Example usage for org.apache.hadoop.conf Configuration set

Introduction

In this page you can find the example usage for org.apache.hadoop.conf Configuration set.

Prototype

public void set(String name, String value) 

Source Link

Document

Set the value of the name property.

Usage

From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setInputColumnFamilies(Configuration conf, String inputKeyspace,
        List<String> inputColumnFamilies) {
    String cf = "";
    if (inputKeyspace == null) {
        throw new UnsupportedOperationException("keyspace may not be null");
    }//w ww.  j  a  va2s . co m
    if (cf == null) {
        throw new UnsupportedOperationException("columnfamily may not be null");
    }

    conf.set(INPUT_KEYSPACE_CONFIG, inputKeyspace);
    conf.setStrings(INPUT_COLUMNFAMILIES_CONFIG,
            inputColumnFamilies.toArray(new String[inputColumnFamilies.size()]));
}

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From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setConsistencyLevel(Configuration conf, ConsistencyLevel cl) {
    conf.set(CassandraConfigHelper.CASSANDRA_CONSISTENCYLEVEL_READ, cl.name());
    conf.set(CassandraConfigHelper.CASSANDRA_CONSISTENCYLEVEL_WRITE, cl.name());
}

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From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setDefaultWriteConsistencyLevel(Configuration configuration) {
    if (configuration.get(CASSANDRA_CONSISTENCYLEVEL_WRITE) == null) {
        configuration.set(CASSANDRA_CONSISTENCYLEVEL_WRITE, DEFAULT_CONSISTENCY_LEVEL);
    }/*ww w  .j av  a2 s  . c o  m*/
}

---

From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setDefaultReadConsistencyLevel(Configuration configuration) {
    if (configuration.get(CASSANDRA_CONSISTENCYLEVEL_READ) == null) {
        configuration.set(CASSANDRA_CONSISTENCYLEVEL_READ, DEFAULT_CONSISTENCY_LEVEL);
    }/*from  ww  w. j  a v  a 2 s .c o m*/
}

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From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setOutputKeyspaceUserName(Configuration configuration, String keyspace, String userName) {
    configuration.set(OUTPUT_KEYSPACE_USER_NAME_KEY + ":" + keyspace, userName);
}

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From source file:andromache.config.CassandraConfigHelper.java

License:Apache License

public static void setOutputKeyspacePassword(Configuration configuration, String keyspace, String password) {
    configuration.set(OUTPUT_KEYSPACE_USER_PASSWORD_KEY + ":" + keyspace, password);
}

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From source file:ar.edu.ungs.garules.CensusJob.java

License:Apache License

/**
 * Main -> Ejecucion del proceso/* w ww.  ja  v a 2  s .  com*/
 * @param args
 * @throws Exception
 */
public static void main(String[] args) throws Exception {

    long time = System.currentTimeMillis();
    Individual<BitSet> bestInd = null;
    if (args.length != 2)
        args = DEFAULT_ARGS;

    // Preparacion del GA
    // --------------------------------------------------------------------------------------------------------------
    Set<Individual<BitSet>> bestIndividuals = new HashSet<Individual<BitSet>>();
    List<Gene> genes = new ArrayList<Gene>();
    genes.add(genCondicionACampo);
    genes.add(genCondicionAOperador);
    genes.add(genCondicionAValor);
    genes.add(genCondicionBPresente);
    genes.add(genCondicionBCampo);
    genes.add(genCondicionBOperador);
    genes.add(genCondicionBValor);
    genes.add(genCondicionCPresente);
    genes.add(genCondicionCCampo);
    genes.add(genCondicionCOperador);
    genes.add(genCondicionCValor);
    genes.add(genPrediccionCampo);
    genes.add(genPrediccionValor);

    Map<Gene, Ribosome<BitSet>> translators = new HashMap<Gene, Ribosome<BitSet>>();
    for (Gene gene : genes)
        translators.put(gene, new BitSetToIntegerRibosome(0));

    Genome<BitSet> genome = new BitSetGenome("Chromosome 1", genes, translators);

    Parameter<BitSet> par = new Parameter<BitSet>(0.035, 0.9, 200, new DescendantAcceptEvaluator<BitSet>(),
            new CensusFitnessEvaluator(), new BitSetOnePointCrossover(), new BitSetFlipMutator(), null,
            new BitSetRandomPopulationInitializer(), null, new ProbabilisticRouletteSelector(),
            new GlobalSinglePopulation<BitSet>(genome), 500, 100d, new BitSetMorphogenesisAgent(), genome);

    ParallelFitnessEvaluationGA<BitSet> ga = new ParallelFitnessEvaluationGA<BitSet>(par);
    ga.init();
    // --------------------------------------------------------------------------------------------------------------
    // Fin de Preparacion del GA

    // Itera hasta el maximo de generaciones permitidas 
    for (int i = 0; i < par.getMaxGenerations(); i++) {
        ga.initGeneration();
        Configuration conf = new Configuration();

        // Debug
        //showPopulation(ga.getPopulation());
        //System.out.println((System.currentTimeMillis()-time)/1000 + "s transcurridos desde el inicio");

        // Pasamos como parmetro las condiciones a evaluar
        Iterator<Individual<BitSet>> ite = ga.getPopulation().iterator();
        int contador = 0;
        Set<String> expUnicas = new HashSet<String>();
        while (ite.hasNext()) {
            Individual<BitSet> ind = ite.next();
            String rep = RuleStringAdaptor.adapt(RuleAdaptor.adapt(ind));
            expUnicas.add(rep);
        }
        for (String rep : expUnicas)
            if (ocurrencias.get(rep) == null) {
                conf.set(String.valueOf(contador), rep);
                contador++;
            }

        // Configuracion del job i
        Job job = new Job(conf, "GA rules - Generation " + i);
        job.setJarByClass(CensusJob.class);
        job.setMapperClass(CensusMapper.class);
        job.setCombinerClass(CensusReducer.class);
        job.setReducerClass(CensusReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        job.setOutputFormatClass(SequenceFileOutputFormat.class);
        FileInputFormat.addInputPath(job, new Path(args[0]));
        SequenceFileOutputFormat.setOutputPath(job, new Path(args[1] + "g" + i));

        // Corrida del trabajo map-reduce representando a la generacion i
        job.waitForCompletion(true);

        // Aca calculamos el fitness en base a lo que arrojo el job y si hay un mejor individuo lo agregamos al set de mejores individuos....  
        llenarOcurrencias(conf, args[1] + "g" + i);

        // Corremos GA para la generacion.
        Individual<BitSet> winnerGen = ga.run(new CensusFitnessEvaluator(ocurrencias));

        // Mantenemos los mejores individuos
        if (bestInd == null) {
            bestInd = winnerGen;
            bestIndividuals.add(winnerGen);
        } else if (winnerGen.getFitness() > bestInd.getFitness()) {
            bestInd = winnerGen;
            bestIndividuals.add(winnerGen);
        }

        // Debug
        System.out.println("Mejor Individuo Generacion " + i + " => " + RuleAdaptor.adapt(bestInd)
                + " => Fitness = " + bestInd.getFitness());

    }

    // Ordenamos y mostramos los mejores individuos
    List<Individual<BitSet>> bestIndList = new ArrayList<Individual<BitSet>>(bestIndividuals);
    Collections.sort(bestIndList, new Comparator<Individual<BitSet>>() {
        public int compare(Individual<BitSet> o1, Individual<BitSet> o2) {
            return (o1.getFitness() > o2.getFitness() ? -1 : (o1.getFitness() == o2.getFitness() ? 0 : 1));
        }
    });
    showPopulation(bestIndList);
    System.out.println("Tiempo total de corrida " + (System.currentTimeMillis() - time) / 1000 + "s");

}

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From source file:at.ac.tuwien.infosys.jcloudscale.datastore.driver.hbase.HbaseConfig.java

License:Apache License

/**
 * Create the HBase Configuration for a given datastore
 *
 * @param datastore the given datastore/*  ww w  . ja  va2 s.  c o m*/
 * @return the HBase Configuration
 */
public static Configuration getConfig(Datastore datastore) {
    Configuration configuration = HBaseConfiguration.create();
    configuration.clear();
    configuration.set("hbase.zookeeper.quorum", datastore.getHost());
    return configuration;
}

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From source file:at.illecker.hama.hybrid.examples.hellohybrid.HelloHybridBSP.java

License:Apache License

public static void main(String[] args) throws InterruptedException, IOException, ClassNotFoundException {

    Configuration conf = new HamaConfiguration();

    if (args.length > 0) {
        if (args.length == 1) {
            conf.setInt("bsp.peers.num", Integer.parseInt(args[0]));
        } else {/*from  ww w.jav  a2 s . com*/
            System.out.println("Wrong argument size!");
            System.out.println("    Argument1=numBspTask");
            return;
        }
    } else {
        // BSPJobClient jobClient = new BSPJobClient(conf);
        // ClusterStatus cluster = jobClient.getClusterStatus(true);
        // job.setNumBspTask(cluster.getMaxTasks());

        conf.setInt("bsp.peers.num", 2); // 1 CPU and 1 GPU
    }
    // Enable one GPU task
    conf.setInt("bsp.peers.gpu.num", 1);
    conf.setBoolean("hama.pipes.logging", true);

    LOG.info("NumBspTask: " + conf.getInt("bsp.peers.num", 0));
    LOG.info("NumBspGpuTask: " + conf.getInt("bsp.peers.gpu.num", 0));
    LOG.info("bsp.tasks.maximum: " + conf.get("bsp.tasks.maximum"));
    LOG.info("inputPath: " + CONF_INPUT_DIR);
    LOG.info("outputPath: " + CONF_OUTPUT_DIR);

    Path example = new Path(CONF_INPUT_DIR.getParent(), "example.seq");
    conf.set(CONF_EXAMPLE_PATH, example.toString());
    LOG.info("exampleFile: " + example.toString());

    prepareInput(conf, CONF_INPUT_DIR, example, CONF_N);

    BSPJob job = createHelloHybridBSPConf(conf, CONF_INPUT_DIR, CONF_OUTPUT_DIR);

    long startTime = System.currentTimeMillis();
    if (job.waitForCompletion(true)) {
        LOG.info("Job Finished in " + (System.currentTimeMillis() - startTime) / 1000.0 + " seconds");

        // Print input files
        // printOutput(job, CONF_INPUT_DIR);
        // printOutput(job, example);

        // Print output
        printOutput(job, FileOutputFormat.getOutputPath(job));
    }
}

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From source file:at.illecker.hama.hybrid.examples.kmeans.KMeansHybridBSP.java

License:Apache License

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

    // Defaults/*from  ww  w.  j  a  v a 2 s  .c o  m*/
    int numBspTask = 1;
    int numGpuBspTask = 1;
    int blockSize = BLOCK_SIZE;
    int gridSize = GRID_SIZE;
    long n = 10; // input vectors
    int k = 3; // start vectors
    int vectorDimension = 2;
    int maxIteration = 10;
    boolean useTestExampleInput = false;
    boolean isDebugging = false;
    boolean timeMeasurement = false;
    int GPUPercentage = 80;

    Configuration conf = new HamaConfiguration();
    FileSystem fs = FileSystem.get(conf);

    // Set numBspTask to maxTasks
    // BSPJobClient jobClient = new BSPJobClient(conf);
    // ClusterStatus cluster = jobClient.getClusterStatus(true);
    // numBspTask = cluster.getMaxTasks();

    if (args.length > 0) {
        if (args.length == 12) {
            numBspTask = Integer.parseInt(args[0]);
            numGpuBspTask = Integer.parseInt(args[1]);
            blockSize = Integer.parseInt(args[2]);
            gridSize = Integer.parseInt(args[3]);
            n = Long.parseLong(args[4]);
            k = Integer.parseInt(args[5]);
            vectorDimension = Integer.parseInt(args[6]);
            maxIteration = Integer.parseInt(args[7]);
            useTestExampleInput = Boolean.parseBoolean(args[8]);
            GPUPercentage = Integer.parseInt(args[9]);
            isDebugging = Boolean.parseBoolean(args[10]);
            timeMeasurement = Boolean.parseBoolean(args[11]);

        } else {
            System.out.println("Wrong argument size!");
            System.out.println("    Argument1=numBspTask");
            System.out.println("    Argument2=numGpuBspTask");
            System.out.println("    Argument3=blockSize");
            System.out.println("    Argument4=gridSize");
            System.out.println("    Argument5=n | Number of input vectors (" + n + ")");
            System.out.println("    Argument6=k | Number of start vectors (" + k + ")");
            System.out.println(
                    "    Argument7=vectorDimension | Dimension of each vector (" + vectorDimension + ")");
            System.out.println(
                    "    Argument8=maxIterations | Number of maximal iterations (" + maxIteration + ")");
            System.out.println("    Argument9=testExample | Use testExample input (true|false=default)");
            System.out.println("    Argument10=GPUPercentage (percentage of input)");
            System.out.println("    Argument11=isDebugging (true|false=defaul)");
            System.out.println("    Argument12=timeMeasurement (true|false=defaul)");
            return;
        }
    }

    // Set config variables
    conf.setBoolean(CONF_DEBUG, isDebugging);
    conf.setBoolean("hama.pipes.logging", false);
    conf.setBoolean(CONF_TIME, timeMeasurement);

    // Set CPU tasks
    conf.setInt("bsp.peers.num", numBspTask);
    // Set GPU tasks
    conf.setInt("bsp.peers.gpu.num", numGpuBspTask);
    // Set GPU blockSize and gridSize
    conf.set(CONF_BLOCKSIZE, "" + blockSize);
    conf.set(CONF_GRIDSIZE, "" + gridSize);
    // Set maxIterations for KMeans
    conf.setInt(CONF_MAX_ITERATIONS, maxIteration);
    // Set n for KMeans
    conf.setLong(CONF_N, n);
    // Set GPU workload
    conf.setInt(CONF_GPU_PERCENTAGE, GPUPercentage);

    LOG.info("NumBspTask: " + conf.getInt("bsp.peers.num", 0));
    LOG.info("NumGpuBspTask: " + conf.getInt("bsp.peers.gpu.num", 0));
    LOG.info("bsp.tasks.maximum: " + conf.get("bsp.tasks.maximum"));
    LOG.info("GPUPercentage: " + conf.get(CONF_GPU_PERCENTAGE));
    LOG.info("BlockSize: " + conf.get(CONF_BLOCKSIZE));
    LOG.info("GridSize: " + conf.get(CONF_GRIDSIZE));
    LOG.info("isDebugging: " + conf.get(CONF_DEBUG));
    LOG.info("timeMeasurement: " + conf.get(CONF_TIME));
    LOG.info("useTestExampleInput: " + useTestExampleInput);
    LOG.info("inputPath: " + CONF_INPUT_DIR);
    LOG.info("centersPath: " + CONF_CENTER_DIR);
    LOG.info("outputPath: " + CONF_OUTPUT_DIR);
    LOG.info("n: " + n);
    LOG.info("k: " + k);
    LOG.info("vectorDimension: " + vectorDimension);
    LOG.info("maxIteration: " + maxIteration);

    Path centerIn = new Path(CONF_CENTER_DIR, "center_in.seq");
    Path centerOut = new Path(CONF_CENTER_DIR, "center_out.seq");
    conf.set(CONF_CENTER_IN_PATH, centerIn.toString());
    conf.set(CONF_CENTER_OUT_PATH, centerOut.toString());

    // prepare Input
    if (useTestExampleInput) {
        // prepareTestInput(conf, fs, input, centerIn);
        prepareInputData(conf, fs, CONF_INPUT_DIR, centerIn, numBspTask, numGpuBspTask, n, k, vectorDimension,
                null, GPUPercentage);
    } else {
        prepareInputData(conf, fs, CONF_INPUT_DIR, centerIn, numBspTask, numGpuBspTask, n, k, vectorDimension,
                new Random(3337L), GPUPercentage);
    }

    BSPJob job = createKMeansHybridBSPConf(conf, CONF_INPUT_DIR, CONF_OUTPUT_DIR);

    long startTime = System.currentTimeMillis();
    if (job.waitForCompletion(true)) {
        LOG.info("Job Finished in " + (System.currentTimeMillis() - startTime) / 1000.0 + " seconds");

        if (isDebugging) {
            printFile(conf, fs, centerOut, new PipesVectorWritable(), NullWritable.get());
            printOutput(conf, fs, ".log", new IntWritable(), new PipesVectorWritable());
        }

        if (k < 50) {
            printFile(conf, fs, centerOut, new PipesVectorWritable(), NullWritable.get());
        }
    }
}

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