geotrellis.spark.util.KryoSerializer.scala Maven / Gradle / Ivy

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GeoTrellis is an open source geographic data processing engine for high performance applications.

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/*
 * Copyright (C) 2012 The Regents of The University California.
 * All rights reserved.
 *
 * Licensed 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 geotrellis.spark.util

import java.nio.ByteBuffer

import org.apache.spark.{SparkConf, SparkEnv}
import org.apache.spark.serializer.{KryoSerializer => SparkKryoSerializer}
import java.io.InputStream
import scala.reflect.ClassTag

/**
 * Java object serialization using Kryo. This is much more efficient, but Kryo
 * sometimes is buggy to use. We use this mainly to serialize the object
 * inspectors.
 */
object KryoSerializer {

  @transient lazy val ser: SparkKryoSerializer = {
    val sparkConf =
      Option(SparkEnv.get)
        .map(_.conf)
        .getOrElse(
          new SparkConf()
            .set("spark.kryo.registrator", classOf[geotrellis.spark.io.kryo.KryoRegistrator].getName)
         )

    new SparkKryoSerializer(sparkConf)
  }

  def serialize[T: ClassTag](o: T): Array[Byte] = {
    ser.newInstance().serialize(o).array()
  }

  def deserialize[T: ClassTag](bytes: Array[Byte]): T  = {
    ser.newInstance().deserialize[T](ByteBuffer.wrap(bytes))
  }

  def deserializeStream[T: ClassTag](is: InputStream): T = {
    ser.newInstance().deserializeStream(is).readObject[T]
  }
}