Github user mridulm commented on a diff in the pull request: https://github.com/apache/spark/pull/2030#discussion_r16432379 --- Diff: core/src/main/scala/org/apache/spark/broadcast/TorrentBroadcast.scala --- @@ -18,50 +18,116 @@ package org.apache.spark.broadcast import java.io._ +import java.nio.ByteBuffer +import scala.collection.JavaConversions.asJavaEnumeration import scala.reflect.ClassTag import scala.util.Random import org.apache.spark.{Logging, SparkConf, SparkEnv, SparkException} import org.apache.spark.io.CompressionCodec import org.apache.spark.storage.{BroadcastBlockId, StorageLevel} +import org.apache.spark.util.ByteBufferInputStream /** - * A [[org.apache.spark.broadcast.Broadcast]] implementation that uses a BitTorrent-like - * protocol to do a distributed transfer of the broadcasted data to the executors. - * The mechanism is as follows. The driver divides the serializes the broadcasted data, - * divides it into smaller chunks, and stores them in the BlockManager of the driver. - * These chunks are reported to the BlockManagerMaster so that all the executors can - * learn the location of those chunks. The first time the broadcast variable (sent as - * part of task) is deserialized at a executor, all the chunks are fetched using - * the BlockManager. When all the chunks are fetched (initially from the driver's - * BlockManager), they are combined and deserialized to recreate the broadcasted data. - * However, the chunks are also stored in the BlockManager and reported to the - * BlockManagerMaster. As more executors fetch the chunks, BlockManagerMaster learns - * multiple locations for each chunk. Hence, subsequent fetches of each chunk will be - * made to other executors who already have those chunks, resulting in a distributed - * fetching. This prevents the driver from being the bottleneck in sending out multiple - * copies of the broadcast data (one per executor) as done by the - * [[org.apache.spark.broadcast.HttpBroadcast]]. + * A BitTorrent-like implementation of [[org.apache.spark.broadcast.Broadcast]]. + * + * The mechanism is as follows: + * + * The driver divides the serialized object into small chunks and + * stores those chunks in the BlockManager of the driver. + * + * On each executor, the executor first attempts to fetch the object from its BlockManager. If + * it does not exist, it then uses remote fetches to fetch the small chunks from the driver and/or + * other executors if available. Once it gets the chunks, it puts the chunks in its own + * BlockManager, ready for other executors to fetch from. + * + * This prevents the driver from being the bottleneck in sending out multiple copies of the + * broadcast data (one per executor) as done by the [[org.apache.spark.broadcast.HttpBroadcast]]. + * + * @param obj object to broadcast + * @param isLocal whether Spark is running in local mode (single JVM process). + * @param id A unique identifier for the broadcast variable. */ private[spark] class TorrentBroadcast[T: ClassTag]( - @transient var value_ : T, isLocal: Boolean, id: Long) + obj : T, --- End diff -- and transient ? Not sure if I am missing something here ?
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