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   * Licensed to the Apache Software Foundation (ASF) under one
   * or more contributor license agreements.  See the NOTICE file
   * 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.
   */
  package org.apache.beam.runners.spark.util;
  
  import static org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.base.Preconditions.checkNotNull;
  
  import java.util.List;
  import java.util.Map;
  import java.util.stream.Collectors;
  import java.util.stream.Stream;
  import java.util.stream.StreamSupport;
  import org.apache.beam.runners.core.InMemoryMultimapSideInputView;
  import org.apache.beam.runners.core.SideInputReader;
  import org.apache.beam.runners.spark.translation.SparkPCollectionView;
  import org.apache.beam.sdk.coders.Coder;
  import org.apache.beam.sdk.coders.KvCoder;
  import org.apache.beam.sdk.transforms.Materializations;
  import org.apache.beam.sdk.transforms.Materializations.IterableView;
  import org.apache.beam.sdk.transforms.Materializations.MultimapView;
  import org.apache.beam.sdk.transforms.ViewFn;
  import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
  import org.apache.beam.sdk.values.KV;
  import org.apache.beam.sdk.values.PCollectionView;
  import org.apache.beam.sdk.values.TupleTag;
  import org.apache.beam.sdk.values.WindowedValue;
  import org.apache.beam.sdk.values.WindowingStrategy;
  import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Iterables;
  import org.checkerframework.checker.nullness.qual.Nullable;
  
  /** A {@link SideInputReader} for the SparkRunner. */
  @SuppressWarnings({
    "rawtypes", // TODO(https://github.com/apache/beam/issues/20447)
    "nullness" // TODO(https://github.com/apache/beam/issues/20497)
  })
  public class SparkSideInputReader implements SideInputReader {
    private final Map<TupleTag<?>, KV<WindowingStrategy<?, ?>, SideInputBroadcast<?>>> sideInputs;
  
    public SparkSideInputReader(
        Map<TupleTag<?>, KV<WindowingStrategy<?, ?>, SideInputBroadcast<?>>> sideInputs) {
      this.sideInputs = sideInputs;
    }
  
    @Override
    public <T> @Nullable T get(PCollectionView<T> view, BoundedWindow window) {
      // --- validate sideInput.
      checkNotNull(view, "The PCollectionView passed to sideInput cannot be null ");
      KV<WindowingStrategy<?, ?>, SideInputBroadcast<?>> windowedBroadcastHelper =
          sideInputs.get(view.getTagInternal());
      checkNotNull(windowedBroadcastHelper, "SideInput for view %s is not available.", view);
  
      // --- sideInput window
      final BoundedWindow sideInputWindow = view.getWindowMappingFn().getSideInputWindow(window);
  
      // --- match the appropriate sideInput window.
      // a tag will point to all matching sideInputs, that is all windows.
      // now that we've obtained the appropriate sideInputWindow, all that's left is to filter by it.
      final SideInputBroadcast<?> sideInputBroadcast = windowedBroadcastHelper.getValue();
      Iterable<WindowedValue<?>> availableSideInputs =
          (Iterable<WindowedValue<?>>) sideInputBroadcast.getValue();
  
      final Stream<WindowedValue<?>> stream =
          StreamSupport.stream(availableSideInputs.spliterator(), false)
              .filter(
                  sideInputCandidate -> {
                    if (sideInputCandidate == null) {
                      return false;
                    }
                    return Iterables.contains(sideInputCandidate.getWindows(), sideInputWindow);
                  });
      final List<?> sideInputForWindow =
          this.getSideInputForWindow(sideInputBroadcast.getSparkPCollectionViewType(), stream);
  
      switch (view.getViewFn().getMaterialization().getUrn()) {
        case Materializations.ITERABLE_MATERIALIZATION_URN:
          {
            ViewFn<IterableView, T> viewFn = (ViewFn<IterableView, T>) view.getViewFn();
            return viewFn.apply(() -> sideInputForWindow);
          }
        case Materializations.MULTIMAP_MATERIALIZATION_URN:
          {
            ViewFn<MultimapView, T> viewFn = (ViewFn<MultimapView, T>) view.getViewFn();
            Coder<?> keyCoder = ((KvCoder<?, ?>) view.getCoderInternal()).getKeyCoder();
            return viewFn.apply(
                InMemoryMultimapSideInputView.fromIterable(keyCoder, (Iterable) sideInputForWindow));
          }
        default:
          throw new IllegalStateException(
              String.format(
                  "Unknown side input materialization format requested '%s'",
                  view.getViewFn().getMaterialization().getUrn()));
      }
    }
  
    /**
     * Extracts side input values from windowed values based on the collection view type.
     *
     * <p>For {@link SparkPCollectionView.Type#STATIC} view types, simply extracts the value from each
     * {@link WindowedValue}.
     *
     * <p>For {@link SparkPCollectionView.Type#STREAMING} view types, performs additional processing
     * by flattening any List values, as streaming side inputs arrive as collections that need to be
     * processed individually.
     *
     * @param sparkPCollectionViewType the type of PCollection view (STATIC or STREAMING)
     * @param stream the stream of WindowedValues filtered for the current window
     * @return a list of extracted side input values
     */
    private List<?> getSideInputForWindow(
        SparkPCollectionView.Type sparkPCollectionViewType, Stream<WindowedValue<?>> stream) {
      switch (sparkPCollectionViewType) {
        case STATIC:
          return stream.map(WindowedValue::getValue).collect(Collectors.toList());
        case STREAMING:
          return stream
              .flatMap(
                  (WindowedValue<?> windowedValue) -> {
                    final Object value = windowedValue.getValue();
                    // Streaming side inputs arrive as List collections.
                    // These lists need to be flattened to process each element individually.
                    if (value instanceof List) {
                      final List<?> list = (List) value;
                      return list.stream();
                    } else {
                      return Stream.of(value);
                    }
                  })
              .collect(Collectors.toList());
        default:
          throw new IllegalStateException(
              String.format("Unknown pcollection view type %s", sparkPCollectionViewType));
      }
    }
  
    @Override
    public <T> boolean contains(PCollectionView<T> view) {
      return sideInputs.containsKey(view.getTagInternal());
    }
  
    @Override
    public boolean isEmpty() {
      return sideInputs != null && sideInputs.isEmpty();
    }
  }
  