Examples with IExecutor edu.iu.dsc.tws.api.compute.executor.IExecutor used on opensource projects

Example 6 with IExecutor

use of edu.iu.dsc.tws.api.compute.executor.IExecutor in project twister2 by DSC-SPIDAL.

the class SvmSgdIterativeRunner method runTrainingGraph.

private void runTrainingGraph() {
    iterativeSVMTrainingTaskGraph = buildSvmSgdIterativeTrainingTG();
    iterativeSVMTrainingExecutionPlan = taskExecutor.plan(iterativeSVMTrainingTaskGraph);
    IExecutor ex = taskExecutor.createExecution(iterativeSVMTrainingTaskGraph, iterativeSVMTrainingExecutionPlan);
    for (int i = 0; i < this.binaryBatchModel.getIterations(); i++) {
        LOG.info(String.format("Iteration  %d ", i));
        taskExecutor.addInput(iterativeSVMTrainingTaskGraph, iterativeSVMTrainingExecutionPlan, Constants.SimpleGraphConfig.ITERATIVE_DATASTREAMER_SOURCE, Constants.SimpleGraphConfig.INPUT_DATA, trainingDoubleDataPointObject);
        taskExecutor.addInput(iterativeSVMTrainingTaskGraph, iterativeSVMTrainingExecutionPlan, Constants.SimpleGraphConfig.ITERATIVE_DATASTREAMER_SOURCE, Constants.SimpleGraphConfig.INPUT_WEIGHT_VECTOR, inputDoubleWeightvectorObject);
        ex.execute();
        inputDoubleWeightvectorObject = taskExecutor.getOutput(iterativeSVMTrainingTaskGraph, iterativeSVMTrainingExecutionPlan, Constants.SimpleGraphConfig.ITERATIVE_SVM_REDUCE);
    }
    ex.closeExecution();
}

Example 7 with IExecutor

use of edu.iu.dsc.tws.api.compute.executor.IExecutor in project twister2 by DSC-SPIDAL.

the class TaskExecutor method createExecution.

/**
 * Execute a plan and a graph. This call blocks until the execution finishes. In case of
 * streaming, this call doesn't return while for batch computations it returns after
 * the execution is done.
 *
 * @param graph the dataflow graph
 * @param plan the execution plan
 */
public IExecutor createExecution(ComputeGraph graph, ExecutionPlan plan) {
    IExecutor ex = executor.getExecutor(config, plan, graph.getOperationMode(), new ExecutionHookImpl(config, dataObjectMap, plan, currentExecutors));
    currentExecutors.add(ex);
    return ex;
}

Example 8 with IExecutor

use of edu.iu.dsc.tws.api.compute.executor.IExecutor in project twister2 by DSC-SPIDAL.

the class IterativeJob method execute.

@Override
public void execute(WorkerEnvironment workerEnv) {
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    TaskExecutor taskExecutor = cEnv.getTaskExecutor();
    int workerId = workerEnv.getWorkerId();
    Config config = workerEnv.getConfig();
    LOG.log(Level.INFO, "Task worker starting: " + workerId);
    IterativeSourceTask g = new IterativeSourceTask();
    PartitionTask r = new PartitionTask();
    ComputeGraphBuilder graphBuilder = ComputeGraphBuilder.newBuilder(config);
    graphBuilder.addSource("source", g, 4);
    ComputeConnection computeConnection = graphBuilder.addCompute("sink", r, 4);
    computeConnection.partition("source").viaEdge("partition").withDataType(MessageTypes.OBJECT);
    graphBuilder.setMode(OperationMode.BATCH);
    ComputeGraph graph = graphBuilder.build();
    ExecutionPlan plan = taskExecutor.plan(graph);
    IExecutor ex = taskExecutor.createExecution(graph, plan);
    for (int i = 0; i < 10; i++) {
        LOG.info("Starting iteration: " + i);
        taskExecutor.addInput(graph, plan, "source", "input", new DataObjectImpl<>(config));
        // this is a blocking call
        ex.execute();
        DataObject<Object> dataSet = taskExecutor.getOutput(graph, plan, "sink");
        DataPartition<Object>[] values = dataSet.getPartitions();
    }
    ex.closeExecution();
}

Example 9 with IExecutor

use of edu.iu.dsc.tws.api.compute.executor.IExecutor in project twister2 by DSC-SPIDAL.

the class SingleSourceShortestPathWorker method execute.

@Override
public void execute() {
    SsspParameters ssspParameters = SsspParameters.build(config);
    int parallelismValue = ssspParameters.getParallelismValue();
    int dsize = ssspParameters.getDsize();
    String dataDirectory = ssspParameters.getDatapointDirectory();
    String soruceVertex = ssspParameters.getSourcevertex();
    sourceVertexGlobal = soruceVertex;
    /* First Graph to partition and read the partitioned adjacency list datas **/
    // Build the first taskgraph
    ComputeGraph datapointsTaskGraph = buildDataPointsTG(dataDirectory, dsize, parallelismValue, soruceVertex, config);
    // Get the execution plan for the first task graph
    ExecutionPlan firstGraphExecutionPlan = taskExecutor.plan(datapointsTaskGraph);
    // Actual execution for the first taskgraph
    taskExecutor.execute(datapointsTaskGraph, firstGraphExecutionPlan);
    // Retrieve the output of the first task graph
    // +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    // Build the second taskgraph
    ComputeGraph graphInitialValueTaskGraph = buildSsspInitialTG(dataDirectory, dsize, parallelismValue, soruceVertex, config);
    // Get the execution plan for the second task graph
    ExecutionPlan secondGraphExecutionPlan = taskExecutor.plan(graphInitialValueTaskGraph);
    // Actual execution for the second taskgraph
    taskExecutor.execute(graphInitialValueTaskGraph, secondGraphExecutionPlan);
    // Retrieve the output of the second task graph
    // +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    /* Third Graph to do the actual calculation **/
    ComputeGraph sssptaskgraph = buildComputationSsspTG(parallelismValue, config);
    IExecutor ex = taskExecutor.createExecution(sssptaskgraph);
    int itr = 0;
    while (globaliterationStatus) {
        ex.execute(false);
        itr++;
    }
    ex.close();
    taskExecutor.close();
    if (workerId == 1) {
        System.out.println("Tatol iteration: " + itr);
    }
}

Example 10 with IExecutor

use of edu.iu.dsc.tws.api.compute.executor.IExecutor in project twister2 by DSC-SPIDAL.

the class KMeansCheckpointingWorker method execute.

/**
 * First, the execute method invokes the generateDataPoints method to generate the datapoints file
 * and centroid file based on the respective filesystem submitted by the user. Next, it invoke
 * the DataObjectSource and DataObjectSink to partition and read the partitioned data points
 * respectively through data points task graph. Then, it calls the DataFileReader to read the
 * centroid values from the filesystem through centroid task graph. Next, the datapoints are
 * stored in DataSet \(0th object\) and centroids are stored in DataSet 1st object\). Finally, it
 * constructs the kmeans task graph to perform the clustering process which computes the distance
 * between the centroids and data points.
 */
@SuppressWarnings("unchecked")
@Override
public void execute(WorkerEnvironment workerEnv) {
    int workerId = workerEnv.getWorkerId();
    Config config = workerEnv.getConfig();
    IWorkerController workerController = workerEnv.getWorkerController();
    ComputeEnvironment taskEnv = ComputeEnvironment.init(workerEnv);
    CheckpointingWorkerEnv checkpointingEnv = CheckpointingWorkerEnv.newBuilder(config, workerId, workerController).registerVariable(I_KEY, IntegerPacker.getInstance()).registerVariable(CENT_OBJ, ObjectPacker.getInstance()).build();
    Snapshot snapshot = checkpointingEnv.getSnapshot();
    TaskExecutor taskExecutor = taskEnv.getTaskExecutor();
    LOG.info("Task worker starting: " + workerId + " Current snapshot ver: " + snapshot.getVersion());
    int parallelismValue = config.getIntegerValue(DataObjectConstants.PARALLELISM_VALUE);
    int dimension = config.getIntegerValue(DataObjectConstants.DIMENSIONS);
    int numFiles = config.getIntegerValue(DataObjectConstants.NUMBER_OF_FILES);
    int dsize = config.getIntegerValue(DataObjectConstants.DSIZE);
    int csize = config.getIntegerValue(DataObjectConstants.CSIZE);
    int iterations = config.getIntegerValue(DataObjectConstants.ARGS_ITERATIONS);
    String dataDirectory = config.getStringValue(DataObjectConstants.DINPUT_DIRECTORY) + workerId;
    String centroidDirectory = config.getStringValue(DataObjectConstants.CINPUT_DIRECTORY) + workerId;
    String type = config.getStringValue(DataObjectConstants.FILE_TYPE);
    KMeansUtils.generateDataPoints(config, dimension, numFiles, dsize, csize, dataDirectory, centroidDirectory, type);
    long startTime = System.currentTimeMillis();
    /* First Graph to partition and read the partitioned data points **/
    ComputeGraph datapointsTaskGraph = KMeansComputeJob.buildDataPointsTG(dataDirectory, dsize, parallelismValue, dimension, config, type);
    // Get the execution plan for the first task graph
    ExecutionPlan datapointsExecutionPlan = taskExecutor.plan(datapointsTaskGraph);
    // Actual execution for the first taskgraph
    taskExecutor.execute(datapointsTaskGraph, datapointsExecutionPlan);
    // Retrieve the output of the first task graph
    DataObject<Object> dataPointsObject = taskExecutor.getOutput(datapointsTaskGraph, datapointsExecutionPlan, "datapointsink");
    DataObject<Object> centroidsDataObject;
    if (!snapshot.checkpointAvailable(CENT_OBJ)) {
        /* Second Graph to read the centroids **/
        ComputeGraph centroidsTaskGraph = KMeansComputeJob.buildCentroidsTG(centroidDirectory, csize, parallelismValue, dimension, config, type);
        // Get the execution plan for the second task graph
        ExecutionPlan centroidsExecutionPlan = taskExecutor.plan(centroidsTaskGraph);
        // Actual execution for the second taskgraph
        taskExecutor.execute(centroidsTaskGraph, centroidsExecutionPlan);
        // Retrieve the output of the first task graph
        centroidsDataObject = taskExecutor.getOutput(centroidsTaskGraph, centroidsExecutionPlan, "centroidsink");
    } else {
        centroidsDataObject = (DataObject<Object>) snapshot.get(CENT_OBJ);
    }
    long endTimeData = System.currentTimeMillis();
    /* Third Graph to do the actual calculation **/
    ComputeGraph kmeansTaskGraph = KMeansComputeJob.buildKMeansTG(parallelismValue, config);
    // Perform the iterations from 0 to 'n' number of iterations
    IExecutor ex = taskExecutor.createExecution(kmeansTaskGraph);
    for (int i = 0; i < iterations; i++) {
        // actual execution of the third task graph
        ex.execute(i == iterations - 1);
    }
    DataPartition<?> centroidPartition = centroidsDataObject.getPartition(workerId);
    double[][] centroid = (double[][]) centroidPartition.getConsumer().next();
    long endTime = System.currentTimeMillis();
    if (workerId == 0) {
        LOG.info("Data Load time : " + (endTimeData - startTime) + "\n" + "Total Time : " + (endTime - startTime) + "Compute Time : " + (endTime - endTimeData));
    }
    LOG.info("Final Centroids After\t" + iterations + "\titerations\t" + Arrays.deepToString(centroid));
    taskEnv.close();
}