m-trieu commented on code in PR #28537:
URL: https://github.com/apache/beam/pull/28537#discussion_r1333650700
##########
runners/google-cloud-dataflow-java/worker/src/main/java/org/apache/beam/runners/dataflow/worker/StreamingDataflowWorker.java:
##########
@@ -170,106 +191,35 @@ public class StreamingDataflowWorker {
private static final Function<MapTask, MutableNetwork<Node, Edge>>
mapTaskToBaseNetwork =
new MapTaskToNetworkFunction(idGenerator);
- private static Random clientIdGenerator = new Random();
-
- // Maximum number of threads for processing. Currently each thread
processes one key at a time.
- static final int MAX_PROCESSING_THREADS = 300;
- static final long THREAD_EXPIRATION_TIME_SEC = 60;
- static final long TARGET_COMMIT_BUNDLE_BYTES = 32 << 20;
- static final int MAX_COMMIT_QUEUE_BYTES = 500 << 20; // 500MB
- static final int NUM_COMMIT_STREAMS = 1;
- static final int GET_WORK_STREAM_TIMEOUT_MINUTES = 3;
- static final Duration COMMIT_STREAM_TIMEOUT = Duration.standardMinutes(1);
-
private static final int DEFAULT_STATUS_PORT = 8081;
-
// Maximum size of the result of a GetWork request.
private static final long MAX_GET_WORK_FETCH_BYTES = 64L << 20; // 64m
-
// Reserved ID for counter updates.
// Matches kWindmillCounterUpdate in workflow_worker_service_multi_hubs.cc.
private static final String WINDMILL_COUNTER_UPDATE_WORK_ID = "3";
-
/** Maximum number of failure stacktraces to report in each update sent to
backend. */
private static final int MAX_FAILURES_TO_REPORT_IN_UPDATE = 1000;
- // TODO(https://github.com/apache/beam/issues/19632): Update throttling
counters to use generic
- // throttling-msecs metric.
- public static final MetricName BIGQUERY_STREAMING_INSERT_THROTTLE_TIME =
- MetricName.named(
-
"org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$DatasetServiceImpl",
- "throttling-msecs");
-
private static final Duration MAX_LOCAL_PROCESSING_RETRY_DURATION =
Duration.standardMinutes(5);
-
- /** Returns whether an exception was caused by a {@link OutOfMemoryError}. */
- private static boolean isOutOfMemoryError(Throwable t) {
- while (t != null) {
- if (t instanceof OutOfMemoryError) {
- return true;
- }
- t = t.getCause();
- }
- return false;
- }
-
- private static MapTask parseMapTask(String input) throws IOException {
- return Transport.getJsonFactory().fromString(input, MapTask.class);
- }
-
- public static void main(String[] args) throws Exception {
- JvmInitializers.runOnStartup();
-
-
DataflowWorkerHarnessHelper.initializeLogging(StreamingDataflowWorker.class);
- DataflowWorkerHarnessOptions options =
- DataflowWorkerHarnessHelper.initializeGlobalStateAndPipelineOptions(
- StreamingDataflowWorker.class);
- DataflowWorkerHarnessHelper.configureLogging(options);
- checkArgument(
- options.isStreaming(),
- "%s instantiated with options indicating batch use",
- StreamingDataflowWorker.class.getName());
-
- checkArgument(
- !DataflowRunner.hasExperiment(options, "beam_fn_api"),
- "%s cannot be main() class with beam_fn_api enabled",
- StreamingDataflowWorker.class.getSimpleName());
-
- StreamingDataflowWorker worker =
- StreamingDataflowWorker.fromDataflowWorkerHarnessOptions(options);
-
- // Use the MetricsLogger container which is used by BigQueryIO to
periodically log process-wide
- // metrics.
- MetricsEnvironment.setProcessWideContainer(new MetricsLogger(null));
-
- JvmInitializers.runBeforeProcessing(options);
- worker.startStatusPages();
- worker.start();
- }
-
+ private static final Random clientIdGenerator = new Random();
+ final WindmillStateCache stateCache;
Review Comment:
Also for my own knowledge, why don't we use Guice or Dagger dependency
injection (if we want to avoid the runtime overhead)? @scwhittle
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