зеркало из https://github.com/microsoft/spark.git
Fix issue #65: Change @serializable to extends Serializable in 2.9 branch
Note that we use scala.Serializable introduced in Scala 2.9 instead of java.io.Serializable. Also, case classes inherit from scala.Serializable by default.
This commit is contained in:
Родитель
2e57338896
Коммит
0fba22b3d2
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@ -111,8 +111,7 @@ trait Aggregator[V, A] {
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def mergeAggregators(a: A, b: A): A
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}
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@serializable
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class DefaultCombiner[M] extends Combiner[M, ArrayBuffer[M]] {
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class DefaultCombiner[M] extends Combiner[M, ArrayBuffer[M]] with Serializable {
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def createCombiner(msg: M): ArrayBuffer[M] =
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ArrayBuffer(msg)
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def mergeMsg(combiner: ArrayBuffer[M], msg: M): ArrayBuffer[M] =
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@ -121,8 +120,7 @@ class DefaultCombiner[M] extends Combiner[M, ArrayBuffer[M]] {
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a ++= b
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}
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@serializable
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class NullAggregator[V] extends Aggregator[V, Option[Nothing]] {
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class NullAggregator[V] extends Aggregator[V, Option[Nothing]] with Serializable {
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def createAggregator(vert: V): Option[Nothing] = None
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def mergeAggregators(a: Option[Nothing], b: Option[Nothing]): Option[Nothing] = None
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}
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@ -130,8 +128,8 @@ class NullAggregator[V] extends Aggregator[V, Option[Nothing]] {
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/**
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* Represents a Bagel vertex.
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*
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* Subclasses may store state along with each vertex and must be
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* annotated with @serializable.
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* Subclasses may store state along with each vertex and must
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* inherit from java.io.Serializable or scala.Serializable.
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*/
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trait Vertex {
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def id: String
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@ -142,7 +140,7 @@ trait Vertex {
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* Represents a Bagel message to a target vertex.
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*
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* Subclasses may contain a payload to deliver to the target vertex
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* and must be annotated with @serializable.
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* and must inherit from java.io.Serializable or scala.Serializable.
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*/
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trait Message {
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def targetId: String
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@ -151,8 +149,8 @@ trait Message {
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/**
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* Represents a directed edge between two vertices.
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*
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* Subclasses may store state along each edge and must be annotated
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* with @serializable.
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* Subclasses may store state along each edge and must inherit from
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* java.io.Serializable or scala.Serializable.
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*/
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trait Edge {
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def targetId: String
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@ -81,8 +81,7 @@ object ShortestPath {
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}
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}
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@serializable
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object MinCombiner extends Combiner[SPMessage, Int] {
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object MinCombiner extends Combiner[SPMessage, Int] with Serializable {
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def createCombiner(msg: SPMessage): Int =
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msg.value
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def mergeMsg(combiner: Int, msg: SPMessage): Int =
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@ -91,6 +90,6 @@ object MinCombiner extends Combiner[SPMessage, Int] {
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min(a, b)
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}
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@serializable class SPVertex(val id: String, val value: Int, val outEdges: Seq[SPEdge], val active: Boolean) extends Vertex
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@serializable class SPEdge(val targetId: String, val value: Int) extends Edge
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@serializable class SPMessage(val targetId: String, val value: Int) extends Message
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class SPVertex(val id: String, val value: Int, val outEdges: Seq[SPEdge], val active: Boolean) extends Vertex with Serializable
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class SPEdge(val targetId: String, val value: Int) extends Edge with Serializable
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class SPMessage(val targetId: String, val value: Int) extends Message with Serializable
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@ -76,8 +76,7 @@ object WikipediaPageRank {
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}
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}
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@serializable
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object PRCombiner extends Combiner[PRMessage, Double] {
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object PRCombiner extends Combiner[PRMessage, Double] with Serializable {
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def createCombiner(msg: PRMessage): Double =
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msg.value
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def mergeMsg(combiner: Double, msg: PRMessage): Double =
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@ -105,8 +104,7 @@ object PRCombiner extends Combiner[PRMessage, Double] {
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}
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}
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@serializable
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object PRNoCombiner extends DefaultCombiner[PRMessage] {
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object PRNoCombiner extends DefaultCombiner[PRMessage] with Serializable {
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def compute(numVertices: Long, epsilon: Double)(self: PRVertex, messages: Option[ArrayBuffer[PRMessage]], superstep: Int): (PRVertex, Iterable[PRMessage]) =
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PRCombiner.compute(numVertices, epsilon)(self, messages match {
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case Some(msgs) => Some(msgs.map(_.value).sum)
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@ -114,7 +112,7 @@ object PRNoCombiner extends DefaultCombiner[PRMessage] {
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}, superstep)
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}
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@serializable class PRVertex() extends Vertex {
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class PRVertex() extends Vertex with Serializable {
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var id: String = _
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var value: Double = _
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var outEdges: ArrayBuffer[PREdge] = _
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@ -129,7 +127,7 @@ object PRNoCombiner extends DefaultCombiner[PRMessage] {
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}
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}
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@serializable class PRMessage() extends Message {
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class PRMessage() extends Message with Serializable {
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var targetId: String = _
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var value: Double = _
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@ -140,7 +138,7 @@ object PRNoCombiner extends DefaultCombiner[PRMessage] {
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}
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}
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@serializable class PREdge() extends Edge {
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class PREdge() extends Edge with Serializable {
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var targetId: String = _
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def this(targetId: String) {
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@ -12,8 +12,8 @@ import spark._
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import spark.bagel.Bagel._
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@serializable class TestVertex(val id: String, val active: Boolean, val age: Int) extends Vertex
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@serializable class TestMessage(val targetId: String) extends Message
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class TestVertex(val id: String, val active: Boolean, val age: Int) extends Vertex with Serializable
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class TestMessage(val targetId: String) extends Message with Serializable
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class BagelSuite extends FunSuite with Assertions {
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test("halting by voting") {
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@ -4,8 +4,8 @@ import java.io._
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import scala.collection.mutable.Map
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@serializable class Accumulator[T](
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@transient initialValue: T, param: AccumulatorParam[T])
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class Accumulator[T] (
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@transient initialValue: T, param: AccumulatorParam[T]) extends Serializable
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{
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val id = Accumulators.newId
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@transient var value_ = initialValue // Current value on master
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@ -32,7 +32,7 @@ import scala.collection.mutable.Map
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override def toString = value_.toString
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}
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@serializable trait AccumulatorParam[T] {
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trait AccumulatorParam[T] extends Serializable {
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def addInPlace(t1: T, t2: T): T
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def zero(initialValue: T): T
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}
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@ -1,8 +1,7 @@
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package spark
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@serializable
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class Aggregator[K, V, C] (
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val createCombiner: V => C,
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val mergeValue: (C, V) => C,
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val mergeCombiners: (C, C) => C
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)
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) extends Serializable
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@ -1,14 +1,13 @@
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package spark
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@serializable class CartesianSplit(idx: Int, val s1: Split, val s2: Split)
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extends Split {
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class CartesianSplit(idx: Int, val s1: Split, val s2: Split)
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extends Split with Serializable {
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override val index = idx
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}
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@serializable
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class CartesianRDD[T: ClassManifest, U:ClassManifest](
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sc: SparkContext, rdd1: RDD[T], rdd2: RDD[U])
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extends RDD[Pair[T, U]](sc) {
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extends RDD[Pair[T, U]](sc) with Serializable {
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val numSplitsInRdd2 = rdd2.splits.size
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@transient val splits_ = {
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@ -6,24 +6,21 @@ import java.io.ObjectInputStream
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import scala.collection.mutable.ArrayBuffer
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import scala.collection.mutable.HashMap
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@serializable
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sealed trait CoGroupSplitDep
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sealed trait CoGroupSplitDep extends Serializable
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case class NarrowCoGroupSplitDep(rdd: RDD[_], split: Split) extends CoGroupSplitDep
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case class ShuffleCoGroupSplitDep(shuffleId: Int) extends CoGroupSplitDep
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@serializable
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class CoGroupSplit(idx: Int, val deps: Seq[CoGroupSplitDep])
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extends Split {
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extends Split with Serializable {
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override val index = idx
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override def hashCode(): Int = idx
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}
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@serializable
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class CoGroupAggregator extends Aggregator[Any, Any, ArrayBuffer[Any]] (
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{ x => ArrayBuffer(x) },
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{ (b, x) => b += x },
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{ (b1, b2) => b1 ++ b2 }
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)
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) with Serializable
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class CoGroupedRDD[K](rdds: Seq[RDD[(_, _)]], part: Partitioner)
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extends RDD[(K, Seq[Seq[_]])](rdds.head.context) with Logging {
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@ -1,7 +1,6 @@
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package spark
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@serializable
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abstract class Dependency[T](val rdd: RDD[T], val isShuffle: Boolean)
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abstract class Dependency[T](val rdd: RDD[T], val isShuffle: Boolean) extends Serializable
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abstract class NarrowDependency[T](rdd: RDD[T])
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extends Dependency(rdd, false) {
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@ -13,8 +13,8 @@ import org.apache.hadoop.mapred.Reporter
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import org.apache.hadoop.util.ReflectionUtils
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/** A Spark split class that wraps around a Hadoop InputSplit */
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@serializable class HadoopSplit(rddId: Int, idx: Int, @transient s: InputSplit)
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extends Split {
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class HadoopSplit(rddId: Int, idx: Int, @transient s: InputSplit)
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extends Split with Serializable {
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val inputSplit = new SerializableWritable[InputSplit](s)
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override def hashCode(): Int = (41 * (41 + rddId) + idx).toInt
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@ -20,7 +20,7 @@ import spark.Logging
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* also contain an output key class, an output value class, a filename to write to, etc
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* exactly like in a Hadoop job.
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*/
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@serializable class HadoopWriter(@transient jobConf: JobConf) extends Logging {
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class HadoopWriter(@transient jobConf: JobConf) extends Logging with Serializable {
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private val now = new Date()
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private val conf = new SerializableWritable(jobConf)
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@ -30,8 +30,7 @@ import SparkContext._
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/**
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* Extra functions available on RDDs of (key, value) pairs through an implicit conversion.
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*/
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@serializable
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class PairRDDFunctions[K: ClassManifest, V: ClassManifest](self: RDD[(K, V)]) extends Logging {
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class PairRDDFunctions[K: ClassManifest, V: ClassManifest](self: RDD[(K, V)]) extends Logging with Serializable {
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def reduceByKeyToDriver(func: (V, V) => V): Map[K, V] = {
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def mergeMaps(m1: HashMap[K, V], m2: HashMap[K, V]): HashMap[K, V] = {
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for ((k, v) <- m2) {
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@ -2,9 +2,9 @@ package spark
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import java.util.concurrent.atomic.AtomicLong
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@serializable class ParallelCollectionSplit[T: ClassManifest](
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class ParallelCollectionSplit[T: ClassManifest](
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val rddId: Long, val slice: Int, values: Seq[T])
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extends Split {
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extends Split with Serializable {
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def iterator(): Iterator[T] = values.iterator
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override def hashCode(): Int = (41 * (41 + rddId) + slice).toInt
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@ -1,7 +1,6 @@
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package spark
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@serializable
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abstract class Partitioner {
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abstract class Partitioner extends Serializable {
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def numPartitions: Int
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def getPartition(key: Any): Int
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}
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@ -44,8 +44,7 @@ import SparkContext._
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* In addition, PairRDDFunctions contains extra methods available on RDDs of key-value pairs,
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* and SequenceFileRDDFunctions contains extra methods for saving RDDs to Hadoop SequenceFiles.
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*/
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@serializable
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abstract class RDD[T: ClassManifest](@transient sc: SparkContext) {
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abstract class RDD[T: ClassManifest](@transient sc: SparkContext) extends Serializable {
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// Methods that must be implemented by subclasses
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def splits: Array[Split]
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def compute(split: Split): Iterator[T]
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@ -2,7 +2,7 @@ package spark
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import java.util.Random
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@serializable class SampledRDDSplit(val prev: Split, val seed: Int) extends Split {
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class SampledRDDSplit(val prev: Split, val seed: Int) extends Split with Serializable {
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override val index = prev.index
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}
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@ -31,8 +31,7 @@ import SparkContext._
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* through an implicit conversion. Note that this can't be part of PairRDDFunctions because
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* we need more implicit parameters to convert our keys and values to Writable.
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*/
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@serializable
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class SequenceFileRDDFunctions[K <% Writable: ClassManifest, V <% Writable : ClassManifest](self: RDD[(K,V)]) extends Logging {
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class SequenceFileRDDFunctions[K <% Writable: ClassManifest, V <% Writable : ClassManifest](self: RDD[(K,V)]) extends Logging with Serializable {
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def getWritableClass[T <% Writable: ClassManifest](): Class[_ <: Writable] = {
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val c = {
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if (classOf[Writable].isAssignableFrom(classManifest[T].erasure))
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@ -6,8 +6,7 @@ import org.apache.hadoop.io.ObjectWritable
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import org.apache.hadoop.io.Writable
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import org.apache.hadoop.mapred.JobConf
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@serializable
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class SerializableWritable[T <: Writable](@transient var t: T) {
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class SerializableWritable[T <: Writable](@transient var t: T) extends Serializable {
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def value = t
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override def toString = t.toString
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@ -363,5 +363,4 @@ object SparkContext {
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* that doesn't know the type of T when it is created. This sounds strange but is necessary to
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* support converting subclasses of Writable to themselves (writableWritableConverter).
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*/
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@serializable
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class WritableConverter[T](val writableClass: ClassManifest[T] => Class[_ <: Writable], val convert: Writable => T) {}
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class WritableConverter[T](val writableClass: ClassManifest[T] => Class[_ <: Writable], val convert: Writable => T) extends Serializable
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@ -3,7 +3,7 @@ package spark
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/**
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* A partition of an RDD.
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*/
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@serializable trait Split {
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trait Split extends Serializable {
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/**
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* Get the split's index within its parent RDD
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*/
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@ -1,11 +1,8 @@
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package spark
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@serializable
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class TaskContext(val stageId: Int, val splitId: Int, val attemptId: Int) {
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}
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class TaskContext(val stageId: Int, val splitId: Int, val attemptId: Int) extends Serializable
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@serializable
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abstract class Task[T] {
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abstract class Task[T] extends Serializable {
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def run (id: Int): T
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def preferredLocations: Seq[String] = Nil
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def generation: Option[Long] = None
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|
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@ -5,5 +5,4 @@ import scala.collection.mutable.Map
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// Task result. Also contains updates to accumulator variables.
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// TODO: Use of distributed cache to return result is a hack to get around
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// what seems to be a bug with messages over 60KB in libprocess; fix it
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@serializable
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private class TaskResult[T](val value: T, val accumUpdates: Map[Long, Any])
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private class TaskResult[T](val value: T, val accumUpdates: Map[Long, Any]) extends Serializable
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|
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|
@ -2,17 +2,15 @@ package spark
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import scala.collection.mutable.ArrayBuffer
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@serializable
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class UnionSplit[T: ClassManifest](idx: Int, rdd: RDD[T], split: Split)
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extends Split {
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extends Split with Serializable {
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def iterator() = rdd.iterator(split)
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def preferredLocations() = rdd.preferredLocations(split)
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override val index = idx
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}
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@serializable
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class UnionRDD[T: ClassManifest](sc: SparkContext, rdds: Seq[RDD[T]])
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extends RDD[T](sc) {
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extends RDD[T](sc) with Serializable {
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@transient val splits_ : Array[Split] = {
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val array = new Array[Split](rdds.map(_.splits.size).sum)
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var pos = 0
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|
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@ -10,9 +10,8 @@ import scala.math
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import spark._
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@serializable
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class BitTorrentBroadcast[T](@transient var value_ : T, isLocal: Boolean)
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extends Broadcast[T] with Logging {
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extends Broadcast[T] with Logging with Serializable {
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def value = value_
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|
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@ -7,8 +7,7 @@ import java.util.concurrent.{Executors, ThreadFactory, ThreadPoolExecutor}
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import spark._
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@serializable
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trait Broadcast[T] {
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trait Broadcast[T] extends Serializable {
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val uuid = UUID.randomUUID
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def value: T
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@ -20,7 +19,7 @@ trait Broadcast[T] {
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}
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object Broadcast
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extends Logging {
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extends Logging with Serializable {
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// Messages
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val REGISTER_BROADCAST_TRACKER = 0
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val UNREGISTER_BROADCAST_TRACKER = 1
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|
@ -191,18 +190,15 @@ extends Logging {
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|||
}
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}
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@serializable
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||||
case class BroadcastBlock (val blockID: Int, val byteArray: Array[Byte]) { }
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case class BroadcastBlock (val blockID: Int, val byteArray: Array[Byte]) extends Serializable
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@serializable
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||||
case class VariableInfo (@transient val arrayOfBlocks : Array[BroadcastBlock],
|
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val totalBlocks: Int,
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val totalBytes: Int) {
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val totalBytes: Int) extends Serializable {
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@transient var hasBlocks = 0
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||||
}
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||||
|
||||
@serializable
|
||||
class SpeedTracker {
|
||||
class SpeedTracker extends Serializable {
|
||||
// Mapping 'source' to '(totalTime, numBlocks)'
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||||
private var sourceToSpeedMap = Map[SourceInfo, (Long, Int)] ()
|
||||
|
||||
|
|
|
@ -9,9 +9,8 @@ import scala.math
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|||
|
||||
import spark._
|
||||
|
||||
@serializable
|
||||
class ChainedBroadcast[T](@transient var value_ : T, isLocal: Boolean)
|
||||
extends Broadcast[T] with Logging {
|
||||
extends Broadcast[T] with Logging with Serializable {
|
||||
|
||||
def value = value_
|
||||
|
||||
|
|
|
@ -11,9 +11,8 @@ import org.apache.hadoop.fs.{FileSystem, Path, RawLocalFileSystem}
|
|||
|
||||
import spark._
|
||||
|
||||
@serializable
|
||||
class DfsBroadcast[T](@transient var value_ : T, isLocal: Boolean)
|
||||
extends Broadcast[T] with Logging {
|
||||
extends Broadcast[T] with Logging with Serializable {
|
||||
|
||||
def value = value_
|
||||
|
||||
|
|
|
@ -10,7 +10,6 @@ import spark._
|
|||
* CHANGED: Keep track of the blockSize for THIS broadcast variable.
|
||||
* Broadcast.BlockSize is expected to be updated across different broadcasts
|
||||
*/
|
||||
@serializable
|
||||
case class SourceInfo (val hostAddress: String,
|
||||
val listenPort: Int,
|
||||
val totalBlocks: Int = SourceInfo.UnusedParam,
|
||||
|
|
|
@ -9,9 +9,8 @@ import scala.math
|
|||
|
||||
import spark._
|
||||
|
||||
@serializable
|
||||
class TreeBroadcast[T](@transient var value_ : T, isLocal: Boolean)
|
||||
extends Broadcast[T] with Logging {
|
||||
extends Broadcast[T] with Logging with Serializable {
|
||||
|
||||
def value = value_
|
||||
|
||||
|
|
|
@ -1,6 +1,6 @@
|
|||
package spark.examples
|
||||
|
||||
@serializable class Vector(val elements: Array[Double]) {
|
||||
class Vector(val elements: Array[Double]) extends Serializable {
|
||||
def length = elements.length
|
||||
|
||||
def apply(index: Int) = elements(index)
|
||||
|
|
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Ссылка в новой задаче