Examples with DefaultExecutionVertexOperations org.apache.flink.runtime.scheduler.DefaultExecutionVertexOperations used on opensource projects

Example 1 with DefaultExecutionVertexOperations

use of org.apache.flink.runtime.scheduler.DefaultExecutionVertexOperations in project flink by apache.

the class AdaptiveBatchSchedulerFactory method createInstance.

@Override
public SchedulerNG createInstance(Logger log, JobGraph jobGraph, Executor ioExecutor, Configuration jobMasterConfiguration, SlotPoolService slotPoolService, ScheduledExecutorService futureExecutor, ClassLoader userCodeLoader, CheckpointRecoveryFactory checkpointRecoveryFactory, Time rpcTimeout, BlobWriter blobWriter, JobManagerJobMetricGroup jobManagerJobMetricGroup, Time slotRequestTimeout, ShuffleMaster<?> shuffleMaster, JobMasterPartitionTracker partitionTracker, ExecutionDeploymentTracker executionDeploymentTracker, long initializationTimestamp, ComponentMainThreadExecutor mainThreadExecutor, FatalErrorHandler fatalErrorHandler, JobStatusListener jobStatusListener) throws Exception {
    checkState(jobGraph.getJobType() == JobType.BATCH, "Adaptive batch scheduler only supports batch jobs");
    checkAllExchangesBlocking(jobGraph);
    final SlotPool slotPool = slotPoolService.castInto(SlotPool.class).orElseThrow(() -> new IllegalStateException("The DefaultScheduler requires a SlotPool."));
    final SlotSelectionStrategy slotSelectionStrategy = SlotSelectionStrategyUtils.selectSlotSelectionStrategy(JobType.BATCH, jobMasterConfiguration);
    final PhysicalSlotRequestBulkChecker bulkChecker = PhysicalSlotRequestBulkCheckerImpl.createFromSlotPool(slotPool, SystemClock.getInstance());
    final PhysicalSlotProvider physicalSlotProvider = new PhysicalSlotProviderImpl(slotSelectionStrategy, slotPool);
    final ExecutionSlotAllocatorFactory allocatorFactory = new SlotSharingExecutionSlotAllocatorFactory(physicalSlotProvider, false, bulkChecker, slotRequestTimeout);
    final RestartBackoffTimeStrategy restartBackoffTimeStrategy = RestartBackoffTimeStrategyFactoryLoader.createRestartBackoffTimeStrategyFactory(jobGraph.getSerializedExecutionConfig().deserializeValue(userCodeLoader).getRestartStrategy(), jobMasterConfiguration, jobGraph.isCheckpointingEnabled()).create();
    log.info("Using restart back off time strategy {} for {} ({}).", restartBackoffTimeStrategy, jobGraph.getName(), jobGraph.getJobID());
    final ExecutionGraphFactory executionGraphFactory = new DefaultExecutionGraphFactory(jobMasterConfiguration, userCodeLoader, executionDeploymentTracker, futureExecutor, ioExecutor, rpcTimeout, jobManagerJobMetricGroup, blobWriter, shuffleMaster, partitionTracker, true);
    return new AdaptiveBatchScheduler(log, jobGraph, ioExecutor, jobMasterConfiguration, bulkChecker::start, new ScheduledExecutorServiceAdapter(futureExecutor), userCodeLoader, new CheckpointsCleaner(), checkpointRecoveryFactory, jobManagerJobMetricGroup, new VertexwiseSchedulingStrategy.Factory(), FailoverStrategyFactoryLoader.loadFailoverStrategyFactory(jobMasterConfiguration), restartBackoffTimeStrategy, new DefaultExecutionVertexOperations(), new ExecutionVertexVersioner(), allocatorFactory, initializationTimestamp, mainThreadExecutor, jobStatusListener, executionGraphFactory, shuffleMaster, rpcTimeout, DefaultVertexParallelismDecider.from(jobMasterConfiguration), jobMasterConfiguration.getInteger(JobManagerOptions.ADAPTIVE_BATCH_SCHEDULER_MAX_PARALLELISM));
}