Example usage for org.apache.hadoop.mapred JobConf setJobName

List of usage examples for org.apache.hadoop.mapred JobConf setJobName

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Introduction

In this page you can find the example usage for org.apache.hadoop.mapred JobConf setJobName.

Prototype

public void setJobName(String name)

Source Link

Document

Set the user-specified job name.

Usage

From source file:ca.etsmtl.logti.log792.mti830.RowCounter.java

License:Apache License

/**
 * @param args/*from w  w w  . j  a  va  2 s . c  om*/
 * @return the JobConf
 * @throws IOException
 */
@SuppressWarnings({ "unused", "deprecation" })
public JobConf createSubmittableJob(String[] args) throws IOException {
    JobConf c = new JobConf(getConf(), RowCounter.class);
    c.setJobName(NAME);
    // Columns are space delimited
    StringBuilder sb = new StringBuilder();
    final int columnoffset = 2;
    for (int i = columnoffset; i < args.length; i++) {
        if (i > columnoffset) {
            sb.append(" ");
        }
        sb.append(args[i]);
    }
    // Second argument is the table name.
    TableMapReduceUtil.initTableMapJob(args[1], sb.toString(), this.getClass(), ImmutableBytesWritable.class,
            RowResult.class, c);
    c.setReducerClass(IdentityReducer.class);
    // First arg is the output directory.
    FileOutputFormat.setOutputPath(c, new Path(args[0]));
    return c;
}

From source file:cascading.flow.FlowStep.java

License:Open Source License

protected JobConf getJobConf(JobConf parentConf) throws IOException {
    JobConf conf = parentConf == null ? new JobConf() : new JobConf(parentConf);

    // set values first so they can't break things downstream
    if (hasProperties()) {
        for (Map.Entry entry : getProperties().entrySet())
            conf.set(entry.getKey().toString(), entry.getValue().toString());
    }/*  w  w  w.  ja va2  s .c o m*/

    // disable warning
    conf.setBoolean("mapred.used.genericoptionsparser", true);

    conf.setJobName(getStepName());

    conf.setOutputKeyClass(Tuple.class);
    conf.setOutputValueClass(Tuple.class);

    conf.setMapperClass(FlowMapper.class);
    conf.setReducerClass(FlowReducer.class);

    // set for use by the shuffling phase
    TupleSerialization.setSerializations(conf);

    initFromSources(conf);

    initFromSink(conf);

    initFromTraps(conf);

    if (sink.getScheme().getNumSinkParts() != 0) {
        // if no reducer, set num map tasks to control parts
        if (getGroup() != null)
            conf.setNumReduceTasks(sink.getScheme().getNumSinkParts());
        else
            conf.setNumMapTasks(sink.getScheme().getNumSinkParts());
    }

    conf.setOutputKeyComparatorClass(TupleComparator.class);

    if (getGroup() == null) {
        conf.setNumReduceTasks(0); // disable reducers
    } else {
        // must set map output defaults when performing a reduce
        conf.setMapOutputKeyClass(Tuple.class);
        conf.setMapOutputValueClass(Tuple.class);

        // handles the case the groupby sort should be reversed
        if (getGroup().isSortReversed())
            conf.setOutputKeyComparatorClass(ReverseTupleComparator.class);

        addComparators(conf, "cascading.group.comparator", getGroup().getGroupingSelectors());

        if (getGroup().isGroupBy())
            addComparators(conf, "cascading.sort.comparator", getGroup().getSortingSelectors());

        if (!getGroup().isGroupBy()) {
            conf.setPartitionerClass(CoGroupingPartitioner.class);
            conf.setMapOutputKeyClass(IndexTuple.class); // allows groups to be sorted by index
            conf.setMapOutputValueClass(IndexTuple.class);
            conf.setOutputKeyComparatorClass(IndexTupleCoGroupingComparator.class); // sorts by group, then by index
            conf.setOutputValueGroupingComparator(CoGroupingComparator.class);
        }

        if (getGroup().isSorted()) {
            conf.setPartitionerClass(GroupingPartitioner.class);
            conf.setMapOutputKeyClass(TuplePair.class);

            if (getGroup().isSortReversed())
                conf.setOutputKeyComparatorClass(ReverseGroupingSortingComparator.class);
            else
                conf.setOutputKeyComparatorClass(GroupingSortingComparator.class);

            // no need to supply a reverse comparator, only equality is checked
            conf.setOutputValueGroupingComparator(GroupingComparator.class);
        }
    }

    // perform last so init above will pass to tasks
    conf.setInt("cascading.flow.step.id", id);
    conf.set("cascading.flow.step", Util.serializeBase64(this));

    return conf;
}

From source file:cascading.flow.hadoop.HadoopFlowStep.java

License:Open Source License

public JobConf createInitializedConfig(FlowProcess<JobConf> flowProcess, JobConf parentConfig) {
    JobConf conf = parentConfig == null ? new JobConf() : HadoopUtil.copyJobConf(parentConfig);

    // disable warning
    conf.setBoolean("mapred.used.genericoptionsparser", true);

    conf.setJobName(getStepDisplayName(conf.getInt("cascading.display.id.truncate", Util.ID_LENGTH)));

    conf.setOutputKeyClass(Tuple.class);
    conf.setOutputValueClass(Tuple.class);

    conf.setMapRunnerClass(FlowMapper.class);
    conf.setReducerClass(FlowReducer.class);

    // set for use by the shuffling phase
    TupleSerialization.setSerializations(conf);

    initFromSources(flowProcess, conf);//from w  w  w.  java  2 s.com

    initFromSink(flowProcess, conf);

    initFromTraps(flowProcess, conf);

    initFromStepConfigDef(conf);

    int numSinkParts = getSink().getScheme().getNumSinkParts();

    if (numSinkParts != 0) {
        // if no reducer, set num map tasks to control parts
        if (getGroup() != null)
            conf.setNumReduceTasks(numSinkParts);
        else
            conf.setNumMapTasks(numSinkParts);
    } else if (getGroup() != null) {
        int gatherPartitions = conf.getNumReduceTasks();

        if (gatherPartitions == 0)
            gatherPartitions = conf.getInt(FlowRuntimeProps.GATHER_PARTITIONS, 0);

        if (gatherPartitions == 0)
            throw new FlowException(getName(),
                    "a default number of gather partitions must be set, see FlowRuntimeProps");

        conf.setNumReduceTasks(gatherPartitions);
    }

    conf.setOutputKeyComparatorClass(TupleComparator.class);

    if (getGroup() == null) {
        conf.setNumReduceTasks(0); // disable reducers
    } else {
        // must set map output defaults when performing a reduce
        conf.setMapOutputKeyClass(Tuple.class);
        conf.setMapOutputValueClass(Tuple.class);
        conf.setPartitionerClass(GroupingPartitioner.class);

        // handles the case the groupby sort should be reversed
        if (getGroup().isSortReversed())
            conf.setOutputKeyComparatorClass(ReverseTupleComparator.class);

        addComparators(conf, "cascading.group.comparator", getGroup().getKeySelectors(), this, getGroup());

        if (getGroup().isGroupBy())
            addComparators(conf, "cascading.sort.comparator", getGroup().getSortingSelectors(), this,
                    getGroup());

        if (!getGroup().isGroupBy()) {
            conf.setPartitionerClass(CoGroupingPartitioner.class);
            conf.setMapOutputKeyClass(IndexTuple.class); // allows groups to be sorted by index
            conf.setMapOutputValueClass(IndexTuple.class);
            conf.setOutputKeyComparatorClass(IndexTupleCoGroupingComparator.class); // sorts by group, then by index
            conf.setOutputValueGroupingComparator(CoGroupingComparator.class);
        }

        if (getGroup().isSorted()) {
            conf.setPartitionerClass(GroupingSortingPartitioner.class);
            conf.setMapOutputKeyClass(TuplePair.class);

            if (getGroup().isSortReversed())
                conf.setOutputKeyComparatorClass(ReverseGroupingSortingComparator.class);
            else
                conf.setOutputKeyComparatorClass(GroupingSortingComparator.class);

            // no need to supply a reverse comparator, only equality is checked
            conf.setOutputValueGroupingComparator(GroupingComparator.class);
        }
    }

    // perform last so init above will pass to tasks
    String versionString = Version.getRelease();

    if (versionString != null)
        conf.set("cascading.version", versionString);

    conf.set(CASCADING_FLOW_STEP_ID, getID());
    conf.set("cascading.flow.step.num", Integer.toString(getOrdinal()));

    HadoopUtil.setIsInflow(conf);

    Iterator<FlowNode> iterator = getFlowNodeGraph().getTopologicalIterator();

    String mapState = pack(iterator.next(), conf);
    String reduceState = pack(iterator.hasNext() ? iterator.next() : null, conf);

    // hadoop 20.2 doesn't like dist cache when using local mode
    int maxSize = Short.MAX_VALUE;

    int length = mapState.length() + reduceState.length();

    if (isHadoopLocalMode(conf) || length < maxSize) // seems safe
    {
        conf.set("cascading.flow.step.node.map", mapState);

        if (!Util.isEmpty(reduceState))
            conf.set("cascading.flow.step.node.reduce", reduceState);
    } else {
        conf.set("cascading.flow.step.node.map.path",
                HadoopMRUtil.writeStateToDistCache(conf, getID(), "map", mapState));

        if (!Util.isEmpty(reduceState))
            conf.set("cascading.flow.step.node.reduce.path",
                    HadoopMRUtil.writeStateToDistCache(conf, getID(), "reduce", reduceState));
    }

    return conf;
}

From source file:cascading.flow.hadoop.MapReduceFlowPlatformTest.java

License:Open Source License

@Test
public void testFlow() throws IOException {
    getPlatform().copyFromLocal(inputFileApache);

    JobConf defaultConf = (JobConf) ((BaseHadoopPlatform) getPlatform()).getConfiguration();

    JobConf conf = new JobConf(defaultConf);
    conf.setJobName("mrflow");

    conf.setOutputKeyClass(LongWritable.class);
    conf.setOutputValueClass(Text.class);

    conf.setMapperClass(IdentityMapper.class);
    conf.setReducerClass(IdentityReducer.class);

    conf.setInputFormat(TextInputFormat.class);
    conf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(conf, new Path(inputFileApache));

    String outputPath = getOutputPath("flowTest");
    FileOutputFormat.setOutputPath(conf, new Path(outputPath));

    Flow flow = new MapReduceFlow("mrflow", conf, true);

    validateLength(new Hfs(new TextLine(), inputFileApache).openForRead(new HadoopFlowProcess(defaultConf)),
            10);//w w  w  .j a  v a  2 s .c  om

    flow.complete();

    validateLength(new Hfs(new TextLine(), outputPath).openForRead(new HadoopFlowProcess(defaultConf)), 10);
}

From source file:cascading.flow.hadoop.MapReduceFlowPlatformTest.java

License:Open Source License

@Test
public void testCascade() throws IOException {
    getPlatform().copyFromLocal(inputFileApache);

    // Setup two standard cascading flows that will generate the input for the first MapReduceFlow
    Tap source1 = new Hfs(new TextLine(new Fields("offset", "line")), remove(inputFileApache, false));
    String sinkPath4 = getOutputPath("flow4");
    Tap sink1 = new Hfs(new TextLine(new Fields("offset", "line")), remove(sinkPath4, true), SinkMode.REPLACE);
    Flow firstFlow = getPlatform().getFlowConnector(getProperties()).connect(source1, sink1,
            new Pipe("first-flow"));

    String sinkPath5 = getOutputPath("flow5");
    Tap sink2 = new Hfs(new TextLine(new Fields("offset", "line")), remove(sinkPath5, true), SinkMode.REPLACE);
    Flow secondFlow = getPlatform().getFlowConnector(getProperties()).connect(sink1, sink2,
            new Pipe("second-flow"));

    JobConf defaultConf = HadoopPlanner.createJobConf(getProperties());

    JobConf firstConf = new JobConf(defaultConf);
    firstConf.setJobName("first-mr");

    firstConf.setOutputKeyClass(LongWritable.class);
    firstConf.setOutputValueClass(Text.class);

    firstConf.setMapperClass(IdentityMapper.class);
    firstConf.setReducerClass(IdentityReducer.class);

    firstConf.setInputFormat(TextInputFormat.class);
    firstConf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(firstConf, new Path(remove(sinkPath5, true)));
    String sinkPath1 = getOutputPath("flow1");
    FileOutputFormat.setOutputPath(firstConf, new Path(remove(sinkPath1, true)));

    Flow firstMR = new MapReduceFlow(firstConf, true);

    JobConf secondConf = new JobConf(defaultConf);
    secondConf.setJobName("second-mr");

    secondConf.setOutputKeyClass(LongWritable.class);
    secondConf.setOutputValueClass(Text.class);

    secondConf.setMapperClass(IdentityMapper.class);
    secondConf.setReducerClass(IdentityReducer.class);

    secondConf.setInputFormat(TextInputFormat.class);
    secondConf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(secondConf, new Path(remove(sinkPath1, true)));
    String sinkPath2 = getOutputPath("flow2");
    FileOutputFormat.setOutputPath(secondConf, new Path(remove(sinkPath2, true)));

    Flow secondMR = new MapReduceFlow(secondConf, true);

    Job job = new Job(defaultConf);
    job.setJobName("third-mr");

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

    job.setMapperClass(org.apache.hadoop.mapreduce.Mapper.class);
    job.setReducerClass(org.apache.hadoop.mapreduce.Reducer.class);

    job.setInputFormatClass(org.apache.hadoop.mapreduce.lib.input.TextInputFormat.class);
    job.setOutputFormatClass(org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.class);
    job.getConfiguration().set("mapred.mapper.new-api", "true");
    job.getConfiguration().set("mapred.reducer.new-api", "true");

    org.apache.hadoop.mapreduce.lib.input.FileInputFormat.addInputPath(job, new Path(remove(sinkPath2, true)));
    String sinkPath3 = getOutputPath("flow3");
    org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.setOutputPath(job,
            new Path(remove(sinkPath3, true)));

    Flow thirdMR = new MapReduceFlow(new JobConf(job.getConfiguration()), true);

    CascadeConnector cascadeConnector = new CascadeConnector();

    // pass out of order
    Cascade cascade = cascadeConnector.connect(firstFlow, secondFlow, thirdMR, firstMR, secondMR);

    cascade.complete();// w w  w  .java  2  s  . c o m

    validateLength(new Hfs(new TextLine(), sinkPath3).openForRead(new HadoopFlowProcess(defaultConf)), 10);
}

From source file:cascading.flow.MapReduceFlowTest.java

License:Open Source License

public void testFlow() throws IOException {
    if (!new File(inputFileApache).exists())
        fail("data file not found");

    copyFromLocal(inputFileApache);//from w  w w . ja  va  2  s  .co m

    JobConf defaultConf = MultiMapReducePlanner.getJobConf(getProperties());

    JobConf conf = new JobConf(defaultConf);
    conf.setJobName("mrflow");

    conf.setOutputKeyClass(LongWritable.class);
    conf.setOutputValueClass(Text.class);

    conf.setMapperClass(IdentityMapper.class);
    conf.setReducerClass(IdentityReducer.class);

    conf.setInputFormat(TextInputFormat.class);
    conf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(conf, new Path(inputFileApache));
    FileOutputFormat.setOutputPath(conf, new Path(outputPath1));

    Flow flow = new MapReduceFlow("mrflow", conf, true);

    validateLength(flow.openSource(), 10);

    flow.complete();

    validateLength(flow.openSink(), 10);
}

From source file:cascading.flow.MapReduceFlowTest.java

License:Open Source License

public void testCascade() throws IOException {
    if (!new File(inputFileApache).exists())
        fail("data file not found");

    copyFromLocal(inputFileApache);//from   w w  w .j a v  a2 s .  c  o  m

    // Setup two standard cascading flows that will generate the input for the first MapReduceFlow
    Tap source1 = new Hfs(new TextLine(new Fields("offset", "line")), remove(inputFileApache, false));
    Tap sink1 = new Hfs(new TextLine(new Fields("offset", "line")), remove(outputPath4, true), true);
    Flow firstFlow = new FlowConnector(getProperties()).connect(source1, sink1, new Pipe("first-flow"));

    Tap sink2 = new Hfs(new TextLine(new Fields("offset", "line")), remove(outputPath5, true), true);
    Flow secondFlow = new FlowConnector(getProperties()).connect(sink1, sink2, new Pipe("second-flow"));

    JobConf defaultConf = MultiMapReducePlanner.getJobConf(getProperties());

    JobConf firstConf = new JobConf(defaultConf);
    firstConf.setJobName("first-mr");

    firstConf.setOutputKeyClass(LongWritable.class);
    firstConf.setOutputValueClass(Text.class);

    firstConf.setMapperClass(IdentityMapper.class);
    firstConf.setReducerClass(IdentityReducer.class);

    firstConf.setInputFormat(TextInputFormat.class);
    firstConf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(firstConf, new Path(remove(outputPath5, true)));
    FileOutputFormat.setOutputPath(firstConf, new Path(remove(outputPath1, true)));

    Flow firstMR = new MapReduceFlow(firstConf, true);

    JobConf secondConf = new JobConf(defaultConf);
    secondConf.setJobName("second-mr");

    secondConf.setOutputKeyClass(LongWritable.class);
    secondConf.setOutputValueClass(Text.class);

    secondConf.setMapperClass(IdentityMapper.class);
    secondConf.setReducerClass(IdentityReducer.class);

    secondConf.setInputFormat(TextInputFormat.class);
    secondConf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(secondConf, new Path(remove(outputPath1, true)));
    FileOutputFormat.setOutputPath(secondConf, new Path(remove(outputPath2, true)));

    Flow secondMR = new MapReduceFlow(secondConf, true);

    JobConf thirdConf = new JobConf(defaultConf);
    thirdConf.setJobName("third-mr");

    thirdConf.setOutputKeyClass(LongWritable.class);
    thirdConf.setOutputValueClass(Text.class);

    thirdConf.setMapperClass(IdentityMapper.class);
    thirdConf.setReducerClass(IdentityReducer.class);

    thirdConf.setInputFormat(TextInputFormat.class);
    thirdConf.setOutputFormat(TextOutputFormat.class);

    FileInputFormat.setInputPaths(thirdConf, new Path(remove(outputPath2, true)));
    FileOutputFormat.setOutputPath(thirdConf, new Path(remove(outputPath3, true)));

    Flow thirdMR = new MapReduceFlow(thirdConf, true);

    CascadeConnector cascadeConnector = new CascadeConnector();

    // pass out of order
    Cascade cascade = cascadeConnector.connect(firstFlow, secondFlow, thirdMR, firstMR, secondMR);

    //    cascade.writeDOT( "mrcascade.dot" );

    cascade.complete();

    validateLength(thirdMR.openSink(), 10);
}

From source file:cl.borrego.store.hadoop.SimpleClient.java

License:Open Source License

public void main() {
    // Create a new JobConf
    JobConf job = new JobConf(new Configuration(), SimpleClient.class);

    // Specify various job-specific parameters
    job.setJobName("myjob");
    // Submit the job, then poll for progress until the job is complete
    try {/*  www  . j  av  a  2s  .  c  o  m*/
        JobClient.runJob(job);
    } catch (IOException e) {
        e.printStackTrace(); //To change body of catch statement use File | Settings | File Templates.
    }

}

From source file:clusteringblocks.ClusteringBlocks.java

public int run(String[] args) throws Exception {
    Configuration conf = getConf();

    JobConf job = new JobConf(conf, ClusteringBlocks.class);

    Path in = new Path(args[0]);
    Path out = new Path(args[1]);
    FileInputFormat.setInputPaths(job, in);
    FileOutputFormat.setOutputPath(job, out);

    job.setJobName("ClusteringBlocks");
    job.setMapperClass(MapClass.class);
    job.setReducerClass(Reduce.class);

    job.setInputFormat(KeyValueTextInputFormat.class);
    job.setOutputFormat(TextOutputFormat.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    //   job.set("key.value.separator.in.input.line", "");

    JobClient.runJob(job);//from w w w.j  av a 2  s.  c om

    return 0;
}

From source file:cn.edu.xmu.dm.mapreduce.MultiFileWordCount.java

License:Apache License

public int run(String[] args) throws Exception {

    if (args.length < 2) {
        printUsage();//from w  w w  .j  av  a 2s. c o m
        return 1;
    }

    JobConf job = new JobConf(getConf(), MultiFileWordCount.class);
    job.setJobName("MultiFileWordCount");

    // set the InputFormat of the job to our InputFormat
    job.setInputFormat(MyInputFormat.class);

    // the keys are words (strings)
    job.setOutputKeyClass(Text.class);
    // the values are counts (ints)
    job.setOutputValueClass(LongWritable.class);

    // use the defined mapper
    job.setMapperClass(MapClass.class);
    // use the WordCount Reducer
    job.setCombinerClass(LongSumReducer.class);
    job.setReducerClass(LongSumReducer.class);

    FileInputFormat.addInputPaths(job, args[0]);
    FileOutputFormat.setOutputPath(job, new Path(args[1]));

    JobClient.runJob(job);

    return 0;
}