content: /*
   * 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.coders;
  
  import com.esotericsoftware.kryo.Kryo;
  import java.util.ArrayList;
  import java.util.LinkedHashMap;
  import org.apache.beam.runners.spark.io.MicrobatchSource;
  import org.apache.beam.runners.spark.stateful.StateAndTimers;
  import org.apache.beam.runners.spark.translation.ValueAndCoderKryoSerializer;
  import org.apache.beam.runners.spark.translation.ValueAndCoderLazySerializable;
  import org.apache.beam.runners.spark.util.ByteArray;
  import org.apache.beam.sdk.transforms.windowing.PaneInfo;
  import org.apache.beam.sdk.values.KV;
  import org.apache.beam.sdk.values.TupleTag;
  import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.HashBasedTable;
  import org.apache.spark.serializer.KryoRegistrator;
  import scala.collection.mutable.WrappedArray;
  
  /**
   * Custom {@link KryoRegistrator}s for Beam's Spark runner needs and registering used class in spark
   * translation for better serialization performance. This is not the default serialization
   * mechanism.
   *
   * <p>To use it you must enable the Kryo based serializer using {@code spark.serializer} with value
   * {@code org.apache.spark.serializer.KryoSerializer} and register this class via Spark {@code
   * spark.kryo.registrator} configuration.
   */
  @SuppressWarnings({
    "rawtypes" // TODO(https://github.com/apache/beam/issues/20447)
  })
  public class SparkRunnerKryoRegistrator implements KryoRegistrator {
  
    @Override
    public void registerClasses(Kryo kryo) {
      // MicrobatchSource is serialized as data and may not be Kryo-serializable.
      kryo.register(MicrobatchSource.class, new StatelessJavaSerializer());
      kryo.register(ValueAndCoderLazySerializable.class, new ValueAndCoderKryoSerializer());
  
      kryo.register(ArrayList.class);
      kryo.register(ByteArray.class);
      kryo.register(HashBasedTable.class);
      kryo.register(KV.class);
      kryo.register(LinkedHashMap.class);
      kryo.register(Object[].class);
      kryo.register(PaneInfo.class);
      kryo.register(StateAndTimers.class);
      kryo.register(TupleTag.class);
      kryo.register(WrappedArray.ofRef.class);
  
      try {
        kryo.register(
            Class.forName(
                "org.apache.beam.sdk.values.WindowedValues$TimestampedValueInGlobalWindow"));
        kryo.register(
            Class.forName(
                "org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.HashBasedTable$Factory"));
      } catch (ClassNotFoundException e) {
        throw new IllegalStateException("Unable to register classes with kryo.", e);
      }
    }
  }
  