Examples with ComputeEnvironment edu.iu.dsc.tws.task.ComputeEnvironment used on opensource projects

Example 6 with ComputeEnvironment

use of edu.iu.dsc.tws.task.ComputeEnvironment in project twister2 by DSC-SPIDAL.

the class WordCount method execute.

@Override
public void execute(WorkerEnvironment workerEnv) {
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    // create source and aggregator
    WordSource source = new WordSource();
    WordAggregator counter = new WordAggregator();
    // build the graph
    ComputeGraphBuilder builder = ComputeGraphBuilder.newBuilder(workerEnv.getConfig());
    builder.addSource("word-source", source, 4);
    builder.addCompute("word-aggregator", counter, 4).partition("word-source").viaEdge(EDGE).withDataType(MessageTypes.OBJECT);
    builder.setMode(OperationMode.STREAMING);
    // build the graph
    ComputeGraph graph = builder.build();
    // execute graph
    cEnv.getTaskExecutor().execute(graph);
}

Example 7 with ComputeEnvironment

use of edu.iu.dsc.tws.task.ComputeEnvironment in project twister2 by DSC-SPIDAL.

the class BenchTaskWorker method execute.

@Override
public void execute(WorkerEnvironment workerEnv) {
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    int workerId = workerEnv.getWorkerId();
    Config config = workerEnv.getConfig();
    if (resultsRecorder == null) {
        resultsRecorder = new BenchmarkResultsRecorder(config, workerId == 0);
    }
    Timing.setDefaultTimingUnit(TimingUnit.NANO_SECONDS);
    jobParameters = JobParameters.build(config);
    computeGraphBuilder = ComputeGraphBuilder.newBuilder(config);
    if (jobParameters.isStream()) {
        computeGraphBuilder.setMode(OperationMode.STREAMING);
    } else {
        computeGraphBuilder.setMode(OperationMode.BATCH);
    }
    inputDataArray = DataGenerator.generateIntData(jobParameters.getSize());
    buildTaskGraph();
    computeGraph = computeGraphBuilder.build();
    executionPlan = cEnv.getTaskExecutor().plan(computeGraph);
    IExecution execution = cEnv.getTaskExecutor().createExecution(computeGraph, executionPlan).iExecute();
    if (jobParameters.isStream()) {
        while (execution.progress() && (sendersInProgress.get() != 0 || receiversInProgress.get() != 0)) {
        // do nothing
        }
        // now just spin for several iterations to progress the remaining communication.
        // todo fix streaming to return false, when comm is done
        long timeNow = System.currentTimeMillis();
        LOG.info("Streaming Example task will wait 10secs to finish communication...");
        while (System.currentTimeMillis() - timeNow < 10000) {
            execution.progress();
        }
    } else {
        while (execution.progress()) {
        // do nothing
        }
    }
    LOG.info("Stopping execution....");
    execution.stop();
    execution.close();
}

Example 8 with ComputeEnvironment

use of edu.iu.dsc.tws.task.ComputeEnvironment in project twister2 by DSC-SPIDAL.

the class ConstraintTaskExample method execute.

@Override
public void execute(WorkerEnvironment workerEnv) {
    int workerId = workerEnv.getWorkerId();
    Config config = workerEnv.getConfig();
    long startTime = System.currentTimeMillis();
    LOG.log(Level.INFO, "Task worker starting: " + workerId);
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    TaskExecutor taskExecutor = cEnv.getTaskExecutor();
    String dinput = String.valueOf(config.get(DataObjectConstants.DINPUT_DIRECTORY));
    int dimension = Integer.parseInt(String.valueOf(config.get(DataObjectConstants.DIMENSIONS)));
    int parallelismValue = Integer.parseInt(String.valueOf(config.get(DataObjectConstants.PARALLELISM_VALUE)));
    int dsize = Integer.parseInt(String.valueOf(config.get(DataObjectConstants.DSIZE)));
    DataGenerator dataGenerator = new DataGenerator(config, workerId);
    dataGenerator.generate(new Path(dinput), dsize, dimension);
    ComputeGraph firstGraph = buildFirstGraph(parallelismValue, config, dinput, dsize, dimension, "firstgraphpoints", "1");
    ComputeGraph secondGraph = buildSecondGraph(parallelismValue, config, dimension, "firstgraphpoints", "1");
    // Get the execution plan for the first task graph
    ExecutionPlan firstGraphExecutionPlan = taskExecutor.plan(firstGraph);
    taskExecutor.execute(firstGraph, firstGraphExecutionPlan);
    DataObject<Object> firstGraphObject = taskExecutor.getOutput("firstsink");
    // Get the execution plan for the second task graph
    ExecutionPlan secondGraphExecutionPlan = taskExecutor.plan(secondGraph);
    taskExecutor.addInput("firstgraphpoints", firstGraphObject);
    taskExecutor.execute(secondGraph, secondGraphExecutionPlan);
    long endTime = System.currentTimeMillis();
    LOG.info("Total Execution Time: " + (endTime - startTime));
}

Example 9 with ComputeEnvironment

use of edu.iu.dsc.tws.task.ComputeEnvironment in project twister2 by DSC-SPIDAL.

the class KafkaExample method execute.

@Override
public void execute(WorkerEnvironment workerEnv) {
    ComputeEnvironment cEnv = ComputeEnvironment.init(workerEnv);
    ComputeGraphBuilder graphBuilder = ComputeGraphBuilder.newBuilder(workerEnv.getConfig());
    graphBuilder.setMode(OperationMode.STREAMING);
    graphBuilder.addSource("ksource", new KSource(), 2);
    graphBuilder.addCompute("sink", new KSink(), 2).direct("ksource").viaEdge("edge");
    cEnv.buildAndExecute(graphBuilder);
}

Example 10 with ComputeEnvironment

use of edu.iu.dsc.tws.task.ComputeEnvironment 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();
}