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

Example 11 with IExecutor

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

the class KMeansComputeJob 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();
    LOG.log(Level.FINE, "Task worker starting: " + workerId);
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    TaskExecutor taskExecutor = cEnv.getTaskExecutor();
    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 = buildDataPointsTG(dataDirectory, dsize, parallelismValue, dimension, config, type);
    /* Second Graph to read the centroids **/
    ComputeGraph centroidsTaskGraph = buildCentroidsTG(centroidDirectory, csize, parallelismValue, dimension, config, type);
    /* Third Graph to do the actual calculation **/
    ComputeGraph kmeansTaskGraph = buildKMeansTG(parallelismValue, 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);
    // Get the execution plan for the second task graph
    ExecutionPlan secondGraphExecutionPlan = taskExecutor.plan(centroidsTaskGraph);
    // Actual execution for the second taskgraph
    taskExecutor.execute(centroidsTaskGraph, secondGraphExecutionPlan);
    long endTimeData = System.currentTimeMillis();
    // 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);
    }
    cEnv.close();
    long endTime = System.currentTimeMillis();
    LOG.info("Total K-Means Execution Time: " + (endTime - startTime) + "\tData Load time : " + (endTimeData - startTime) + "\tCompute Time : " + (endTime - endTimeData));
}