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

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

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Introduction

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

Prototype

public void setInputFormatClass(Class<? extends InputFormat> cls) throws IllegalStateException

Source Link

Document

Set the InputFormat for the job.

Usage

From source file:com.datasalt.pangool.tuplemr.mapred.lib.input.PangoolMultipleInputs.java

License:Apache License

private static void addInputPath(Job job, Path path, String inputFormatInstance) {
    /*/*from   w w  w  .  j a  v  a  2s.  co  m*/
     * Only internal -> not allowed to add inputs without associated InputProcessor files
     */
    String inputFormatMapping = path.toString() + ";" + inputFormatInstance;
    Configuration conf = job.getConfiguration();
    String inputFormats = conf.get(PANGOOL_INPUT_DIR_FORMATS_CONF);
    conf.set(PANGOOL_INPUT_DIR_FORMATS_CONF,
            inputFormats == null ? inputFormatMapping : inputFormats + "," + inputFormatMapping);

    job.setInputFormatClass(DelegatingInputFormat.class);
}

From source file:com.datasalt.pangool.tuplemr.mapred.lib.output.TestTupleInputOutputFormat.java

License:Apache License

public void testSplits(long maxSplitSize, int generatedRows) throws IOException, InterruptedException,
        IllegalArgumentException, SecurityException, ClassNotFoundException, InstantiationException,
        IllegalAccessException, InvocationTargetException, NoSuchMethodException {
    logger.info("Testing maxSplitSize: " + maxSplitSize + " and generatedRows:" + generatedRows);
    FileSystem fS = FileSystem.get(getConf());
    Random r = new Random(1);
    Schema schema = new Schema("schema", Fields.parse("i:int,s:string"));
    ITuple tuple = new Tuple(schema);

    Path outPath = new Path(OUT);
    TupleFile.Writer writer = new TupleFile.Writer(FileSystem.get(getConf()), getConf(), outPath, schema);
    for (int i = 0; i < generatedRows; i++) {
        tuple.set("i", r.nextInt());
        tuple.set("s", r.nextLong() + "");
        writer.append(tuple);/*from   w  w w  .j a va  2  s .  c  om*/
    }
    writer.close();

    TupleInputFormat format = ReflectionUtils.newInstance(TupleInputFormat.class, getConf());
    Job job = new Job(getConf());
    FileInputFormat.setInputPaths(job, outPath);
    logger.info("Using max input split size: " + maxSplitSize);
    FileInputFormat.setMaxInputSplitSize(job, maxSplitSize);
    job.setInputFormatClass(FileInputFormat.class);

    // Read all the splits and count. The number of read rows must
    // be the same than the written ones.
    int count = 0;
    for (InputSplit split : format.getSplits(job)) {
        TaskAttemptID attemptId = new TaskAttemptID(new TaskID(), 1);
        TaskAttemptContext attemptContext = TaskAttemptContextFactory.get(getConf(), attemptId);
        logger.info("Sampling split: " + split);
        RecordReader<ITuple, NullWritable> reader = format.createRecordReader(split, attemptContext);
        reader.initialize(split, attemptContext);
        while (reader.nextKeyValue()) {
            tuple = reader.getCurrentKey();
            count++;
        }
        reader.close();
    }

    assertEquals(generatedRows, count);

    HadoopUtils.deleteIfExists(fS, outPath);
}

From source file:com.digitalpebble.behemoth.mahout.BehemothDocumentProcessor.java

License:Apache License

/**
 * Convert the input documents into token array using the
 * {@link StringTuple} The input documents has to be in the
 * {@link org.apache.hadoop.io.SequenceFile} format
 * /*w w  w  .  jav  a  2s  . c o m*/
 * @param input
 *            input directory of the documents in
 *            {@link org.apache.hadoop.io.SequenceFile} format
 * @param output
 *            output directory were the {@link StringTuple} token array of
 *            each document has to be created
 * @param type
 *            The annotation type representing the tokens
 * @param feature
 *            The name of the features holding the token value
 * @throws IOException
 * @throws ClassNotFoundException
 * @throws InterruptedException
 */
public static void tokenizeDocuments(Path input, String type, String feature, Path output)
        throws IOException, InterruptedException, ClassNotFoundException {
    Configuration conf = new Configuration();
    // 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.set(TOKEN_TYPE, type);
    conf.set(FEATURE_NAME, feature);

    Job job = new Job(conf);
    job.setJobName("DocumentProcessor::BehemothTokenizer: input-folder: " + input);
    job.setJarByClass(BehemothDocumentProcessor.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(StringTuple.class);
    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(BehemothTokenizerMapper.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setNumReduceTasks(0);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    HadoopUtil.delete(conf, output);

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

From source file:com.digitalpebble.behemoth.mahout.BehemothDocumentProcessor.java

License:Apache License

/**
 * Convert the input documents into token array using the
 * {@link StringTuple} The input documents has to be in the
 * {@link org.apache.hadoop.io.SequenceFile} format
 * //  www.j  a v  a2  s  .  c om
 * @param input
 *            input directory of the documents in
 *            {@link org.apache.hadoop.io.SequenceFile} format
 * @param output
 *            output directory were the {@link StringTuple} token array of
 *            each document has to be created
 * @param analyzerClass
 *            The Lucene {@link Analyzer} for tokenizing the UTF-8 text
 */
public static void tokenizeDocuments(Path input, Class<? extends Analyzer> analyzerClass, Path output,
        Configuration baseConf) 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.set(ANALYZER_CLASS, analyzerClass.getName());

    Job job = new Job(conf);
    job.setJobName("DocumentProcessor::LuceneTokenizer: input-folder: " + input);
    job.setJarByClass(BehemothDocumentProcessor.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(StringTuple.class);
    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(LuceneTokenizerMapper.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setNumReduceTasks(0);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    HadoopUtil.delete(conf, output);

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

}

From source file:com.digitalpebble.behemoth.mahout.BehemothDocumentProcessor.java

License:Apache License

public static void dumpLabels(Path input, Path output, Configuration baseConf)
        throws IOException, InterruptedException, ClassNotFoundException {
    Configuration conf = new Configuration(baseConf);
    // this conf parameter needs to be set enable serialisation of conf
    // values//from   www  .j  a  v a  2s  .c  o  m
    conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,"
            + "org.apache.hadoop.io.serializer.WritableSerialization");

    Job job = new Job(conf);
    job.setJobName("DocumentProcessor::LabelDumper: input-folder: " + input);
    job.setJarByClass(BehemothDocumentProcessor.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);
    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(BehemothLabelMapper.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setNumReduceTasks(0);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    HadoopUtil.delete(conf, output);

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

}

From source file:com.digitalpebble.behemoth.mahout.DocumentProcessor.java

License:Apache License

/**
 * Convert the input documents into token array using the
 * {@link StringTuple} The input documents has to be in the
 * {@link org.apache.hadoop.io.SequenceFile} format
 * // w  w w.j  a va  2  s  . c o  m
 * @param input
 *            input directory of the documents in
 *            {@link org.apache.hadoop.io.SequenceFile} format
 * @param output
 *            output directory were the {@link StringTuple} token array of
 *            each document has to be created
 * @param type
 *            The annotation type representing the tokens
 * @param feature
 *            The name of the features holding the token value
 * @throws IOException
 * @throws ClassNotFoundException
 * @throws InterruptedException
 */
public static void tokenizeDocuments(Path input, String type, String feature, Path output)
        throws IOException, InterruptedException, ClassNotFoundException {
    Configuration conf = new Configuration();
    // 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.set(TOKEN_TYPE, type);
    conf.set(FEATURE_NAME, feature);

    Job job = new Job(conf);
    job.setJobName("DocumentProcessor::DocumentTokenizer: input-folder: " + input);
    job.setJarByClass(DocumentProcessor.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(StringTuple.class);
    FileInputFormat.setInputPaths(job, input);
    FileOutputFormat.setOutputPath(job, output);

    job.setMapperClass(SequenceFileTokenizerMapper.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setNumReduceTasks(0);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    HadoopUtil.delete(conf, output);

    job.waitForCompletion(true);
}

From source file:com.elex.dmp.lda.CVB0Driver.java

License:Apache License

private static double calculatePerplexity(Configuration conf, Path corpusPath, Path modelPath, int iteration)
        throws IOException, ClassNotFoundException, InterruptedException {
    String jobName = "Calculating perplexity for " + modelPath;
    log.info("About to run: " + jobName);
    Job job = new Job(conf, jobName);
    job.setJarByClass(CachingCVB0PerplexityMapper.class);
    job.setMapperClass(CachingCVB0PerplexityMapper.class);
    job.setCombinerClass(DualDoubleSumReducer.class);
    job.setReducerClass(DualDoubleSumReducer.class);
    job.setNumReduceTasks(1);//from w w w .ja  va 2s .c o  m
    job.setOutputKeyClass(DoubleWritable.class);
    job.setOutputValueClass(DoubleWritable.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    FileInputFormat.addInputPath(job, corpusPath);
    Path outputPath = perplexityPath(modelPath.getParent(), iteration);
    FileOutputFormat.setOutputPath(job, outputPath);
    setModelPaths(job, modelPath);
    HadoopUtil.delete(conf, outputPath);
    if (!job.waitForCompletion(true)) {
        throw new InterruptedException("Failed to calculate perplexity for: " + modelPath);
    }
    return readPerplexity(conf, modelPath.getParent(), iteration);
}

From source file:com.elex.dmp.lda.CVB0Driver.java

License:Apache License

private static Job writeTopicModel(Configuration conf, Path modelInput, Path output)
        throws IOException, InterruptedException, ClassNotFoundException {
    String jobName = String.format("Writing final topic/term distributions from %s to %s", modelInput, output);
    log.info("About to run: " + jobName);
    Job job = new Job(conf, jobName);
    job.setJarByClass(CVB0Driver.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setMapperClass(CVB0TopicTermVectorNormalizerMapper.class);
    job.setNumReduceTasks(0);/*from   ww  w .  j a  va2s  . c  o m*/
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(VectorWritable.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    FileInputFormat.addInputPath(job, modelInput);
    FileOutputFormat.setOutputPath(job, output);
    job.submit();
    return job;
}

From source file:com.elex.dmp.lda.CVB0Driver.java

License:Apache License

private static Job writeDocTopicInference(Configuration conf, Path corpus, Path modelInput, Path output)
        throws IOException, ClassNotFoundException, InterruptedException {
    String jobName = String.format("Writing final document/topic inference from %s to %s", corpus, output);
    log.info("About to run: " + jobName);
    Job job = new Job(conf, jobName);
    job.setMapperClass(CVB0DocInferenceMapper.class);
    job.setNumReduceTasks(0);/*from   www  .j a  v a  2s.  c  om*/
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(VectorWritable.class);
    FileSystem fs = FileSystem.get(corpus.toUri(), conf);
    if (modelInput != null && fs.exists(modelInput)) {
        FileStatus[] statuses = fs.listStatus(modelInput, PathFilters.partFilter());
        URI[] modelUris = new URI[statuses.length];
        for (int i = 0; i < statuses.length; i++) {
            modelUris[i] = statuses[i].getPath().toUri();
        }
        DistributedCache.setCacheFiles(modelUris, conf);
    }
    setModelPaths(job, modelInput);//bug:mahout-1147
    FileInputFormat.addInputPath(job, corpus);
    FileOutputFormat.setOutputPath(job, output);
    job.setJarByClass(CVB0Driver.class);
    job.submit();
    return job;
}

From source file:com.elex.dmp.lda.CVB0Driver.java

License:Apache License

public static void runIteration(Configuration conf, Path corpusInput, Path modelInput, Path modelOutput,
        int iterationNumber, int maxIterations, int numReduceTasks)
        throws IOException, ClassNotFoundException, InterruptedException {
    String jobName = String.format("Iteration %d of %d, input path: %s", iterationNumber, maxIterations,
            modelInput);//from w  w  w .j av a 2 s  .c om
    log.info("About to run: " + jobName);
    Job job = new Job(conf, jobName);
    job.setJarByClass(CVB0Driver.class);
    job.setMapperClass(CachingCVB0Mapper.class);
    job.setCombinerClass(VectorSumReducer.class);
    job.setReducerClass(VectorSumReducer.class);
    job.setNumReduceTasks(numReduceTasks);
    job.setOutputKeyClass(Text.class);//0.7IntWritable
    job.setOutputValueClass(VectorWritable.class);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    FileInputFormat.addInputPath(job, corpusInput);
    FileOutputFormat.setOutputPath(job, modelOutput);
    setModelPaths(job, modelInput);
    HadoopUtil.delete(conf, modelOutput);
    if (!job.waitForCompletion(true)) {
        throw new InterruptedException(
                String.format("Failed to complete iteration %d stage 1", iterationNumber));
    }
}