runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkGroupAlsoByWindowViaOutputBufferFn.java

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 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
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package org.apache.beam.runners.spark.translation;

import java.util.ArrayList;
import java.util.Collection;
import java.util.Iterator;
import java.util.List;
import org.apache.beam.runners.core.GroupByKeyViaGroupByKeyOnly.GroupAlsoByWindow;
import org.apache.beam.runners.core.InMemoryTimerInternals;
import org.apache.beam.runners.core.OutputWindowedValue;
import org.apache.beam.runners.core.ReduceFnRunner;
import org.apache.beam.runners.core.StateInternals;
import org.apache.beam.runners.core.StateInternalsFactory;
import org.apache.beam.runners.core.SystemReduceFn;
import org.apache.beam.runners.core.TimerInternals;
import org.apache.beam.runners.core.UnsupportedSideInputReader;
import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
import org.apache.beam.runners.core.construction.TriggerTranslation;
import org.apache.beam.runners.core.triggers.ExecutableTriggerStateMachine;
import org.apache.beam.runners.core.triggers.TriggerStateMachines;
import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
import org.apache.beam.sdk.transforms.windowing.PaneInfo;
import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.KV;
import org.apache.beam.sdk.values.TupleTag;
import org.apache.beam.sdk.values.WindowingStrategy;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.joda.time.Instant;

/** An implementation of {@link GroupAlsoByWindow} for the Spark runner. */
class SparkGroupAlsoByWindowViaOutputBufferFn<K, InputT, W extends BoundedWindow>
    implements FlatMapFunction<
        KV<K, Iterable<WindowedValue<InputT>>>, WindowedValue<KV<K, Iterable<InputT>>>> {

  private final WindowingStrategy<?, W> windowingStrategy;
  private final StateInternalsFactory<K> stateInternalsFactory;
  private final SystemReduceFn<K, InputT, Iterable<InputT>, Iterable<InputT>, W> reduceFn;
  private final SerializablePipelineOptions options;

  public SparkGroupAlsoByWindowViaOutputBufferFn(
      WindowingStrategy<?, W> windowingStrategy,
      StateInternalsFactory<K> stateInternalsFactory,
      SystemReduceFn<K, InputT, Iterable<InputT>, Iterable<InputT>, W> reduceFn,
      SerializablePipelineOptions options) {
    this.windowingStrategy = windowingStrategy;
    this.stateInternalsFactory = stateInternalsFactory;
    this.reduceFn = reduceFn;
    this.options = options;
  }

  @Override
  public Iterator<WindowedValue<KV<K, Iterable<InputT>>>> call(
      KV<K, Iterable<WindowedValue<InputT>>> kv) throws Exception {
    K key = kv.getKey();
    Iterable<WindowedValue<InputT>> values = kv.getValue();

    // ------ based on GroupAlsoByWindowsViaOutputBufferDoFn ------//

    // Used with Batch, we know that all the data is available for this key. We can't use the
    // timer manager from the context because it doesn't exist. So we create one and emulate the
    // watermark, knowing that we have all data and it is in timestamp order.
    InMemoryTimerInternals timerInternals = new InMemoryTimerInternals();
    timerInternals.advanceProcessingTime(Instant.now());
    timerInternals.advanceSynchronizedProcessingTime(Instant.now());
    StateInternals stateInternals = stateInternalsFactory.stateInternalsForKey(key);
    GABWOutputWindowedValue<K, InputT> outputter = new GABWOutputWindowedValue<>();

    ReduceFnRunner<K, InputT, Iterable<InputT>, W> reduceFnRunner =
        new ReduceFnRunner<>(
            key,
            windowingStrategy,
            ExecutableTriggerStateMachine.create(
                TriggerStateMachines.stateMachineForTrigger(
                    TriggerTranslation.toProto(windowingStrategy.getTrigger()))),
            stateInternals,
            timerInternals,
            outputter,
            new UnsupportedSideInputReader("GroupAlsoByWindow"),
            reduceFn,
            options.get());

    // Process the grouped values.
    reduceFnRunner.processElements(values);

    // Finish any pending windows by advancing the input watermark to infinity.
    timerInternals.advanceInputWatermark(BoundedWindow.TIMESTAMP_MAX_VALUE);

    // Finally, advance the processing time to infinity to fire any timers.
    timerInternals.advanceProcessingTime(BoundedWindow.TIMESTAMP_MAX_VALUE);
    timerInternals.advanceSynchronizedProcessingTime(BoundedWindow.TIMESTAMP_MAX_VALUE);

    fireEligibleTimers(timerInternals, reduceFnRunner);

    reduceFnRunner.persist();

    return outputter.getOutputs().iterator();
  }

  private void fireEligibleTimers(
      InMemoryTimerInternals timerInternals,
      ReduceFnRunner<K, InputT, Iterable<InputT>, W> reduceFnRunner)
      throws Exception {
    List<TimerInternals.TimerData> timers = new ArrayList<>();
    while (true) {
      TimerInternals.TimerData timer;
      while ((timer = timerInternals.removeNextEventTimer()) != null) {
        timers.add(timer);
      }
      while ((timer = timerInternals.removeNextProcessingTimer()) != null) {
        timers.add(timer);
      }
      while ((timer = timerInternals.removeNextSynchronizedProcessingTimer()) != null) {
        timers.add(timer);
      }
      if (timers.isEmpty()) {
        break;
      }
      reduceFnRunner.onTimers(timers);
      timers.clear();
    }
  }

  private static class GABWOutputWindowedValue<K, V>
      implements OutputWindowedValue<KV<K, Iterable<V>>> {
    private final List<WindowedValue<KV<K, Iterable<V>>>> outputs = new ArrayList<>();

    @Override
    public void outputWindowedValue(
        KV<K, Iterable<V>> output,
        Instant timestamp,
        Collection<? extends BoundedWindow> windows,
        PaneInfo pane) {
      outputs.add(WindowedValue.of(output, timestamp, windows, pane));
    }

    @Override
    public <AdditionalOutputT> void outputWindowedValue(
        TupleTag<AdditionalOutputT> tag,
        AdditionalOutputT output,
        Instant timestamp,
        Collection<? extends BoundedWindow> windows,
        PaneInfo pane) {
      throw new UnsupportedOperationException("GroupAlsoByWindow should not use tagged outputs.");
    }

    Iterable<WindowedValue<KV<K, Iterable<V>>>> getOutputs() {
      return outputs;
    }
  }
}