Examples with FlinkMetricContainer org.apache.flink.python.metric.FlinkMetricContainer used on opensource projects

Example 1 with FlinkMetricContainer

use of org.apache.flink.python.metric.FlinkMetricContainer in project flink by apache.

the class BeamPythonFunctionRunner method open.

// ------------------------------------------------------------------------
@Override
public void open(PythonConfig config) throws Exception {
    this.bundleStarted = false;
    this.resultBuffer = new LinkedBlockingQueue<>();
    this.reusableResultTuple = new Tuple2<>();
    // The creation of stageBundleFactory depends on the initialized environment manager.
    environmentManager.open();
    PortablePipelineOptions portableOptions = PipelineOptionsFactory.as(PortablePipelineOptions.class);
    if (jobOptions.containsKey(PythonOptions.STATE_CACHE_SIZE.key())) {
        portableOptions.as(ExperimentalOptions.class).setExperiments(Collections.singletonList(ExperimentalOptions.STATE_CACHE_SIZE + "=" + jobOptions.get(PythonOptions.STATE_CACHE_SIZE.key())));
    }
    Struct pipelineOptions = PipelineOptionsTranslation.toProto(portableOptions);
    if (memoryManager != null && config.isUsingManagedMemory()) {
        Preconditions.checkArgument(managedMemoryFraction > 0 && managedMemoryFraction <= 1.0, "The configured managed memory fraction for Python worker process must be within (0, 1], was: %s. " + "It may be because the consumer type \"Python\" was missing or set to 0 for the config option \"taskmanager.memory.managed.consumer-weights\"." + managedMemoryFraction);
        final LongFunctionWithException<PythonSharedResources, Exception> initializer = (size) -> new PythonSharedResources(createJobBundleFactory(pipelineOptions), createPythonExecutionEnvironment(size));
        sharedResources = memoryManager.getSharedMemoryResourceForManagedMemory(MANAGED_MEMORY_RESOURCE_ID, initializer, managedMemoryFraction);
        LOG.info("Obtained shared Python process of size {} bytes", sharedResources.getSize());
        sharedResources.getResourceHandle().addPythonEnvironmentManager(environmentManager);
        JobBundleFactory jobBundleFactory = sharedResources.getResourceHandle().getJobBundleFactory();
        RunnerApi.Environment environment = sharedResources.getResourceHandle().getEnvironment();
        stageBundleFactory = createStageBundleFactory(jobBundleFactory, environment);
    } else {
        // there is no way to access the MemoryManager for the batch job of old planner,
        // fallback to the way that spawning a Python process for each Python operator
        jobBundleFactory = createJobBundleFactory(pipelineOptions);
        stageBundleFactory = createStageBundleFactory(jobBundleFactory, createPythonExecutionEnvironment(-1));
    }
    progressHandler = getProgressHandler(flinkMetricContainer);
}