Example usage for org.apache.hadoop.mapreduce Job setJobName

List of usage examples for org.apache.hadoop.mapreduce Job setJobName

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Introduction

In this page you can find the example usage for org.apache.hadoop.mapreduce Job setJobName.

Prototype

public void setJobName(String name) throws IllegalStateException

Source Link

Document

Set the user-specified job name.

Usage

From source file:com.elex.dmp.vectorizer.DictionaryVectorizer.java

License:Apache License

/**
 * Count the frequencies of words in parallel using Map/Reduce. The input documents have to be in
 * {@link SequenceFile} format/* w w  w .ja  v a  2  s .  co  m*/
 */
private static void startWordCounting(Path input, Path output, Configuration baseConf, int minSupport)
        throws IOException, InterruptedException, ClassNotFoundException {

    Configuration conf = new Configuration(baseConf);
    // this conf parameter needs to be set enable serialisation of conf values
    conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,"
            + "org.apache.hadoop.io.serializer.WritableSerialization");
    conf.setInt(MIN_SUPPORT, minSupport);

    Job job = new Job(conf);

    job.setJobName("DictionaryVectorizer::WordCount: input-folder: " + input);
    job.setJarByClass(DictionaryVectorizer.class);

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

    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(TermCountMapper.class);

    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setCombinerClass(TermCountCombiner.class);
    job.setReducerClass(TermCountReducer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);

    HadoopUtil.delete(conf, output);

    boolean succeeded = job.waitForCompletion(true);
    if (!succeeded)
        throw new IllegalStateException("Job failed!");
}

From source file:com.elex.dmp.vectorizer.FixDictionaryVectorizer.java

License:Apache License

/**
 * Create a partial vector using a chunk of features from the input documents. The input documents has to be
 * in the {@link SequenceFile} format//from ww  w  .java 2 s. c  om
 * 
 * @param input
 *          input directory of the documents in {@link SequenceFile} format
 * @param baseConf
 *          job configuration
 * @param maxNGramSize
 *          maximum size of ngrams to generate
 * @param dictionaryFilePath
 *          location of the chunk of features and the id's
 * @param output
 *          output directory were the partial vectors have to be created
 * @param dimension
 * @param sequentialAccess
 *          output vectors should be optimized for sequential access
 * @param namedVectors
 *          output vectors should be named, retaining key (doc id) as a label
 * @param numReducers 
 *          the desired number of reducer tasks
 */
private static void makePartialVectors(Path input, Configuration baseConf, int maxNGramSize,
        Path dictionaryFilePath, Path output, int dimension, boolean sequentialAccess, boolean namedVectors,
        int numReducers) throws IOException, InterruptedException, ClassNotFoundException {

    Configuration conf = new Configuration(baseConf);
    // this conf parameter needs to be set enable serialisation of conf values
    conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,"
            + "org.apache.hadoop.io.serializer.WritableSerialization");
    conf.setInt(PartialVectorMerger.DIMENSION, dimension);
    conf.setBoolean(PartialVectorMerger.SEQUENTIAL_ACCESS, sequentialAccess);
    conf.setBoolean(PartialVectorMerger.NAMED_VECTOR, namedVectors);
    conf.setInt(MAX_NGRAMS, maxNGramSize);
    DistributedCache.setCacheFiles(new URI[] { dictionaryFilePath.toUri() }, conf);

    Job job = new Job(conf);
    job.setJobName("DictionaryVectorizer::MakePartialVectors: input-folder: " + input + ", dictionary-file: "
            + dictionaryFilePath);
    job.setJarByClass(FixDictionaryVectorizer.class);

    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(StringTuple.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(VectorWritable.class);
    FileInputFormat.setInputPaths(job, input);

    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(Mapper.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setReducerClass(TFPartialVectorReducer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    job.setNumReduceTasks(numReducers);

    HadoopUtil.delete(conf, output);

    boolean succeeded = job.waitForCompletion(true);
    if (!succeeded)
        throw new IllegalStateException("Job failed!");
}

From source file:com.elex.dmp.vectorizer.FixDictionaryVectorizer.java

License:Apache License

/**
 * Count the frequencies of words in parallel using Map/Reduce. The input documents have to be in
 * {@link SequenceFile} format/*ww  w.  ja v a 2 s .c  o m*/
 */
private static void startWordCounting(Path input, Path output, Configuration baseConf, int minSupport)
        throws IOException, InterruptedException, ClassNotFoundException {

    Configuration conf = new Configuration(baseConf);
    // this conf parameter needs to be set enable serialisation of conf values
    conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,"
            + "org.apache.hadoop.io.serializer.WritableSerialization");
    conf.setInt(MIN_SUPPORT, minSupport);

    Job job = new Job(conf);

    job.setJobName("DictionaryVectorizer::WordCount: input-folder: " + input);
    job.setJarByClass(FixDictionaryVectorizer.class);

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

    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(TermCountMapper.class);

    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setCombinerClass(TermCountCombiner.class);
    job.setReducerClass(TermCountReducer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);

    HadoopUtil.delete(conf, output);

    boolean succeeded = job.waitForCompletion(true);
    if (!succeeded)
        throw new IllegalStateException("Job failed!");
}

From source file:com.ema.hadoop.bestclient.BestClient.java

public static void main(String[] args) throws Exception {

    if (args.length != 4) {
        System.err.println("Usage: BestClient <input path> <output path> <date start> <date end>");
        System.exit(-1);/*from   w  w w. j a  v  a 2s.co  m*/
    }

    Job job = Job.getInstance();
    job.setJarByClass(BestClient.class);
    job.setJobName("Best client job");

    JobConf jobConf = (JobConf) job.getConfiguration();
    jobConf.setStrings("dates", args[2], args[3]);

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

    job.setMapperClass(BCMapper.class);
    job.setReducerClass(BCReducer.class);

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

    System.exit(job.waitForCompletion(true) ? 0 : 1);
}

From source file:com.ema.hadoop.wordcount.WordCount.java

public static void main(String[] args) throws Exception {

    if (args.length != 2) {
        System.err.println("Usage: WordCount <input path> <output path>");
        System.exit(-1);/*from  www.  jav a  2  s .  com*/
    }

    Job job = Job.getInstance();
    job.setJarByClass(WordCount.class);
    job.setJobName("Word count job");

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

    job.setMapperClass(WCMapper.class);
    job.setReducerClass(WCReducer.class);

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

    System.exit(job.waitForCompletion(true) ? 0 : 1);
}

From source file:com.ema.hadoop.wordcount.WordCount_cache.java

public static void main(String[] args) throws Exception {

    if (args.length != 2) {
        System.err.println("Usage: WordCount <input path> <output path>");
        System.exit(-1);//from   w w  w.  j  ava  2 s .  c  om
    }

    // First we write the stop word list
    // it could also be a file manually loaded into HDFS

    String[] stopwords = { "the", "a" };
    Configuration configuration = new Configuration();
    FileSystem hdfs = FileSystem.get(new URI("hdfs://localhost:9000"), configuration);
    Path file = new Path("hdfs://localhost:9000/user/student/stop_words.txt");
    if (hdfs.exists(file)) {
        hdfs.delete(file, true);
    }
    OutputStream os = hdfs.create(file, new Progressable() {
        @Override
        public void progress() {
            out.println("...bytes written");
        }
    });
    BufferedWriter br = new BufferedWriter(new OutputStreamWriter(os, "UTF-8"));
    for (String w : stopwords) {
        br.write(w + "\n");
    }

    br.close();
    hdfs.close();

    Job job = Job.getInstance();
    job.addCacheFile(new Path("hdfs://localhost:9000/user/student/stop_words.txt").toUri());

    job.setJarByClass(WordCount_cache.class);
    job.setJobName("Word count job");

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

    job.setMapperClass(WCMapper_cache.class);
    job.setReducerClass(WCReducer.class);

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

    System.exit(job.waitForCompletion(true) ? 0 : 1);
}

From source file:com.examples.ch03.ParseWeblogs_Ex_1.java

public int run(String[] args) throws Exception {
    Path inputPath = new Path("apache_clf.txt");
    Path outputPath = new Path("output");
    Configuration conf = getConf();
    Job weblogJob = Job.getInstance(conf);
    weblogJob.setJobName("Weblog Transformer");
    weblogJob.setJarByClass(getClass());
    weblogJob.setNumReduceTasks(0);//from   www  .ja  v a  2s  . co  m

    weblogJob.setMapperClass(CLFMapper_Ex_1.class);
    weblogJob.setMapOutputKeyClass(Text.class);
    weblogJob.setMapOutputValueClass(Text.class);

    weblogJob.setOutputKeyClass(Text.class);
    weblogJob.setOutputValueClass(Text.class);

    weblogJob.setInputFormatClass(TextInputFormat.class);
    weblogJob.setOutputFormatClass(TextOutputFormat.class);

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

    if (weblogJob.waitForCompletion(true)) {
        return 0;
    }
    return 1;
}

From source file:com.fanlehai.hadoop.join.CompositeJoin.java

License:Apache License

/**
 * The main driver for sort program. Invoke this method to submit the
 * map/reduce job./* w  ww . j  a v a  2 s . com*/
 * 
 * @throws IOException
 *             When there is communication problems with the job tracker.
 */

@SuppressWarnings("rawtypes")
public int run(String[] args) throws Exception {
    Configuration conf = getConf();
    JobClient client = new JobClient(conf);
    ClusterStatus cluster = client.getClusterStatus();
    int num_reduces = (int) (cluster.getMaxReduceTasks() * 0.9);
    String join_reduces = conf.get(REDUCES_PER_HOST);
    if (join_reduces != null) {
        num_reduces = cluster.getTaskTrackers() * Integer.parseInt(join_reduces);
    }
    Job job = Job.getInstance(conf);
    job.setJobName("join");
    job.setJarByClass(CompositeJoin.class);

    job.setMapperClass(Mapper.class);
    job.setReducerClass(Reducer.class);

    Class<? extends InputFormat> inputFormatClass = KeyValueTextInputFormat.class;// SequenceFileInputFormat.class;
    Class<? extends OutputFormat> outputFormatClass = SequenceFileOutputFormat.class;
    Class<? extends WritableComparable> outputKeyClass = Text.class;// BytesWritable.class;
    Class<? extends Writable> outputValueClass = Text.class;//TupleWritable.class;
    String op = "inner";
    List<String> otherArgs = new ArrayList<String>();
    for (int i = 0; i < args.length; ++i) {
        try {
            if ("-r".equals(args[i])) {
                num_reduces = Integer.parseInt(args[++i]);
            } else if ("-inFormat".equals(args[i])) {
                inputFormatClass = Class.forName(args[++i]).asSubclass(InputFormat.class);
            } else if ("-outFormat".equals(args[i])) {
                outputFormatClass = Class.forName(args[++i]).asSubclass(OutputFormat.class);
            } else if ("-outKey".equals(args[i])) {
                outputKeyClass = Class.forName(args[++i]).asSubclass(WritableComparable.class);
            } else if ("-outValue".equals(args[i])) {
                outputValueClass = Class.forName(args[++i]).asSubclass(Writable.class);
            } else if ("-joinOp".equals(args[i])) {
                op = args[++i];
            } else {
                otherArgs.add(args[i]);
            }
        } catch (NumberFormatException except) {
            System.out.println("ERROR: Integer expected instead of " + args[i]);
            return printUsage();
        } catch (ArrayIndexOutOfBoundsException except) {
            System.out.println("ERROR: Required parameter missing from " + args[i - 1]);
            return printUsage(); // exits
        }
    }

    // Set user-supplied (possibly default) job configs
    job.setNumReduceTasks(num_reduces);

    if (otherArgs.size() < 2) {
        System.out.println("ERROR: Wrong number of parameters: ");
        return printUsage();
    }

    String strOut = otherArgs.remove(otherArgs.size() - 1);
    FileSystem.get(new Configuration()).delete(new Path(strOut), true);

    FileOutputFormat.setOutputPath(job, new Path(strOut));
    List<Path> plist = new ArrayList<Path>(otherArgs.size());
    for (String s : otherArgs) {
        plist.add(new Path(s));
    }

    job.setInputFormatClass(CompositeInputFormat.class);
    job.getConfiguration().set(CompositeInputFormat.JOIN_EXPR,
            CompositeInputFormat.compose(op, inputFormatClass, plist.toArray(new Path[0])));
    job.setOutputFormatClass(outputFormatClass);

    job.setMapperClass(MapComposite.class);

    job.setOutputKeyClass(outputKeyClass);
    job.setOutputValueClass(outputValueClass);

    Date startTime = new Date();
    System.out.println("Job started: " + startTime);
    int ret = job.waitForCompletion(true) ? 0 : 1;
    Date end_time = new Date();
    System.out.println("Job ended: " + end_time);
    System.out.println("The job took " + (end_time.getTime() - startTime.getTime()) / 1000 + " seconds.");
    return ret;
}

From source file:com.fanlehai.hadoop.serialize.avro.MapReduceAvroWordCount.java

License:Apache License

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

    if (args.length != 2) {
        printUsage();/*from w  w  w  .ja v a2s .  c  om*/
    }

    FileSystem.get(new Configuration()).delete(new Path(args[1]), true);
    Job job = Job.getInstance(super.getConf(), "AvroWordCount");

    job.setJarByClass(MapReduceAvroWordCount.class);
    job.setJobName("AvroWordCount");

    // We call setOutputSchema first so we can override the configuration
    // parameters it sets
    AvroJob.setOutputKeySchema(job, Pair.getPairSchema(Schema.create(Type.STRING), Schema.create(Type.INT)));
    job.setOutputValueClass(NullWritable.class);

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

    job.setInputFormatClass(TextInputFormat.class);

    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(IntWritable.class);
    job.setSortComparatorClass(Text.Comparator.class);

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

    return job.waitForCompletion(true) ? 1 : 0;
}

From source file:com.fanlehai.hadoop.serialize.avro.MapReduceColorCount.java

License:Apache License

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

    if (args.length != 2) {
        printUsage();//from ww  w  .  j a  v a  2s  .c  o  m
    }

    FileSystem.get(new Configuration()).delete(new Path(args[1]), true);
    Job job = Job.getInstance(super.getConf(), "MapReduceAvroWordCount");

    job.setJarByClass(MapReduceColorCount.class);
    job.setJobName("Color Count");

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

    job.setInputFormatClass(AvroKeyInputFormat.class);
    job.setMapperClass(ColorCountMapper.class);
    AvroJob.setInputKeySchema(job, User.getClassSchema());
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(IntWritable.class);

    job.setOutputFormatClass(AvroKeyValueOutputFormat.class);
    job.setReducerClass(ColorCountReducer.class);
    AvroJob.setOutputKeySchema(job, Schema.create(Schema.Type.STRING));
    AvroJob.setOutputValueSchema(job, Schema.create(Schema.Type.INT));

    return job.waitForCompletion(true) ? 1 : 0;
}