List of runJob() Examples

Examples of runJob()

com.ontology2.haruhi.Cluster.runJob()
it.eng.spagobi.engines.talend.runtime.RuntimeRepository.runJob()
Run job. @param job the job @param env the environment @throws JobNotFoundException the job not found exception @throws ContextNotFoundException the context not found exception @throws JobExecutionException the job execution exception
org.apache.cloudstack.framework.jobs.AsyncJobDispatcher.runJob()
org.apache.hadoop.mapred.JobClient.runJob()
Utility that submits a job, then polls for progress until the job is complete. @param job the job configuration. @throws IOException
org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesDriver.runJob()
Run the job @param input the input pathname String @param output the output pathname String @throws ClassNotFoundException @throws InterruptedException
org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesDriver.runJob()
Run the job @param input the input pathname String @param output the output pathname String @throws ClassNotFoundException @throws InterruptedException
org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureDriver.runJob()
Run the job @param input the input pathname String @param output the output pathname String
org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfDriver.runJob()
Run the job @param input the input pathname String @param output the output pathname String @throws ClassNotFoundException
org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver.runJob()
Run the job @param input the input pathname String @param output the output pathname String
org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()
org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob.runJob()
Progammatic invocation of run() @param eigenInput Output of LanczosSolver @param corpusInput Input of LanczosSolver
org.apache.pig.backend.hadoop.executionengine.tez.plan.operator.NativeTezOper.runJob()
org.ggf.drmaa.Session.runJob()
Submit a job with attributes defined in the job template, jt. The returned job identifier is a String identical to that returned from the underlying DRM system. @param jt the job template to be used to create the job @throws DrmaaException May be one of the following:
- TryLaterException -- the DRM was temporarily unable to fulfill the request, but a retry might succeed
- DeniedByDrmException -- the DRM has rejected the job due to configuration problems either in the DRM or the job template
- InvalidJobTemplateException -- the JobTemplate instance does not belong to the current session, was not created with createJobTemplate(), or has already been deleted
- NoActiveSessionException -- the session has not yet been initialized or has already been exited
- DrmCommunicationException -- the DRMAA implementation was unable to contact the DRM
- AuthorizationException -- the executing user does not have sufficient permissions to execute the desired action
- IllegalArgumentException -- an argument is invalid
- InternalException -- an error has occured in the DRMAA implementation
@return job identifier String identical to that returned from theunderlying DRM system
org.ofbiz.service.job.JobManager.runJob()
Queues a Job to run now.

Examples of org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver.runJob()

    
    log.info("Calculating weight sums for labels and features...");
    // Calculate the Sums of weights for each label, for each feature and for
    // each feature and for each label
    BayesWeightSummerDriver summer = new BayesWeightSummerDriver();
    summer.runJob(input, output, params);
    
    log.info("Calculating the weight Normalisation factor for each class...");
    // Calculate the normalization factor Sigma_W_ij for each complement class.
    BayesThetaNormalizerDriver normalizer = new BayesThetaNormalizerDriver();
    normalizer.runJob(input, output, params);

View Full Code Here

Examples of org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver.runJob()

    
    log.info("Calculating weight sums for labels and features...");
    // Calculate the Sums of weights for each label, for each feature and for
    // each feature and for each label
    BayesWeightSummerDriver summer = new BayesWeightSummerDriver();
    summer.runJob(input, output, params);
    
    log.info("Calculating the weight Normalisation factor for each complement class...");
    // Calculate the normalization factor Sigma_W_ij for each complement class.
    CBayesThetaNormalizerDriver normalizer = new CBayesThetaNormalizerDriver();
    normalizer.runJob(input, output, params);

View Full Code Here

Examples of org.apache.mahout.classifier.bayes.mapreduce.common.BayesWeightSummerDriver.runJob()

    tfidf.runJob(input, output, params);


    log.info("Calculating weight sums for labels and features...");
    //Calculate the Sums of weights for each label, for each feature and for each feature and for each label
    BayesWeightSummerDriver summer = new BayesWeightSummerDriver();
    summer.runJob(input, output, params);


    log.info("Calculating the weight Normalisation factor for each class...");
    //Calculate the normalization factor Sigma_W_ij for each complement class.
    BayesThetaNormalizerDriver normalizer = new BayesThetaNormalizerDriver();
    normalizer.runJob(input, output, params);

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

    int overshoot = (int) ((double) clusters * OVERSHOOT_MULTIPLIER);
    List<Double> eigenValues = new ArrayList<Double>(overshoot);
    Matrix eigenVectors = new DenseMatrix(overshoot, numDims);
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    Path lanczosSeqFiles = new Path(outputCalc, "eigenvectors-" + (System.nanoTime() & 0xFF));
    solver.runJob(conf,
                  L.getRowPath(),
                  new Path(outputTmp, "lanczos-" + (System.nanoTime() & 0xFF)),
                  L.numRows(),
                  L.numCols(),
                  true,

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

                                                               int overshoot,
                                                               List<Double> eigenValues,
                                                               Matrix eigenVectors, Path tmp) throws IOException {
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    Path seqFiles = new Path(tmp, "eigendecomp-" + (System.nanoTime() & 0xFF));
    solver.runJob(conf,
                  input.getRowPath(),
                  new Path(tmp, "lanczos-" + (System.nanoTime() & 0xFF)),
                  input.numRows(),
                  input.numCols(),
                  true,

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

                                                               int numEigenVectors,
                                                               int overshoot,
                                                               Path tmp) throws IOException {
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    Path seqFiles = new Path(tmp, "eigendecomp-" + (System.nanoTime() & 0xFF));
    solver.runJob(conf,
                  state,
                  overshoot,
                  true,
                  seqFiles.toString());

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

    // unnecessary vectors later
    int overshoot = (int) ((double) clusters * OVERSHOOT_MULTIPLIER);
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    LanczosState state = new LanczosState(L, numDims, solver.getInitialVector(L));
    Path lanczosSeqFiles = new Path(outputCalc, "eigenvectors-" + (System.nanoTime() & 0xFF));
    solver.runJob(conf,
                  state,
                  overshoot,
                  true,
                  lanczosSeqFiles.toString());

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

                                                               int numEigenVectors,
                                                               int overshoot,
                                                               Path tmp) throws IOException {
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    Path seqFiles = new Path(tmp, "eigendecomp-" + (System.nanoTime() & 0xFF));
    solver.runJob(conf,
                  state,
                  overshoot,
                  true,
                  seqFiles.toString());

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver.runJob()

      int overshoot = Math.min((int) (clusters * OVERSHOOTMULTIPLIER), numDims);
      DistributedLanczosSolver solver = new DistributedLanczosSolver();
      LanczosState state = new LanczosState(L, overshoot, DistributedLanczosSolver.getInitialVector(L));
      Path lanczosSeqFiles = new Path(outputCalc, "eigenvectors");


      solver.runJob(conf, state, overshoot, true, lanczosSeqFiles.toString());


      // perform a verification
      EigenVerificationJob verifier = new EigenVerificationJob();
      Path verifiedEigensPath = new Path(outputCalc, "eigenverifier");
      verifier.runJob(conf, lanczosSeqFiles, L.getRowPath(), verifiedEigensPath, true, 1.0, clusters);

View Full Code Here

Examples of org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob.runJob()

                  lanczosSeqFiles.toString());


    // perform a verification
    EigenVerificationJob verifier = new EigenVerificationJob();
    Path verifiedEigensPath = new Path(outputCalc, "eigenverifier");
    verifier.runJob(conf, lanczosSeqFiles, L.getRowPath(), verifiedEigensPath, true, 1.0, 0.0, clusters);
    Path cleanedEigens = verifier.getCleanedEigensPath();
    DistributedRowMatrix W = new DistributedRowMatrix(cleanedEigens, new Path(cleanedEigens, "tmp"), clusters, numDims);
    W.configure(depConf);
    DistributedRowMatrix Wtrans = W.transpose();
    //    DistributedRowMatrix Wt = W.transpose();

View Full Code Here

0 1 2 3 4 5

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.