collection.mutable.ArrayBuffer Scala Examples

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's don't seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo =>
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

package com.kakao.shaded.jackson.module.scala.util

import collection.mutable.{ArrayBuffer, ListBuffer}
import collection.GenTraversable
import collection.generic.GenericCompanion
import scala.reflect.ClassTag

import scala.language.higherKinds


class CompanionSorter[CC[X] <: GenTraversable[X]] {
  type HKClassManifest[CC2[_]] = ClassTag[CC2[_]]

  private[this] val companions = new ArrayBuffer[(Class[_], GenericCompanion[CC])]()

  def add[T[X] <: CC[X] : HKClassManifest](companion: GenericCompanion[T]): CompanionSorter[CC] = {
    companions += implicitly[HKClassManifest[T]].runtimeClass -> companion
    this
  }

  def toList: List[(Class[_], GenericCompanion[CC])] = {
    val cs = companions.toArray
    val output = new ListBuffer[(Class[_], GenericCompanion[CC])]()

    val remaining = cs.map(_ => 1)
    val adjMatrix = Array.ofDim[Int](cs.length, cs.length)

    // Build the adjacency matrix. Only mark the in-edges.
    for (i <- 0 until cs.length; j <- 0 until cs.length) {
      val (ic, _) = cs(i)
      val (jc, _) = cs(j)

      if (i != j && ic.isAssignableFrom(jc)) {
        adjMatrix(i)(j) = 1
      }
    }

    // While we haven't removed every node, remove all nodes with 0 degree in-edges.
    while (output.length < cs.length) {
      val startLength = output.length

      for (i <- 0 until cs.length) {
        if (remaining(i) == 1 && dotProduct(adjMatrix(i), remaining) == 0) {
          output += companions(i)
          remaining(i) = 0
        }
      }

      // If we couldn't remove any nodes, it means we've found a cycle. Realistically this should never happen.
      if (output.length == startLength) {
        throw new IllegalStateException("Companions contain a cycle.")
      }
    }

    output.toList
  }

  private[this] def dotProduct(a: Array[Int], b: Array[Int]): Int = {
    if (a.length != b.length) throw new IllegalArgumentException()

    (0 until a.length).map(i => a(i) * b(i)).sum
  }
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's don't seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo =>
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

import collection.mutable.ArrayBuffer
import java.io.{ObjectInputStream, FileOutputStream, FileInputStream, ObjectOutputStream}

class Person(var name:String) extends Serializable{

  val friends = new ArrayBuffer[Person]()

  def addFriend(friend : Person){
    friends += friend
  }

  override def toString() = {
    var str = "My name is " + name + " and my friends name is "
    friends.foreach(str += _.name + ",")
    str
  }
}


object Test extends App{
  val p1 = new Person("Ivan")
  val p2 = new Person("F2")
  val p3 = new Person("F3")

  p1.addFriend(p2)
  p1.addFriend(p3)
  println(p1)

  val out = new ObjectOutputStream(new FileOutputStream("person.obj"))
  out.writeObject(p1)
  out.close()

  val in =  new ObjectInputStream(new FileInputStream("person.obj"))
  val p = in.readObject().asInstanceOf[Person]
  println(p)
} 

import collection.mutable.ArrayBuffer

class ASCIIArt(str:String){
  val arr:ArrayBuffer[ArrayBuffer[String]] = new ArrayBuffer[ArrayBuffer[String]]()

  if (str != null && !str.trim.eq("")){
    str.split("[\r\n]+").foreach{
      line =>
        val s = new ArrayBuffer[String]()
        s += line
        arr += s
    }
  }

  def this(){
    this("")
  }

  def +(other:ASCIIArt):ASCIIArt={
    val art = new ASCIIArt()
    val length = if (this.arr.length >= other.arr.length) this.arr.length else other.arr.length
    for(i <- 0 until length){
      val s = new ArrayBuffer[String]()
      val thisArr:ArrayBuffer[String] = if (i < this.arr.length) this.arr(i) else new ArrayBuffer[String]()
      val otherArr:ArrayBuffer[String] = if (i < other.arr.length) other.arr(i) else new ArrayBuffer[String]()
      thisArr.foreach(s += _)
      otherArr.foreach(s += _)
      art.arr += s
    }
    art
  }

  def *(other:ASCIIArt):ASCIIArt={
    val art = new ASCIIArt()
    this.arr.foreach(art.arr += _)
    other.arr.foreach(art.arr += _)
    art
  }

  override def toString()={
    var ss:String = ""
    arr.foreach{
      ss += _.mkString(" ") + "\n"
    }
    ss
  }
}

object Test extends App{
  val a = new ASCIIArt(""" /\_/\
                         |( ' ' )
                         |(  -  )
                         | | | |
                         |(__|__)
                         |""".stripMargin)
  val b = new ASCIIArt( """    -----
                          |  / Hello \
                          | <  Scala |
                          |  \ Coder /
                          |    -----
                          |""".stripMargin)
  println(a + b * b)
  println((a + b) * b)
  println(a * b)
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's dont seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo => {
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    }
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

// See LICENSE for license details.

package midas.passes.fame

import firrtl._
import Mappers._
import ir._
import annotations._
import collection.mutable.ArrayBuffer
import midas.targetutils.FirrtlMemModelAnnotation

class LabelSRAMModels extends Transform {
  def inputForm = HighForm
  def outputForm = HighForm

  val confwriter = new passes.memlib.ConfWriter("NONE")
  val memutil = new passes.memlib.ReplaceMemMacros(confwriter)

  def mem2Module(mem: DefMemory): Module = {
    val ports = passes.MemPortUtils.memType(mem).fields.map(f => Port(NoInfo, f.name, Input, f.tpe))
    val connects = ports.map(p => Connect(NoInfo, WSubField(WRef(mem.name), p.name), WRef(p.name)))
    Module(mem.info, mem.name, ports, Block(mem +: connects))
  }

  override def execute(state: CircuitState): CircuitState = {
    val circ = state.circuit
    val moduleNS = Namespace(circ)
    val memModelAnnotations = new ArrayBuffer[Annotation]
    val memModules = new ArrayBuffer[Module]
    val annotatedMems = state.annotations.collect({
      case FirrtlMemModelAnnotation(rt) => rt
    }).toSet

    println(s"[MIDAS 2.0] RAM Models To Extract: ${annotatedMems.size}")

    val transformedModules = circ.modules.map({
      case m: Module =>
        val mt = ModuleTarget(circ.main, m.name)
        def onStmt(stmt: Statement): Statement = stmt.map(onStmt) match {
          case mem: DefMemory if annotatedMems.contains(mt.ref(mem.name)) =>
            val wrapper = mem2Module(mem).copy(name = moduleNS.newName(mem.name))
            val wrapperTarget = ModuleTarget(circ.main, wrapper.name)
            memModules += wrapper
            memModelAnnotations += FAMEModelAnnotation(mt.instOf(mem.name, wrapper.name))
            memModelAnnotations ++= mem.readers.map(rp => ModelReadPort(wrapperTarget.ref(rp)))
            memModelAnnotations ++= mem.writers.map(rp => ModelWritePort(wrapperTarget.ref(rp)))
            memModelAnnotations ++= mem.readwriters.map(rp => ModelReadWritePort(wrapperTarget.ref(rp)))
            WDefInstance(mem.info, mem.name, wrapper.name, UnknownType)
          case s => s
        }
        m.copy(body = m.body.map(onStmt))
      case m => m
    })
    val transformedCircuit = circ.copy(modules = memModules ++ transformedModules)
    state.copy(circuit = transformedCircuit, annotations = state.annotations ++ memModelAnnotations)
  }
} 

// See LICENSE for license details.

package midas.passes.fame

import firrtl._
import Mappers._
import ir._
import annotations._
import collection.mutable.{ArrayBuffer, LinkedHashSet}

// Assumes: AQB form
// Run after ExtractModel
// Label all unbound top-level ports as wire channels
// Label *all* model-to-model connections as wire channels
// Label all children of the top model to be FAME1 transformed

class FAMEDefaults extends Transform {
  def inputForm = LowForm
  def outputForm = LowForm

  override def execute(state: CircuitState): CircuitState = {
    val analysis = new FAMEChannelAnalysis(state, FAME1Transform)
    val topModule = state.circuit.modules.find(_.name == state.circuit.main).get.asInstanceOf[Module]
    val globalSignals = state.annotations.collect({ case g: FAMEGlobalSignal => g.target.ref }).toSet
    val channelNames = state.annotations.collect({ case fca: FAMEChannelConnectionAnnotation => fca.globalName })
    val channelNS = Namespace(channelNames)
    def isGlobal(topPort: Port) = globalSignals.contains(topPort.name)
    def isBound(topPort: Port) = analysis.channelsByPort.contains(analysis.topTarget.ref(topPort.name))
    val defaultExtChannelAnnos = topModule.ports.filterNot(isGlobal).filterNot(isBound).flatMap({
      case Port(_, _, _, ClockType) => None // FIXME: Reject the clock in RC's debug interface
      case Port(_, name, Input, _)  => Some(FAMEChannelConnectionAnnotation(channelNS.newName(name), WireChannel, None, Some(Seq(analysis.topTarget.ref(name)))))
      case Port(_, name, Output, _) => Some(FAMEChannelConnectionAnnotation(channelNS.newName(name), WireChannel, Some(Seq(analysis.topTarget.ref(name))), None))
    })
    val channelModules = new LinkedHashSet[String] // TODO: find modules to absorb into channels, don't label as FAME models
    val defaultLoopbackAnnos = new ArrayBuffer[FAMEChannelConnectionAnnotation]
    val defaultModelAnnos = new ArrayBuffer[FAMETransformAnnotation]
    val topTarget = ModuleTarget(state.circuit.main, topModule.name)
    def onStmt(stmt: Statement): Statement = stmt.map(onStmt) match {
      case wi @ WDefInstance(_, iname, mname, _) if (!channelModules.contains(mname)) =>
        defaultModelAnnos += FAMETransformAnnotation(FAME1Transform, topTarget.copy(module = mname))
        wi
      case c @ Connect(_, WSubField(WRef(lhsiname, _, InstanceKind, _), lhspname, _, _), WSubField(WRef(rhsiname, _, InstanceKind, _), rhspname, _, _)) =>
        if (c.loc.tpe != ClockType && c.expr.tpe != ClockType) {
          defaultLoopbackAnnos += FAMEChannelConnectionAnnotation(
            channelNS.newName(s"${rhsiname}_${rhspname}__to__${lhsiname}_${lhspname}"),
            WireChannel,
            Some(Seq(topTarget.ref(rhsiname).field(rhspname))),
            Some(Seq(topTarget.ref(lhsiname).field(lhspname))))
        }
        c
      case s => s
    }
    topModule.body.map(onStmt)
    state.copy(annotations = state.annotations ++ defaultExtChannelAnnos ++ defaultLoopbackAnnos ++ defaultModelAnnos)
  }
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's don't seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo =>
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's dont seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo => {
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    }
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's don't seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo =>
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
} 

package org.apache.spark.scheduler

import collection.mutable.ArrayBuffer

import org.apache.spark.annotation.DeveloperApi

// information about a specific split instance : handles both split instances.
// So that we do not need to worry about the differences.
@DeveloperApi
class SplitInfo(
    val inputFormatClazz: Class[_],
    val hostLocation: String,
    val path: String,
    val length: Long,
    val underlyingSplit: Any) {
  override def toString(): String = {
    "SplitInfo " + super.toString + " .. inputFormatClazz " + inputFormatClazz +
      ", hostLocation : " + hostLocation + ", path : " + path +
      ", length : " + length + ", underlyingSplit " + underlyingSplit
  }

  override def hashCode(): Int = {
    var hashCode = inputFormatClazz.hashCode
    hashCode = hashCode * 31 + hostLocation.hashCode
    hashCode = hashCode * 31 + path.hashCode
    // ignore overflow ? It is hashcode anyway !
    hashCode = hashCode * 31 + (length & 0x7fffffff).toInt
    hashCode
  }

  // This is practically useless since most of the Split impl's dont seem to implement equals :-(
  // So unless there is identity equality between underlyingSplits, it will always fail even if it
  // is pointing to same block.
  override def equals(other: Any): Boolean = other match {
    case that: SplitInfo => {
      this.hostLocation == that.hostLocation &&
        this.inputFormatClazz == that.inputFormatClazz &&
        this.path == that.path &&
        this.length == that.length &&
        // other split specific checks (like start for FileSplit)
        this.underlyingSplit == that.underlyingSplit
    }
    case _ => false
  }
}

object SplitInfo {

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapredSplit: org.apache.hadoop.mapred.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapredSplit.getLength
    for (host <- mapredSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapredSplit)
    }
    retval
  }

  def toSplitInfo(inputFormatClazz: Class[_], path: String,
                  mapreduceSplit: org.apache.hadoop.mapreduce.InputSplit): Seq[SplitInfo] = {
    val retval = new ArrayBuffer[SplitInfo]()
    val length = mapreduceSplit.getLength
    for (host <- mapreduceSplit.getLocations) {
      retval += new SplitInfo(inputFormatClazz, host, path, length, mapreduceSplit)
    }
    retval
  }
}