf(cfg);

    boolean hasCombiner = jobConf.get("mapred.combiner.class") != null
            || jobConf.get(MRJobConfig.COMBINE_CLASS_ATTR) != null;

    int numReduces = jobConf.getNumReduceTasks();

    jobConf.setBooleanIfUnset("mapred.mapper.new-api", jobConf.get(OLD_MAP_CLASS_ATTR) == null);

    if (jobConf.getUseNewMapper()) {
        String mode = "new map API";

        ensureNotSet(jobConf, "mapred.input.format.class", mode);
        ensureNotSet(jobConf, OLD_MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, "mapred.partitioner.class", mode);
        else
            ensureNotSet(jobConf, "mapred.output.format.class", mode);
    } else {
        String mode = "map compatibility";

        ensureNotSet(jobConf, MRJobConfig.INPUT_FORMAT_CLASS_ATTR, mode);
        ensureNotSet(jobConf, MRJobConfig.MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, MRJobConfig.PARTITIONER_CLASS_ATTR, mode);
        else
            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
    }

    if (numReduces != 0) {
        jobConf.setBooleanIfUnset("mapred.reducer.new-api", jobConf.get(OLD_REDUCE_CLASS_ATTR) == null);

        if (jobConf.getUseNewReducer()) {
            String mode = "new reduce API";

            ensureNotSet(jobConf, "mapred.output.format.class", mode);
            ensureNotSet(jobConf, OLD_REDUCE_CLASS_ATTR, mode);
        } else {
            String mode = "reduce compatibility";

            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
            ensureNotSet(jobConf, MRJobConfig.REDUCE_CLASS_ATTR, mode);
        }
    }

    Map<String, String> props = new HashMap<>();

    for (Map.Entry<String, String> entry : jobConf)
        props.put(entry.getKey(), entry.getValue());

    return new HadoopDefaultJobInfo(jobConf.getJobName(), jobConf.getUser(), hasCombiner, numReduces, props);
}

From source file:org.apache.tez.mapreduce.examples.MRRSleepJob.java

License:Apache License

public DAG createDAG(FileSystem remoteFs, Configuration conf, Path remoteStagingDir, int numMapper,
        int numReducer, int iReduceStagesCount, int numIReducer, long mapSleepTime, int mapSleepCount,
        long reduceSleepTime, int reduceSleepCount, long iReduceSleepTime, int iReduceSleepCount,
        boolean writeSplitsToDFS, boolean generateSplitsInAM) throws IOException, YarnException {

    Configuration mapStageConf = new JobConf(conf);
    mapStageConf.setInt(MRJobConfig.NUM_MAPS, numMapper);
    mapStageConf.setLong(MAP_SLEEP_TIME, mapSleepTime);
    mapStageConf.setLong(REDUCE_SLEEP_TIME, reduceSleepTime);
    mapStageConf.setLong(IREDUCE_SLEEP_TIME, iReduceSleepTime);
    mapStageConf.setInt(MAP_SLEEP_COUNT, mapSleepCount);
    mapStageConf.setInt(REDUCE_SLEEP_COUNT, reduceSleepCount);
    mapStageConf.setInt(IREDUCE_SLEEP_COUNT, iReduceSleepCount);
    mapStageConf.setInt(IREDUCE_STAGES_COUNT, iReduceStagesCount);
    mapStageConf.setInt(IREDUCE_TASKS_COUNT, numIReducer);
    mapStageConf.set(MRJobConfig.MAP_CLASS_ATTR, SleepMapper.class.getName());
    mapStageConf.set(MRJobConfig.INPUT_FORMAT_CLASS_ATTR, SleepInputFormat.class.getName());
    if (numIReducer == 0 && numReducer == 0) {
        mapStageConf.set(MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, NullOutputFormat.class.getName());
    }/*from   www.j a v  a  2  s  .c  o  m*/

    MRHelpers.translateMRConfToTez(mapStageConf);

    Configuration[] intermediateReduceStageConfs = null;
    if (iReduceStagesCount > 0 && numIReducer > 0) {
        intermediateReduceStageConfs = new JobConf[iReduceStagesCount];
        for (int i = 1; i <= iReduceStagesCount; ++i) {
            JobConf iReduceStageConf = new JobConf(conf);
            iReduceStageConf.setLong(MRRSleepJob.REDUCE_SLEEP_TIME, iReduceSleepTime);
            iReduceStageConf.setInt(MRRSleepJob.REDUCE_SLEEP_COUNT, iReduceSleepCount);
            iReduceStageConf.setInt(MRJobConfig.NUM_REDUCES, numIReducer);
            iReduceStageConf.set(MRJobConfig.REDUCE_CLASS_ATTR, ISleepReducer.class.getName());
            iReduceStageConf.set(MRJobConfig.MAP_OUTPUT_KEY_CLASS, IntWritable.class.getName());
            iReduceStageConf.set(MRJobConfig.MAP_OUTPUT_VALUE_CLASS, IntWritable.class.getName());
            iReduceStageConf.set(MRJobConfig.PARTITIONER_CLASS_ATTR, MRRSleepJobPartitioner.class.getName());

            MRHelpers.translateMRConfToTez(iReduceStageConf);
            intermediateReduceStageConfs[i - 1] = iReduceStageConf;
        }
    }

    Configuration finalReduceConf = null;
    if (numReducer > 0) {
        finalReduceConf = new JobConf(conf);
        finalReduceConf.setLong(MRRSleepJob.REDUCE_SLEEP_TIME, reduceSleepTime);
        finalReduceConf.setInt(MRRSleepJob.REDUCE_SLEEP_COUNT, reduceSleepCount);
        finalReduceConf.setInt(MRJobConfig.NUM_REDUCES, numReducer);
        finalReduceConf.set(MRJobConfig.REDUCE_CLASS_ATTR, SleepReducer.class.getName());
        finalReduceConf.set(MRJobConfig.MAP_OUTPUT_KEY_CLASS, IntWritable.class.getName());
        finalReduceConf.set(MRJobConfig.MAP_OUTPUT_VALUE_CLASS, IntWritable.class.getName());
        finalReduceConf.set(MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, NullOutputFormat.class.getName());

        MRHelpers.translateMRConfToTez(finalReduceConf);
    }

    MRHelpers.configureMRApiUsage(mapStageConf);
    if (iReduceStagesCount > 0 && numIReducer > 0) {
        for (int i = 0; i < iReduceStagesCount; ++i) {
            MRHelpers.configureMRApiUsage(intermediateReduceStageConfs[i]);
        }
    }
    if (numReducer > 0) {
        MRHelpers.configureMRApiUsage(finalReduceConf);
    }

    DataSourceDescriptor dataSource = null;
    if (!generateSplitsInAM && writeSplitsToDFS) {

        LOG.info("Writing splits to DFS");
        dataSource = MRInputHelpers.configureMRInputWithLegacySplitGeneration(mapStageConf, remoteStagingDir,
                true);
    } else {
        dataSource = MRInputLegacy.createConfigBuilder(mapStageConf, SleepInputFormat.class)
                .generateSplitsInAM(generateSplitsInAM).build();
    }

    DAG dag = DAG.create("MRRSleepJob");
    String jarPath = ClassUtil.findContainingJar(getClass());
    if (jarPath == null) {
        throw new TezUncheckedException(
                "Could not find any jar containing" + " MRRSleepJob.class in the classpath");
    }
    Path remoteJarPath = remoteFs.makeQualified(new Path(remoteStagingDir, "dag_job.jar"));
    remoteFs.copyFromLocalFile(new Path(jarPath), remoteJarPath);
    FileStatus jarFileStatus = remoteFs.getFileStatus(remoteJarPath);

    TokenCache.obtainTokensForNamenodes(this.credentials, new Path[] { remoteJarPath }, mapStageConf);

    Map<String, LocalResource> commonLocalResources = new HashMap<String, LocalResource>();
    LocalResource dagJarLocalRsrc = LocalResource.newInstance(ConverterUtils.getYarnUrlFromPath(remoteJarPath),
            LocalResourceType.FILE, LocalResourceVisibility.APPLICATION, jarFileStatus.getLen(),
            jarFileStatus.getModificationTime());
    commonLocalResources.put("dag_job.jar", dagJarLocalRsrc);

    List<Vertex> vertices = new ArrayList<Vertex>();

    UserPayload mapUserPayload = TezUtils.createUserPayloadFromConf(mapStageConf);
    int numTasks = generateSplitsInAM ? -1 : numMapper;

    Map<String, String> mapEnv = Maps.newHashMap();
    MRHelpers.updateEnvBasedOnMRTaskEnv(mapStageConf, mapEnv, true);
    Map<String, String> reduceEnv = Maps.newHashMap();
    MRHelpers.updateEnvBasedOnMRTaskEnv(mapStageConf, reduceEnv, false);

    Vertex mapVertex = Vertex.create("map",
            ProcessorDescriptor.create(MapProcessor.class.getName()).setUserPayload(mapUserPayload), numTasks,
            MRHelpers.getResourceForMRMapper(mapStageConf));
    mapVertex.addTaskLocalFiles(commonLocalResources).addDataSource("MRInput", dataSource)
            .setTaskLaunchCmdOpts(MRHelpers.getJavaOptsForMRMapper(mapStageConf)).setTaskEnvironment(mapEnv);
    vertices.add(mapVertex);

    if (iReduceStagesCount > 0 && numIReducer > 0) {
        for (int i = 0; i < iReduceStagesCount; ++i) {
            Configuration iconf = intermediateReduceStageConfs[i];
            UserPayload iReduceUserPayload = TezUtils.createUserPayloadFromConf(iconf);
            Vertex ivertex = Vertex.create("ireduce" + (i + 1),
                    ProcessorDescriptor.create(ReduceProcessor.class.getName())
                            .setUserPayload(iReduceUserPayload),
                    numIReducer, MRHelpers.getResourceForMRReducer(intermediateReduceStageConfs[i]));
            ivertex.addTaskLocalFiles(commonLocalResources)
                    .setTaskLaunchCmdOpts(MRHelpers.getJavaOptsForMRReducer(intermediateReduceStageConfs[i]))
                    .setTaskEnvironment(reduceEnv);
            vertices.add(ivertex);
        }
    }

    Vertex finalReduceVertex = null;
    if (numReducer > 0) {
        UserPayload reducePayload = TezUtils.createUserPayloadFromConf(finalReduceConf);
        finalReduceVertex = Vertex.create("reduce",
                ProcessorDescriptor.create(ReduceProcessor.class.getName()).setUserPayload(reducePayload),
                numReducer, MRHelpers.getResourceForMRReducer(finalReduceConf));
        finalReduceVertex.addTaskLocalFiles(commonLocalResources)
                .addDataSink("MROutput",
                        MROutputLegacy.createConfigBuilder(finalReduceConf, NullOutputFormat.class).build())
                .setTaskLaunchCmdOpts(MRHelpers.getJavaOptsForMRReducer(finalReduceConf))
                .setTaskEnvironment(reduceEnv);
        vertices.add(finalReduceVertex);
    } else {
        // Map only job
        mapVertex.addDataSink("MROutput",
                MROutputLegacy.createConfigBuilder(mapStageConf, NullOutputFormat.class).build());
    }

    Map<String, String> partitionerConf = Maps.newHashMap();
    partitionerConf.put(MRJobConfig.PARTITIONER_CLASS_ATTR, MRRSleepJobPartitioner.class.getName());
    OrderedPartitionedKVEdgeConfig edgeConf = OrderedPartitionedKVEdgeConfig
            .newBuilder(IntWritable.class.getName(), IntWritable.class.getName(),
                    HashPartitioner.class.getName(), partitionerConf)
            .configureInput().useLegacyInput().done().build();

    for (int i = 0; i < vertices.size(); ++i) {
        dag.addVertex(vertices.get(i));
        if (i != 0) {
            dag.addEdge(
                    Edge.create(vertices.get(i - 1), vertices.get(i), edgeConf.createDefaultEdgeProperty()));
        }
    }

    return dag;
}

From source file:org.gridgain.grid.kernal.processors.hadoop.GridHadoopUtils.java

License:Open Source License

/**
 * Creates JobInfo from hadoop configuration.
 *
 * @param cfg Hadoop configuration.//from ww  w . j  a  v a  2  s.c om
 * @return Job info.
 * @throws GridException If failed.
 */
public static GridHadoopDefaultJobInfo createJobInfo(Configuration cfg) throws GridException {
    JobConf jobConf = new JobConf(cfg);

    boolean hasCombiner = jobConf.get("mapred.combiner.class") != null
            || jobConf.get(MRJobConfig.COMBINE_CLASS_ATTR) != null;

    int numReduces = jobConf.getNumReduceTasks();

    jobConf.setBooleanIfUnset("mapred.mapper.new-api", jobConf.get(OLD_MAP_CLASS_ATTR) == null);

    if (jobConf.getUseNewMapper()) {
        String mode = "new map API";

        ensureNotSet(jobConf, "mapred.input.format.class", mode);
        ensureNotSet(jobConf, OLD_MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, "mapred.partitioner.class", mode);
        else
            ensureNotSet(jobConf, "mapred.output.format.class", mode);
    } else {
        String mode = "map compatibility";

        ensureNotSet(jobConf, MRJobConfig.INPUT_FORMAT_CLASS_ATTR, mode);
        ensureNotSet(jobConf, MRJobConfig.MAP_CLASS_ATTR, mode);

        if (numReduces != 0)
            ensureNotSet(jobConf, MRJobConfig.PARTITIONER_CLASS_ATTR, mode);
        else
            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
    }

    if (numReduces != 0) {
        jobConf.setBooleanIfUnset("mapred.reducer.new-api", jobConf.get(OLD_REDUCE_CLASS_ATTR) == null);

        if (jobConf.getUseNewReducer()) {
            String mode = "new reduce API";

            ensureNotSet(jobConf, "mapred.output.format.class", mode);
            ensureNotSet(jobConf, OLD_REDUCE_CLASS_ATTR, mode);
        } else {
            String mode = "reduce compatibility";

            ensureNotSet(jobConf, MRJobConfig.OUTPUT_FORMAT_CLASS_ATTR, mode);
            ensureNotSet(jobConf, MRJobConfig.REDUCE_CLASS_ATTR, mode);
        }
    }

    Map<String, String> props = new HashMap<>();

    for (Map.Entry<String, String> entry : jobConf)
        props.put(entry.getKey(), entry.getValue());

    return new GridHadoopDefaultJobInfo(jobConf.getJobName(), jobConf.getUser(), hasCombiner, numReduces,
            props);
}

Example usage for org.apache.hadoop.mapreduce MRJobConfig REDUCE_CLASS_ATTR

Introduction

Prototype

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