Examples with TaskVertexParser edu.iu.dsc.tws.tsched.utils.TaskVertexParser used on opensource projects

Example 1 with TaskVertexParser

use of edu.iu.dsc.tws.tsched.utils.TaskVertexParser in project twister2 by DSC-SPIDAL.

the class RoundRobinBatchTaskScheduler method schedule.

/**
 * This is the base method which receives the dataflow taskgraph and the worker plan to allocate
 * the task instances to the appropriate workers with their required ram, disk, and cpu values.
 */
@Override
public TaskSchedulePlan schedule(ComputeGraph computeGraph, WorkerPlan workerPlan) {
    Map<Integer, List<TaskInstanceId>> containerInstanceMap;
    Map<Integer, WorkerSchedulePlan> containerPlans = new LinkedHashMap<>();
    for (int i = 0; i < workerPlan.getNumberOfWorkers(); i++) {
        roundRobinAllocation.put(i, new ArrayList<>());
    }
    // To retrieve the batch task instances(it may be single task vertex or a batch of task vertices)
    Set<Vertex> taskVertexSet = new LinkedHashSet<>(computeGraph.getTaskVertexSet());
    TaskVertexParser taskGraphParser = new TaskVertexParser();
    List<Set<Vertex>> taskVertexList = taskGraphParser.parseVertexSet(computeGraph);
    for (Set<Vertex> vertexSet : taskVertexList) {
        if (vertexSet.size() > 1) {
            containerInstanceMap = roundRobinBatchSchedulingAlgorithm(computeGraph, vertexSet);
        } else {
            Vertex vertex = vertexSet.iterator().next();
            containerInstanceMap = roundRobinBatchSchedulingAlgorithm(computeGraph, vertex);
        }
        TaskInstanceMapCalculation instanceMapCalculation = new TaskInstanceMapCalculation(this.instanceRAM, this.instanceCPU, this.instanceDisk);
        Map<Integer, Map<TaskInstanceId, Double>> instancesRamMap = instanceMapCalculation.getInstancesRamMapInContainer(containerInstanceMap, taskVertexSet);
        Map<Integer, Map<TaskInstanceId, Double>> instancesDiskMap = instanceMapCalculation.getInstancesDiskMapInContainer(containerInstanceMap, taskVertexSet);
        Map<Integer, Map<TaskInstanceId, Double>> instancesCPUMap = instanceMapCalculation.getInstancesCPUMapInContainer(containerInstanceMap, taskVertexSet);
        for (int containerId : containerInstanceMap.keySet()) {
            double containerRAMValue = TaskSchedulerContext.containerRamPadding(config);
            double containerDiskValue = TaskSchedulerContext.containerDiskPadding(config);
            double containerCpuValue = TaskSchedulerContext.containerCpuPadding(config);
            List<TaskInstanceId> taskTaskInstanceIds = containerInstanceMap.get(containerId);
            Map<TaskInstanceId, TaskInstancePlan> taskInstancePlanMap = new HashMap<>();
            for (TaskInstanceId id : taskTaskInstanceIds) {
                double instanceRAMValue = instancesRamMap.get(containerId).get(id);
                double instanceDiskValue = instancesDiskMap.get(containerId).get(id);
                double instanceCPUValue = instancesCPUMap.get(containerId).get(id);
                Resource instanceResource = new Resource(instanceRAMValue, instanceDiskValue, instanceCPUValue);
                taskInstancePlanMap.put(id, new TaskInstancePlan(id.getTaskName(), id.getTaskId(), id.getTaskIndex(), instanceResource));
                containerRAMValue += instanceRAMValue;
                containerDiskValue += instanceDiskValue;
                containerCpuValue += instanceDiskValue;
            }
            Worker worker = workerPlan.getWorker(containerId);
            Resource containerResource;
            if (worker != null && worker.getCpu() > 0 && worker.getDisk() > 0 && worker.getRam() > 0) {
                containerResource = new Resource((double) worker.getRam(), (double) worker.getDisk(), (double) worker.getCpu());
            } else {
                containerResource = new Resource(containerRAMValue, containerDiskValue, containerCpuValue);
            }
            WorkerSchedulePlan taskWorkerSchedulePlan;
            if (containerPlans.containsKey(containerId)) {
                taskWorkerSchedulePlan = containerPlans.get(containerId);
                taskWorkerSchedulePlan.getTaskInstances().addAll(taskInstancePlanMap.values());
            } else {
                taskWorkerSchedulePlan = new WorkerSchedulePlan(containerId, new HashSet<>(taskInstancePlanMap.values()), containerResource);
                containerPlans.put(containerId, taskWorkerSchedulePlan);
            }
        }
    }
    return new TaskSchedulePlan(0, new HashSet<>(containerPlans.values()));
}

Example 2 with TaskVertexParser

use of edu.iu.dsc.tws.tsched.utils.TaskVertexParser in project twister2 by DSC-SPIDAL.

the class DataLocalityBatchTaskScheduler method schedule.

/**
 * This is the base method for the data locality aware task scheduling for scheduling the batch
 * task instances. It retrieves the task vertex set of the task graph and send the set to the
 * data locality aware scheduling algorithm to allocate the batch task instances which are closer
 * to the data nodes.
 */
@Override
public TaskSchedulePlan schedule(ComputeGraph graph, WorkerPlan workerPlan) {
    LinkedHashMap<Integer, WorkerSchedulePlan> containerPlans = new LinkedHashMap<>();
    for (int i = 0; i < workerPlan.getNumberOfWorkers(); i++) {
        dataLocalityAwareAllocation.put(i, new ArrayList<>());
    }
    LinkedHashSet<Vertex> taskVertexSet = new LinkedHashSet<>(graph.getTaskVertexSet());
    TaskVertexParser taskVertexParser = new TaskVertexParser();
    List<Set<Vertex>> taskVertexList = taskVertexParser.parseVertexSet(graph);
    for (Set<Vertex> vertexSet : taskVertexList) {
        Map<Integer, List<TaskInstanceId>> containerInstanceMap;
        if (vertexSet.size() > 1) {
            containerInstanceMap = dataLocalityBatchSchedulingAlgorithm(graph, vertexSet, workerPlan);
        } else {
            Vertex vertex = vertexSet.iterator().next();
            containerInstanceMap = dataLocalityBatchSchedulingAlgorithm(graph, vertex, workerPlan);
        }
        TaskInstanceMapCalculation instanceMapCalculation = new TaskInstanceMapCalculation(this.instanceRAM, this.instanceCPU, this.instanceDisk);
        Map<Integer, Map<TaskInstanceId, Double>> instancesRamMap = instanceMapCalculation.getInstancesRamMapInContainer(containerInstanceMap, taskVertexSet);
        Map<Integer, Map<TaskInstanceId, Double>> instancesDiskMap = instanceMapCalculation.getInstancesDiskMapInContainer(containerInstanceMap, taskVertexSet);
        Map<Integer, Map<TaskInstanceId, Double>> instancesCPUMap = instanceMapCalculation.getInstancesCPUMapInContainer(containerInstanceMap, taskVertexSet);
        for (int containerId : containerInstanceMap.keySet()) {
            double containerRAMValue = TaskSchedulerContext.containerRamPadding(config);
            double containerDiskValue = TaskSchedulerContext.containerDiskPadding(config);
            double containerCpuValue = TaskSchedulerContext.containerCpuPadding(config);
            List<TaskInstanceId> taskTaskInstanceIds = containerInstanceMap.get(containerId);
            Map<TaskInstanceId, TaskInstancePlan> taskInstancePlanMap = new HashMap<>();
            for (TaskInstanceId id : taskTaskInstanceIds) {
                double instanceRAMValue = instancesRamMap.get(containerId).get(id);
                double instanceDiskValue = instancesDiskMap.get(containerId).get(id);
                double instanceCPUValue = instancesCPUMap.get(containerId).get(id);
                Resource instanceResource = new Resource(instanceRAMValue, instanceDiskValue, instanceCPUValue);
                taskInstancePlanMap.put(id, new TaskInstancePlan(id.getTaskName(), id.getTaskId(), id.getTaskIndex(), instanceResource));
                containerRAMValue += instanceRAMValue;
                containerDiskValue += instanceDiskValue;
                containerCpuValue += instanceDiskValue;
            }
            Worker worker = workerPlan.getWorker(containerId);
            Resource containerResource;
            if (worker != null && worker.getCpu() > 0 && worker.getDisk() > 0 && worker.getRam() > 0) {
                containerResource = new Resource((double) worker.getRam(), (double) worker.getDisk(), (double) worker.getCpu());
            } else {
                containerResource = new Resource(containerRAMValue, containerDiskValue, containerCpuValue);
            }
            WorkerSchedulePlan taskWorkerSchedulePlan;
            if (containerPlans.containsKey(containerId)) {
                taskWorkerSchedulePlan = containerPlans.get(containerId);
                taskWorkerSchedulePlan.getTaskInstances().addAll(taskInstancePlanMap.values());
            } else {
                taskWorkerSchedulePlan = new WorkerSchedulePlan(containerId, new HashSet<>(taskInstancePlanMap.values()), containerResource);
                containerPlans.put(containerId, taskWorkerSchedulePlan);
            }
        }
    }
    TaskSchedulePlan taskSchedulePlan = new TaskSchedulePlan(0, new HashSet<>(containerPlans.values()));
    Map<Integer, WorkerSchedulePlan> containersMap = taskSchedulePlan.getContainersMap();
    for (Map.Entry<Integer, WorkerSchedulePlan> entry : containersMap.entrySet()) {
        Integer integer = entry.getKey();
        WorkerSchedulePlan workerSchedulePlan = entry.getValue();
        Set<TaskInstancePlan> containerPlanTaskInstances = workerSchedulePlan.getTaskInstances();
        LOG.fine("Task Details for Container Id:" + integer + "\tsize:" + containerPlanTaskInstances.size());
        for (TaskInstancePlan ip : containerPlanTaskInstances) {
            LOG.fine("TaskId:" + ip.getTaskId() + "\tTask Index" + ip.getTaskIndex() + "\tTask Name:" + ip.getTaskName());
        }
    }
    return taskSchedulePlan;
}