merged and debugged
This commit is contained in:
Joseph E. Gonzalez
commit
e523f0d2fb
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@ -22,7 +22,7 @@ import org.apache.spark.SparkContext._
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import org.apache.spark.rdd._
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import org.apache.spark.storage.StorageLevel
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import org.apache.spark.util.collection.{BitSet, OpenHashSet, PrimitiveKeyOpenHashMap}
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import org.apache.spark.graph.impl.AggregationMsg
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/**
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* The `VertexSetIndex` maintains the per-partition mapping from
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@ -659,6 +659,43 @@ object VertexSetRDD {
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apply(rdd,index, (v:V) => v, reduceFunc, reduceFunc)
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def aggregate[V: ClassManifest](
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rdd: RDD[AggregationMsg[V]], index: VertexSetIndex,
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reduceFunc: (V, V) => V): VertexSetRDD[V] = {
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val cReduceFunc = index.rdd.context.clean(reduceFunc)
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assert(rdd.partitioner == index.rdd.partitioner)
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// Use the index to build the new values table
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val values: RDD[ (Array[V], BitSet) ] = index.rdd.zipPartitions(rdd)( (indexIter, tblIter) => {
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// There is only one map
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val index = indexIter.next()
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assert(!indexIter.hasNext)
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val values = new Array[V](index.capacity)
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val bs = new BitSet(index.capacity)
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for (msg <- tblIter) {
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// Get the location of the key in the index
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val pos = index.getPos(msg.vid)
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if ((pos & OpenHashSet.NONEXISTENCE_MASK) != 0) {
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throw new SparkException("Error: Trying to bind an external index " +
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"to an RDD which contains keys that are not in the index.")
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} else {
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// Get the actual index
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val ind = pos & OpenHashSet.POSITION_MASK
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// If this value has already been seen then merge
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if (bs.get(ind)) {
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values(ind) = cReduceFunc(values(ind), msg.data)
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} else { // otherwise just store the new value
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bs.set(ind)
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values(ind) = msg.data
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}
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}
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}
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Iterator((values, bs))
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})
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new VertexSetRDD(index, values)
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}
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/**
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* Construct a vertex set from an RDD using an existing index and a
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* user defined `combiner` to merge duplicate vertices.
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@ -5,14 +5,13 @@ import scala.collection.JavaConversions._
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import scala.collection.mutable
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import scala.collection.mutable.ArrayBuffer
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import org.apache.spark.SparkContext._
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import org.apache.spark.HashPartitioner
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import org.apache.spark.util.ClosureCleaner
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import org.apache.spark.graph._
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import org.apache.spark.graph.impl.GraphImpl._
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import org.apache.spark.graph.impl.MessageToPartitionRDDFunctions._
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import org.apache.spark.graph.impl.MsgRDDFunctions._
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import org.apache.spark.rdd.RDD
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import org.apache.spark.storage.StorageLevel
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import org.apache.spark.util.collection.{BitSet, OpenHashSet, PrimitiveKeyOpenHashMap}
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@ -73,8 +72,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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def this() = this(null, null, null, null)
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/**
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* (localVidMap: VertexSetRDD[Pid, VertexIdToIndexMap]) is a version of the
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* vertex data after it is replicated. Within each partition, it holds a map
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@ -87,22 +84,18 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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@transient val vTableReplicatedValues: RDD[(Pid, Array[VD])] =
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createVTableReplicated(vTable, vid2pid, localVidMap)
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/** Return a RDD of vertices. */
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@transient override val vertices = vTable
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/** Return a RDD of edges. */
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@transient override val edges: RDD[Edge[ED]] = {
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eTable.mapPartitions( iter => iter.next()._2.iterator , true )
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}
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/** Return a RDD that brings edges with its source and destination vertices together. */
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@transient override val triplets: RDD[EdgeTriplet[VD, ED]] =
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makeTriplets(localVidMap, vTableReplicatedValues, eTable)
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override def persist(newLevel: StorageLevel): Graph[VD, ED] = {
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eTable.persist(newLevel)
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vid2pid.persist(newLevel)
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@ -129,7 +122,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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"Min Load" -> minLoad, "Max Load" -> maxLoad)
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}
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/**
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* Display the lineage information for this graph.
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*/
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@ -187,14 +179,12 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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println(visited)
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} // end of print lineage
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override def reverse: Graph[VD, ED] = {
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val newEtable = eTable.mapPartitions( _.map{ case (pid, epart) => (pid, epart.reverse) },
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preservesPartitioning = true)
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new GraphImpl(vTable, vid2pid, localVidMap, newEtable)
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}
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override def mapVertices[VD2: ClassManifest](f: (Vid, VD) => VD2): Graph[VD2, ED] = {
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val newVTable = vTable.mapValuesWithKeys((vid, data) => f(vid, data))
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new GraphImpl(newVTable, vid2pid, localVidMap, eTable)
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@ -206,11 +196,9 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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new GraphImpl(vTable, vid2pid, localVidMap, newETable)
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}
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override def mapTriplets[ED2: ClassManifest](f: EdgeTriplet[VD, ED] => ED2): Graph[VD, ED2] =
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GraphImpl.mapTriplets(this, f)
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override def subgraph(epred: EdgeTriplet[VD,ED] => Boolean = (x => true),
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vpred: (Vid, VD) => Boolean = ((a,b) => true) ): Graph[VD, ED] = {
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@ -250,7 +238,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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new GraphImpl(newVTable, newVid2Pid, localVidMap, newETable)
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}
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override def groupEdgeTriplets[ED2: ClassManifest](
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f: Iterator[EdgeTriplet[VD,ED]] => ED2 ): Graph[VD,ED2] = {
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val newEdges: RDD[Edge[ED2]] = triplets.mapPartitions { partIter =>
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@ -275,7 +262,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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new GraphImpl(vTable, vid2pid, localVidMap, newETable)
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}
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override def groupEdges[ED2: ClassManifest](f: Iterator[Edge[ED]] => ED2 ):
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Graph[VD,ED2] = {
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@ -293,8 +279,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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new GraphImpl(vTable, vid2pid, localVidMap, newETable)
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}
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//////////////////////////////////////////////////////////////////////////////////////////////////
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// Lower level transformation methods
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//////////////////////////////////////////////////////////////////////////////////////////////////
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@ -305,7 +289,6 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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: VertexSetRDD[A] =
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GraphImpl.mapReduceTriplets(this, mapFunc, reduceFunc)
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override def outerJoinVertices[U: ClassManifest, VD2: ClassManifest]
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(updates: RDD[(Vid, U)])(updateF: (Vid, VD, Option[U]) => VD2)
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: Graph[VD2, ED] = {
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@ -313,15 +296,9 @@ class GraphImpl[VD: ClassManifest, ED: ClassManifest] protected (
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val newVTable = vTable.leftJoin(updates)(updateF)
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new GraphImpl(newVTable, vid2pid, localVidMap, eTable)
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}
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} // end of class GraphImpl
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object GraphImpl {
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def apply[VD: ClassManifest, ED: ClassManifest](
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@ -331,7 +308,6 @@ object GraphImpl {
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apply(vertices, edges, defaultVertexAttr, (a:VD, b:VD) => a)
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}
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def apply[VD: ClassManifest, ED: ClassManifest](
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vertices: RDD[(Vid, VD)],
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edges: RDD[Edge[ED]],
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@ -357,7 +333,6 @@ object GraphImpl {
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new GraphImpl(vtable, vid2pid, localVidMap, etable)
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}
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/**
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* Create the edge table RDD, which is much more efficient for Java heap storage than the
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* normal edges data structure (RDD[(Vid, Vid, ED)]).
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@ -379,7 +354,7 @@ object GraphImpl {
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//val part: Pid = canonicalEdgePartitionFunction2D(e.srcId, e.dstId, numPartitions, ceilSqrt)
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// Should we be using 3-tuple or an optimized class
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MessageToPartition(part, (e.srcId, e.dstId, e.attr))
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new MessageToPartition(part, (e.srcId, e.dstId, e.attr))
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}
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.partitionBy(new HashPartitioner(numPartitions))
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.mapPartitionsWithIndex( (pid, iter) => {
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@ -393,7 +368,6 @@ object GraphImpl {
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}, preservesPartitioning = true).cache()
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}
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protected def createVid2Pid[ED: ClassManifest](
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eTable: RDD[(Pid, EdgePartition[ED])],
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vTableIndex: VertexSetIndex): VertexSetRDD[Array[Pid]] = {
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@ -410,7 +384,6 @@ object GraphImpl {
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.mapValues(a => a.toArray).cache()
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}
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protected def createLocalVidMap[ED: ClassManifest](eTable: RDD[(Pid, EdgePartition[ED])]):
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RDD[(Pid, VertexIdToIndexMap)] = {
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eTable.mapPartitions( _.map{ case (pid, epart) =>
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@ -423,7 +396,6 @@ object GraphImpl {
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}, preservesPartitioning = true).cache()
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}
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protected def createVTableReplicated[VD: ClassManifest](
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vTable: VertexSetRDD[VD],
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vid2pid: VertexSetRDD[Array[Pid]],
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@ -432,7 +404,10 @@ object GraphImpl {
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// Join vid2pid and vTable, generate a shuffle dependency on the joined
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// result, and get the shuffle id so we can use it on the slave.
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val msgsByPartition = vTable.zipJoinFlatMap(vid2pid) { (vid, vdata, pids) =>
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pids.iterator.map { pid => MessageToPartition(pid, (vid, vdata)) }
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// TODO(rxin): reuse VertexBroadcastMessage
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pids.iterator.map { pid =>
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new VertexBroadcastMsg[VD](pid, vid, vdata)
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}
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}.partitionBy(replicationMap.partitioner.get).cache()
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replicationMap.zipPartitions(msgsByPartition){
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@ -442,8 +417,8 @@ object GraphImpl {
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// Populate the vertex array using the vidToIndex map
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val vertexArray = new Array[VD](vidToIndex.capacity)
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for (msg <- msgsIter) {
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val ind = vidToIndex.getPos(msg.data._1) & OpenHashSet.POSITION_MASK
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vertexArray(ind) = msg.data._2
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val ind = vidToIndex.getPos(msg.vid) & OpenHashSet.POSITION_MASK
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vertexArray(ind) = msg.data
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}
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Iterator((pid, vertexArray))
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}.cache()
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@ -451,7 +426,6 @@ object GraphImpl {
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// @todo assert edge table has partitioner
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}
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def makeTriplets[VD: ClassManifest, ED: ClassManifest](
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localVidMap: RDD[(Pid, VertexIdToIndexMap)],
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vTableReplicatedValues: RDD[(Pid, Array[VD]) ],
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@ -465,7 +439,6 @@ object GraphImpl {
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}
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}
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def mapTriplets[VD: ClassManifest, ED: ClassManifest, ED2: ClassManifest](
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g: GraphImpl[VD, ED],
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f: EdgeTriplet[VD, ED] => ED2): Graph[VD, ED2] = {
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@ -487,7 +460,6 @@ object GraphImpl {
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new GraphImpl(g.vTable, g.vid2pid, g.localVidMap, newETable)
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}
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def mapReduceTriplets[VD: ClassManifest, ED: ClassManifest, A: ClassManifest](
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g: GraphImpl[VD, ED],
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mapFunc: EdgeTriplet[VD, ED] => Array[(Vid, A)],
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@ -499,33 +471,35 @@ object GraphImpl {
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// Map and preaggregate
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val preAgg = g.eTable.zipPartitions(g.localVidMap, g.vTableReplicatedValues){
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(edgePartitionIter, vidToIndexIter, vertexArrayIter) =>
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val (pid, edgePartition) = edgePartitionIter.next()
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val (_, edgePartition) = edgePartitionIter.next()
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val (_, vidToIndex) = vidToIndexIter.next()
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val (_, vertexArray) = vertexArrayIter.next()
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assert(!edgePartitionIter.hasNext)
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assert(!vidToIndexIter.hasNext)
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assert(!vertexArrayIter.hasNext)
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assert(vidToIndex.capacity == vertexArray.size)
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// Reuse the vidToIndex map to run aggregation.
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val vmap = new PrimitiveKeyOpenHashMap[Vid, VD](vidToIndex, vertexArray)
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// We can reuse the vidToIndex map for aggregation here as well.
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/** @todo Since this has the downside of not allowing "messages" to arbitrary
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* vertices we should consider just using a fresh map.
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*/
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// TODO(jegonzal): This doesn't allow users to send messages to arbitrary vertices.
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val msgArray = new Array[A](vertexArray.size)
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val msgBS = new BitSet(vertexArray.size)
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// Iterate over the partition
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val et = new EdgeTriplet[VD, ED]
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edgePartition.foreach{e =>
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edgePartition.foreach { e =>
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et.set(e)
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et.srcAttr = vmap(e.srcId)
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et.dstAttr = vmap(e.dstId)
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mapFunc(et).foreach{ case (vid, msg) =>
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// TODO(rxin): rewrite the foreach using a simple while loop to speed things up.
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// Also given we are only allowing zero, one, or two messages, we can completely unroll
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// the for loop.
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mapFunc(et).foreach { case (vid, msg) =>
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// verify that the vid is valid
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assert(vid == et.srcId || vid == et.dstId)
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// Get the index of the key
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val ind = vidToIndex.getPos(vid) & OpenHashSet.POSITION_MASK
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// Populate the aggregator map
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if(msgBS.get(ind)) {
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if (msgBS.get(ind)) {
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msgArray(ind) = reduceFunc(msgArray(ind), msg)
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} else {
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msgArray(ind) = msg
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@ -534,20 +508,19 @@ object GraphImpl {
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}
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}
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// construct an iterator of tuples Iterator[(Vid, A)]
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msgBS.iterator.map( ind => (vidToIndex.getValue(ind), msgArray(ind)) )
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msgBS.iterator.map { ind =>
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new AggregationMsg[A](vidToIndex.getValue(ind), msgArray(ind))
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}
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}.partitionBy(g.vTable.index.rdd.partitioner.get)
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// do the final reduction reusing the index map
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VertexSetRDD(preAgg, g.vTable.index, reduceFunc)
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VertexSetRDD.aggregate(preAgg, g.vTable.index, reduceFunc)
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}
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protected def edgePartitionFunction1D(src: Vid, dst: Vid, numParts: Pid): Pid = {
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val mixingPrime: Vid = 1125899906842597L
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(math.abs(src) * mixingPrime).toInt % numParts
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}
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/**
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* This function implements a classic 2D-Partitioning of a sparse matrix.
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* Suppose we have a graph with 11 vertices that we want to partition
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@ -600,7 +573,6 @@ object GraphImpl {
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(col * ceilSqrtNumParts + row) % numParts
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}
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/**
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* Assign edges to an aribtrary machine corresponding to a
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* random vertex cut.
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@ -609,7 +581,6 @@ object GraphImpl {
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math.abs((src, dst).hashCode()) % numParts
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}
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/**
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* @todo This will only partition edges to the upper diagonal
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* of the 2D processor space.
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@ -626,4 +597,3 @@ object GraphImpl {
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}
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} // end of object GraphImpl
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|
|
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@ -1,10 +1,35 @@
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package org.apache.spark.graph.impl
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import org.apache.spark.Partitioner
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import org.apache.spark.graph.Pid
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import org.apache.spark.graph.{Pid, Vid}
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import org.apache.spark.rdd.{ShuffledRDD, RDD}
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class VertexBroadcastMsg[@specialized(Int, Long, Double, Boolean) T](
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@transient var partition: Pid,
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var vid: Vid,
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var data: T)
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extends Product2[Pid, (Vid, T)] {
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override def _1 = partition
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override def _2 = (vid, data)
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override def canEqual(that: Any): Boolean = that.isInstanceOf[VertexBroadcastMsg[_]]
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}
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class AggregationMsg[@specialized(Int, Long, Double, Boolean) T](var vid: Vid, var data: T)
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extends Product2[Vid, T] {
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|
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override def _1 = vid
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override def _2 = data
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|
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override def canEqual(that: Any): Boolean = that.isInstanceOf[AggregationMsg[_]]
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}
|
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|
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|
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/**
|
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* A message used to send a specific value to a partition.
|
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* @param partition index of the target partition.
|
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|
|
@ -22,15 +47,38 @@ class MessageToPartition[@specialized(Int, Long, Double, Char, Boolean/*, AnyRef
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override def canEqual(that: Any): Boolean = that.isInstanceOf[MessageToPartition[_]]
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}
|
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|
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/**
|
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* Companion object for MessageToPartition.
|
||||
*/
|
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object MessageToPartition {
|
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def apply[T](partition: Pid, value: T) = new MessageToPartition(partition, value)
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|
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class VertexBroadcastMsgRDDFunctions[T: ClassManifest](self: RDD[VertexBroadcastMsg[T]]) {
|
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def partitionBy(partitioner: Partitioner): RDD[VertexBroadcastMsg[T]] = {
|
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val rdd = new ShuffledRDD[Pid, (Vid, T), VertexBroadcastMsg[T]](self, partitioner)
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|
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// Set a custom serializer if the data is of int or double type.
|
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if (classManifest[T] == ClassManifest.Int) {
|
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rdd.setSerializer(classOf[IntVertexBroadcastMsgSerializer].getName)
|
||||
} else if (classManifest[T] == ClassManifest.Double) {
|
||||
rdd.setSerializer(classOf[DoubleVertexBroadcastMsgSerializer].getName)
|
||||
}
|
||||
rdd
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
class MessageToPartitionRDDFunctions[T: ClassManifest](self: RDD[MessageToPartition[T]]) {
|
||||
class AggregationMessageRDDFunctions[T: ClassManifest](self: RDD[AggregationMsg[T]]) {
|
||||
def partitionBy(partitioner: Partitioner): RDD[AggregationMsg[T]] = {
|
||||
val rdd = new ShuffledRDD[Vid, T, AggregationMsg[T]](self, partitioner)
|
||||
|
||||
// Set a custom serializer if the data is of int or double type.
|
||||
if (classManifest[T] == ClassManifest.Int) {
|
||||
rdd.setSerializer(classOf[IntAggMsgSerializer].getName)
|
||||
} else if (classManifest[T] == ClassManifest.Double) {
|
||||
rdd.setSerializer(classOf[DoubleAggMsgSerializer].getName)
|
||||
}
|
||||
rdd
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
class MsgRDDFunctions[T: ClassManifest](self: RDD[MessageToPartition[T]]) {
|
||||
|
||||
/**
|
||||
* Return a copy of the RDD partitioned using the specified partitioner.
|
||||
|
|
@ -42,8 +90,16 @@ class MessageToPartitionRDDFunctions[T: ClassManifest](self: RDD[MessageToPartit
|
|||
}
|
||||
|
||||
|
||||
object MessageToPartitionRDDFunctions {
|
||||
object MsgRDDFunctions {
|
||||
implicit def rdd2PartitionRDDFunctions[T: ClassManifest](rdd: RDD[MessageToPartition[T]]) = {
|
||||
new MessageToPartitionRDDFunctions(rdd)
|
||||
new MsgRDDFunctions(rdd)
|
||||
}
|
||||
|
||||
implicit def rdd2vertexMessageRDDFunctions[T: ClassManifest](rdd: RDD[VertexBroadcastMsg[T]]) = {
|
||||
new VertexBroadcastMsgRDDFunctions(rdd)
|
||||
}
|
||||
|
||||
implicit def rdd2aggMessageRDDFunctions[T: ClassManifest](rdd: RDD[AggregationMsg[T]]) = {
|
||||
new AggregationMessageRDDFunctions(rdd)
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,169 @@
|
|||
package org.apache.spark.graph.impl
|
||||
|
||||
import java.io.{InputStream, OutputStream}
|
||||
import java.nio.ByteBuffer
|
||||
|
||||
import org.apache.spark.serializer.{DeserializationStream, SerializationStream, SerializerInstance, Serializer}
|
||||
|
||||
|
||||
/** A special shuffle serializer for VertexBroadcastMessage[Int]. */
|
||||
class IntVertexBroadcastMsgSerializer extends Serializer {
|
||||
override def newInstance(): SerializerInstance = new ShuffleSerializerInstance {
|
||||
|
||||
override def serializeStream(s: OutputStream) = new ShuffleSerializationStream(s) {
|
||||
def writeObject[T](t: T) = {
|
||||
val msg = t.asInstanceOf[VertexBroadcastMsg[Int]]
|
||||
writeLong(msg.vid)
|
||||
writeInt(msg.data)
|
||||
this
|
||||
}
|
||||
}
|
||||
|
||||
override def deserializeStream(s: InputStream) = new ShuffleDeserializationStream(s) {
|
||||
override def readObject[T](): T = {
|
||||
new VertexBroadcastMsg[Int](0, readLong(), readInt()).asInstanceOf[T]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/** A special shuffle serializer for VertexBroadcastMessage[Double]. */
|
||||
class DoubleVertexBroadcastMsgSerializer extends Serializer {
|
||||
override def newInstance(): SerializerInstance = new ShuffleSerializerInstance {
|
||||
|
||||
override def serializeStream(s: OutputStream) = new ShuffleSerializationStream(s) {
|
||||
def writeObject[T](t: T) = {
|
||||
val msg = t.asInstanceOf[VertexBroadcastMsg[Double]]
|
||||
writeLong(msg.vid)
|
||||
writeDouble(msg.data)
|
||||
this
|
||||
}
|
||||
}
|
||||
|
||||
override def deserializeStream(s: InputStream) = new ShuffleDeserializationStream(s) {
|
||||
def readObject[T](): T = {
|
||||
new VertexBroadcastMsg[Double](0, readLong(), readDouble()).asInstanceOf[T]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/** A special shuffle serializer for AggregationMessage[Int]. */
|
||||
class IntAggMsgSerializer extends Serializer {
|
||||
override def newInstance(): SerializerInstance = new ShuffleSerializerInstance {
|
||||
|
||||
override def serializeStream(s: OutputStream) = new ShuffleSerializationStream(s) {
|
||||
def writeObject[T](t: T) = {
|
||||
val msg = t.asInstanceOf[AggregationMsg[Int]]
|
||||
writeLong(msg.vid)
|
||||
writeInt(msg.data)
|
||||
this
|
||||
}
|
||||
}
|
||||
|
||||
override def deserializeStream(s: InputStream) = new ShuffleDeserializationStream(s) {
|
||||
override def readObject[T](): T = {
|
||||
new AggregationMsg[Int](readLong(), readInt()).asInstanceOf[T]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/** A special shuffle serializer for AggregationMessage[Double]. */
|
||||
class DoubleAggMsgSerializer extends Serializer {
|
||||
override def newInstance(): SerializerInstance = new ShuffleSerializerInstance {
|
||||
|
||||
override def serializeStream(s: OutputStream) = new ShuffleSerializationStream(s) {
|
||||
def writeObject[T](t: T) = {
|
||||
val msg = t.asInstanceOf[AggregationMsg[Double]]
|
||||
writeLong(msg.vid)
|
||||
writeDouble(msg.data)
|
||||
this
|
||||
}
|
||||
}
|
||||
|
||||
override def deserializeStream(s: InputStream) = new ShuffleDeserializationStream(s) {
|
||||
def readObject[T](): T = {
|
||||
new AggregationMsg[Double](readLong(), readDouble()).asInstanceOf[T]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
// Helper classes to shorten the implementation of those special serializers.
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
sealed abstract class ShuffleSerializationStream(s: OutputStream) extends SerializationStream {
|
||||
// The implementation should override this one.
|
||||
def writeObject[T](t: T): SerializationStream
|
||||
|
||||
def writeInt(v: Int) {
|
||||
s.write(v >> 24)
|
||||
s.write(v >> 16)
|
||||
s.write(v >> 8)
|
||||
s.write(v)
|
||||
}
|
||||
|
||||
def writeLong(v: Long) {
|
||||
s.write((v >>> 56).toInt)
|
||||
s.write((v >>> 48).toInt)
|
||||
s.write((v >>> 40).toInt)
|
||||
s.write((v >>> 32).toInt)
|
||||
s.write((v >>> 24).toInt)
|
||||
s.write((v >>> 16).toInt)
|
||||
s.write((v >>> 8).toInt)
|
||||
s.write(v.toInt)
|
||||
}
|
||||
|
||||
def writeDouble(v: Double) {
|
||||
writeLong(java.lang.Double.doubleToLongBits(v))
|
||||
}
|
||||
|
||||
override def flush(): Unit = s.flush()
|
||||
|
||||
override def close(): Unit = s.close()
|
||||
}
|
||||
|
||||
|
||||
sealed abstract class ShuffleDeserializationStream(s: InputStream) extends DeserializationStream {
|
||||
// The implementation should override this one.
|
||||
def readObject[T](): T
|
||||
|
||||
def readInt(): Int = {
|
||||
(s.read() & 0xFF) << 24 | (s.read() & 0xFF) << 16 | (s.read() & 0xFF) << 8 | (s.read() & 0xFF)
|
||||
}
|
||||
|
||||
def readLong(): Long = {
|
||||
(s.read().toLong << 56) |
|
||||
(s.read() & 0xFF).toLong << 48 |
|
||||
(s.read() & 0xFF).toLong << 40 |
|
||||
(s.read() & 0xFF).toLong << 32 |
|
||||
(s.read() & 0xFF).toLong << 24 |
|
||||
(s.read() & 0xFF) << 16 |
|
||||
(s.read() & 0xFF) << 8 |
|
||||
(s.read() & 0xFF)
|
||||
}
|
||||
|
||||
def readDouble(): Double = java.lang.Double.longBitsToDouble(readLong())
|
||||
|
||||
override def close(): Unit = s.close()
|
||||
}
|
||||
|
||||
|
||||
sealed trait ShuffleSerializerInstance extends SerializerInstance {
|
||||
|
||||
override def serialize[T](t: T): ByteBuffer = throw new UnsupportedOperationException
|
||||
|
||||
override def deserialize[T](bytes: ByteBuffer): T = throw new UnsupportedOperationException
|
||||
|
||||
override def deserialize[T](bytes: ByteBuffer, loader: ClassLoader): T =
|
||||
throw new UnsupportedOperationException
|
||||
|
||||
// The implementation should override the following two.
|
||||
override def serializeStream(s: OutputStream): SerializationStream
|
||||
override def deserializeStream(s: InputStream): DeserializationStream
|
||||
}
|
||||
124
graphx-shell
Executable file
124
graphx-shell
Executable file
|
|
@ -0,0 +1,124 @@
|
|||
#!/usr/bin/env bash
|
||||
|
||||
#
|
||||
# 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.
|
||||
#
|
||||
|
||||
#
|
||||
# Shell script for starting the Spark Shell REPL
|
||||
# Note that it will set MASTER to spark://${SPARK_MASTER_IP}:${SPARK_MASTER_PORT}
|
||||
# if those two env vars are set in spark-env.sh but MASTER is not.
|
||||
# Options:
|
||||
# -c <cores> Set the number of cores for REPL to use
|
||||
#
|
||||
|
||||
# Enter posix mode for bash
|
||||
set -o posix
|
||||
|
||||
|
||||
# Update the the banner logo
|
||||
export SPARK_BANNER_TEXT="Welcome to
|
||||
______ __ _ __
|
||||
/ ____/________ _____ / /_ | |/ /
|
||||
/ / __/ ___/ __ \`/ __ \/ __ \| /
|
||||
/ /_/ / / / /_/ / /_/ / / / / |
|
||||
\____/_/ \__,_/ .___/_/ /_/_/|_|
|
||||
/_/ Alpha Release
|
||||
|
||||
Powered by:
|
||||
____ __
|
||||
/ __/__ ___ _____/ /__
|
||||
_\ \/ _ \/ _ \`/ __/ '_/
|
||||
/___/ .__/\_,_/_/ /_/\_\
|
||||
/_/ version 0.9.0
|
||||
|
||||
Example:
|
||||
|
||||
scala> val graph = GraphLoader.textFile(sc, \"hdfs://links\")
|
||||
scala> graph.numVertices
|
||||
scala> graph.numEdges
|
||||
scala> val pageRankGraph = Analytics.pagerank(graph, 10) // 10 iterations
|
||||
scala> val maxPr = pageRankGraph.vertices.map{ case (vid, pr) => pr }.max
|
||||
scala> println(maxPr)
|
||||
|
||||
"
|
||||
|
||||
export SPARK_SHELL_INIT_BLOCK="import org.apache.spark.graph._;"
|
||||
|
||||
# Set the serializer to use Kryo for graphx objects
|
||||
SPARK_JAVA_OPTS+=" -Dspark.serializer=org.apache.spark.serializer.KryoSerializer "
|
||||
SPARK_JAVA_OPTS+="-Dspark.kryo.registrator=org.apache.spark.graph.GraphKryoRegistrator "
|
||||
SPARK_JAVA_OPTS+="-Dspark.kryoserializer.buffer.mb=10 "
|
||||
|
||||
|
||||
|
||||
FWDIR="`dirname $0`"
|
||||
|
||||
for o in "$@"; do
|
||||
if [ "$1" = "-c" -o "$1" = "--cores" ]; then
|
||||
shift
|
||||
if [ -n "$1" ]; then
|
||||
OPTIONS="-Dspark.cores.max=$1"
|
||||
shift
|
||||
fi
|
||||
fi
|
||||
done
|
||||
|
||||
# Set MASTER from spark-env if possible
|
||||
if [ -z "$MASTER" ]; then
|
||||
if [ -e "$FWDIR/conf/spark-env.sh" ]; then
|
||||
. "$FWDIR/conf/spark-env.sh"
|
||||
fi
|
||||
if [[ "x" != "x$SPARK_MASTER_IP" && "y" != "y$SPARK_MASTER_PORT" ]]; then
|
||||
MASTER="spark://${SPARK_MASTER_IP}:${SPARK_MASTER_PORT}"
|
||||
export MASTER
|
||||
fi
|
||||
fi
|
||||
|
||||
# Copy restore-TTY-on-exit functions from Scala script so spark-shell exits properly even in
|
||||
# binary distribution of Spark where Scala is not installed
|
||||
exit_status=127
|
||||
saved_stty=""
|
||||
|
||||
# restore stty settings (echo in particular)
|
||||
function restoreSttySettings() {
|
||||
stty $saved_stty
|
||||
saved_stty=""
|
||||
}
|
||||
|
||||
function onExit() {
|
||||
if [[ "$saved_stty" != "" ]]; then
|
||||
restoreSttySettings
|
||||
fi
|
||||
exit $exit_status
|
||||
}
|
||||
|
||||
# to reenable echo if we are interrupted before completing.
|
||||
trap onExit INT
|
||||
|
||||
# save terminal settings
|
||||
saved_stty=$(stty -g 2>/dev/null)
|
||||
# clear on error so we don't later try to restore them
|
||||
if [[ ! $? ]]; then
|
||||
saved_stty=""
|
||||
fi
|
||||
|
||||
$FWDIR/spark-class $OPTIONS org.apache.spark.repl.Main "$@"
|
||||
|
||||
# record the exit status lest it be overwritten:
|
||||
# then reenable echo and propagate the code.
|
||||
exit_status=$?
|
||||
onExit
|
||||
|
|
@ -196,13 +196,17 @@ class SparkILoop(in0: Option[BufferedReader], val out: PrintWriter, val master:
|
|||
|
||||
/** Print a welcome message */
|
||||
def printWelcome() {
|
||||
echo("""Welcome to
|
||||
val prop = System.getenv("SPARK_BANNER_TEXT")
|
||||
val bannerText =
|
||||
if (prop != null) prop else
|
||||
"""Welcome to
|
||||
____ __
|
||||
/ __/__ ___ _____/ /__
|
||||
_\ \/ _ \/ _ `/ __/ '_/
|
||||
/___/ .__/\_,_/_/ /_/\_\ version 0.9.0-SNAPSHOT
|
||||
/_/
|
||||
""")
|
||||
"""
|
||||
echo(bannerText)
|
||||
import Properties._
|
||||
val welcomeMsg = "Using Scala %s (%s, Java %s)".format(
|
||||
versionString, javaVmName, javaVersion)
|
||||
|
|
@ -837,6 +841,10 @@ class SparkILoop(in0: Option[BufferedReader], val out: PrintWriter, val master:
|
|||
org.apache.spark.repl.Main.interp.out.flush();
|
||||
""")
|
||||
command("import org.apache.spark.SparkContext._")
|
||||
val prop = System.getenv("SPARK_SHELL_INIT_BLOCK")
|
||||
if (prop != null) {
|
||||
command(prop)
|
||||
}
|
||||
}
|
||||
echo("Type in expressions to have them evaluated.")
|
||||
echo("Type :help for more information.")
|
||||
|
|
|
|||
Loading…
Reference in a new issue