saprk core 2.0 Partition CheckpointRDDPartition

/**
 * An identifier for a partition in an RDD.
 */
trait Partition extends Serializable {
  /**
   * Get the partition's index within its parent RDD
   */
  def index: Int

  // A better default implementation of HashCode
  override def hashCode(): Int = index

  override def equals(other: Any): Boolean = super.equals(other)
}

/**
 * An RDD partition used to recover checkpointed data.
 */
private[spark] class CheckpointRDDPartition(val index: Int) extends Partition

/**
 * An RDD that recovers checkpointed data from storage.
 */
private[spark] abstract class CheckpointRDD[T: ClassTag](sc: SparkContext)
  extends RDD[T](sc, Nil) {

  // CheckpointRDD should not be checkpointed again
  override def doCheckpoint(): Unit = { }
  override def checkpoint(): Unit = { }
  override def localCheckpoint(): this.type = this

  // Note: There is a bug in MiMa that complains about `AbstractMethodProblem`s in the
  // base [[org.apache.spark.rdd.RDD]] class if we do not override the following methods.
  // scalastyle:off
  protected override def getPartitions: Array[Partition] = ???
  override def compute(p: Partition, tc: TaskContext): Iterator[T] = ???
  // scalastyle:on

}

/**
 * A dummy CheckpointRDD that exists to provide informative error messages during failures.
 *
 * This is simply a placeholder because the original checkpointed RDD is expected to be
 * fully cached. Only if an executor fails or if the user explicitly unpersists the original
 * RDD will Spark ever attempt to compute this CheckpointRDD. When this happens, however,
 * we must provide an informative error message.
 *
 * @param sc the active SparkContext
 * @param rddId the ID of the checkpointed RDD
 * @param numPartitions the number of partitions in the checkpointed RDD
 */
private[spark] class LocalCheckpointRDD[T: ClassTag](
    sc: SparkContext,
    rddId: Int,
    numPartitions: Int)
  extends CheckpointRDD[T](sc) {

  def this(rdd: RDD[T]) {
    this(rdd.context, rdd.id, rdd.partitions.length)
  }

  protected override def getPartitions: Array[Partition] = {
    (0 until numPartitions).toArray.map { i => new CheckpointRDDPartition(i) }
  }

  /**
   * Throw an exception indicating that the relevant block is not found.
   *
   * This should only be called if the original RDD is explicitly unpersisted or if an
   * executor is lost. Under normal circumstances, however, the original RDD (our child)
   * is expected to be fully cached and so all partitions should already be computed and
   * available in the block storage.
   */
  override def compute(partition: Partition, context: TaskContext): Iterator[T] = {
    throw new SparkException(
      s"Checkpoint block ${RDDBlockId(rddId, partition.index)} not found! Either the executor " +
      s"that originally checkpointed this partition is no longer alive, or the original RDD is " +
      s"unpersisted. If this problem persists, you may consider using `rdd.checkpoint()` " +
      s"instead, which is slower than local checkpointing but more fault-tolerant.")
  }

}