Split Time to Time (absolute instant of time) and Duration (duration of time).

streaming/src/main/scala/spark/streaming/Checkpoint.scala

@@ -17,7 +17,7 @@ class Checkpoint(@transient ssc: StreamingContext, val checkpointTime: Time)
   val jars = ssc.sc.jars
   val graph = ssc.graph
   val checkpointDir = ssc.checkpointDir
-  val checkpointInterval = ssc.checkpointInterval
+  val checkpointInterval: Duration = ssc.checkpointInterval
 
   def validate() {
     assert(master != null, "Checkpoint.master is null")

streaming/src/main/scala/spark/streaming/DStream.scala

@@ -2,7 +2,7 @@ package spark.streaming
 
 import spark.streaming.dstream._
 import StreamingContext._
-import Time._
+//import Time._
 
 import spark.{RDD, Logging}
 import spark.storage.StorageLevel
@@ -47,7 +47,7 @@ abstract class DStream[T: ClassManifest] (
   // =======================================================================
 
   /** Time interval after which the DStream generates a RDD */
-  def slideTime: Time 
+  def slideTime: Duration
 
   /** List of parent DStreams on which this DStream depends on */
   def dependencies: List[DStream[_]]
@@ -67,14 +67,14 @@ abstract class DStream[T: ClassManifest] (
   protected[streaming] var zeroTime: Time = null
 
   // Duration for which the DStream will remember each RDD created
-  protected[streaming] var rememberDuration: Time = null
+  protected[streaming] var rememberDuration: Duration = null
 
   // Storage level of the RDDs in the stream
   protected[streaming] var storageLevel: StorageLevel = StorageLevel.NONE
 
   // Checkpoint details
   protected[streaming] val mustCheckpoint = false
-  protected[streaming] var checkpointInterval: Time = null
+  protected[streaming] var checkpointInterval: Duration = null
   protected[streaming] var checkpointData = new DStreamCheckpointData(HashMap[Time, Any]())
 
   // Reference to whole DStream graph
@@ -108,7 +108,7 @@ abstract class DStream[T: ClassManifest] (
    * Enable periodic checkpointing of RDDs of this DStream
    * @param interval Time interval after which generated RDD will be checkpointed
    */
-  def checkpoint(interval: Time): DStream[T] = {
+  def checkpoint(interval: Duration): DStream[T] = {
     if (isInitialized) {
       throw new UnsupportedOperationException(
         "Cannot change checkpoint interval of an DStream after streaming context has started")
@@ -224,7 +224,7 @@ abstract class DStream[T: ClassManifest] (
     dependencies.foreach(_.setGraph(graph))
   }
 
-  protected[streaming] def remember(duration: Time) {
+  protected[streaming] def remember(duration: Duration) {
     if (duration != null && duration > rememberDuration) {
       rememberDuration = duration
       logInfo("Duration for remembering RDDs set to " + rememberDuration + " for " + this)
@@ -531,7 +531,7 @@ abstract class DStream[T: ClassManifest] (
    * @param windowTime width of the window; must be a multiple of this DStream's interval.
    * @return
    */
-  def window(windowTime: Time): DStream[T] = window(windowTime, this.slideTime)
+  def window(windowTime: Duration): DStream[T] = window(windowTime, this.slideTime)
 
   /**
    * Return a new DStream which is computed based on windowed batches of this DStream.
@@ -541,7 +541,7 @@ abstract class DStream[T: ClassManifest] (
    *                   the new DStream will generate RDDs); must be a multiple of this
    *                   DStream's interval
    */
-  def window(windowTime: Time, slideTime: Time): DStream[T] = {
+  def window(windowTime: Duration, slideTime: Duration): DStream[T] = {
     new WindowedDStream(this, windowTime, slideTime)
   }
 
@@ -550,22 +550,22 @@ abstract class DStream[T: ClassManifest] (
    * This is equivalent to window(batchTime, batchTime).
    * @param batchTime tumbling window duration; must be a multiple of this DStream's interval
    */
-  def tumble(batchTime: Time): DStream[T] = window(batchTime, batchTime)
+  def tumble(batchTime: Duration): DStream[T] = window(batchTime, batchTime)
 
   /**
    * Returns a new DStream in which each RDD has a single element generated by reducing all
    * elements in a window over this DStream. windowTime and slideTime are as defined in the
    * window() operation. This is equivalent to window(windowTime, slideTime).reduce(reduceFunc)
    */
-  def reduceByWindow(reduceFunc: (T, T) => T, windowTime: Time, slideTime: Time): DStream[T] = {
+  def reduceByWindow(reduceFunc: (T, T) => T, windowTime: Duration, slideTime: Duration): DStream[T] = {
     this.window(windowTime, slideTime).reduce(reduceFunc)
   }
 
   def reduceByWindow(
       reduceFunc: (T, T) => T,
       invReduceFunc: (T, T) => T,
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time
+      slideTime: Duration
     ): DStream[T] = {
       this.map(x => (1, x))
           .reduceByKeyAndWindow(reduceFunc, invReduceFunc, windowTime, slideTime, 1)
@@ -577,7 +577,7 @@ abstract class DStream[T: ClassManifest] (
    * of elements in a window over this DStream. windowTime and slideTime are as defined in the
    * window() operation. This is equivalent to window(windowTime, slideTime).count()
    */
-  def countByWindow(windowTime: Time, slideTime: Time): DStream[Int] = {
+  def countByWindow(windowTime: Duration, slideTime: Duration): DStream[Int] = {
     this.map(_ => 1).reduceByWindow(_ + _, _ - _, windowTime, slideTime)
   }
 

streaming/src/main/scala/spark/streaming/DStreamGraph.scala

@@ -12,8 +12,8 @@ final private[streaming] class DStreamGraph extends Serializable with Logging {
   private val outputStreams = new ArrayBuffer[DStream[_]]()
 
   private[streaming] var zeroTime: Time = null
-  private[streaming] var batchDuration: Time = null
+  private[streaming] var batchDuration: Duration = null
-  private[streaming] var rememberDuration: Time = null
+  private[streaming] var rememberDuration: Duration = null
   private[streaming] var checkpointInProgress = false
 
   private[streaming] def start(time: Time) {
@@ -41,7 +41,7 @@ final private[streaming] class DStreamGraph extends Serializable with Logging {
     }
   }
 
-  private[streaming] def setBatchDuration(duration: Time) {
+  private[streaming] def setBatchDuration(duration: Duration) {
     this.synchronized {
       if (batchDuration != null) {
         throw new Exception("Batch duration already set as " + batchDuration +
@@ -51,7 +51,7 @@ final private[streaming] class DStreamGraph extends Serializable with Logging {
     batchDuration = duration
   }
 
-  private[streaming] def remember(duration: Time) {
+  private[streaming] def remember(duration: Duration) {
     this.synchronized {
       if (rememberDuration != null) {
         throw new Exception("Batch duration already set as " + batchDuration +

streaming/src/main/scala/spark/streaming/Duration.scala

@@ -0,0 +1,62 @@
+package spark.streaming
+
+class Duration (private val millis: Long) {
+
+  def < (that: Duration): Boolean = (this.millis < that.millis)
+
+  def <= (that: Duration): Boolean = (this.millis <= that.millis)
+
+  def > (that: Duration): Boolean = (this.millis > that.millis)
+
+  def >= (that: Duration): Boolean = (this.millis >= that.millis)
+
+  def + (that: Duration): Duration = new Duration(millis + that.millis)
+
+  def - (that: Duration): Duration = new Duration(millis - that.millis)
+
+  def * (times: Int): Duration = new Duration(millis * times)
+
+  def / (that: Duration): Long = millis / that.millis
+
+  def isMultipleOf(that: Duration): Boolean =
+    (this.millis % that.millis == 0)
+
+  def min(that: Duration): Duration = if (this < that) this else that
+
+  def max(that: Duration): Duration = if (this > that) this else that
+
+  def isZero: Boolean = (this.millis == 0)
+
+  override def toString: String = (millis.toString + " ms")
+
+  def toFormattedString: String = millis.toString
+
+  def milliseconds: Long = millis
+}
+
+
+/**
+ * Helper object that creates instance of [[spark.streaming.Duration]] representing
+ * a given number of milliseconds.
+ */
+object Milliseconds {
+  def apply(milliseconds: Long) = new Duration(milliseconds)
+}
+
+/**
+ * Helper object that creates instance of [[spark.streaming.Duration]] representing
+ * a given number of seconds.
+ */
+object Seconds {
+  def apply(seconds: Long) = new Duration(seconds * 1000)
+}
+
+/**
+ * Helper object that creates instance of [[spark.streaming.Duration]] representing
+ * a given number of minutes.
+ */
+object Minutes {
+  def apply(minutes: Long) = new Duration(minutes * 60000)
+}
+
+

streaming/src/main/scala/spark/streaming/Interval.scala

@@ -1,16 +1,16 @@
 package spark.streaming
 
 private[streaming]
-case class Interval(beginTime: Time, endTime: Time) {
+class Interval(val beginTime: Time, val endTime: Time) {
-  def this(beginMs: Long, endMs: Long) = this(Time(beginMs), new Time(endMs))
+  def this(beginMs: Long, endMs: Long) = this(new Time(beginMs), new Time(endMs))
   
-  def duration(): Time = endTime - beginTime
+  def duration(): Duration = endTime - beginTime
 
-  def + (time: Time): Interval = {
+  def + (time: Duration): Interval = {
     new Interval(beginTime + time, endTime + time) 
   }
 
-  def - (time: Time): Interval = {
+  def - (time: Duration): Interval = {
     new Interval(beginTime - time, endTime - time)
   }
 
@@ -27,24 +27,14 @@ case class Interval(beginTime: Time, endTime: Time) {
   
   def >= (that: Interval) = !(this < that)
 
-  def next(): Interval = {
+  override def toString = "[" + beginTime + ", " + endTime + "]"
-    this + (endTime - beginTime)
-  }
-
-  def isZero = (beginTime.isZero && endTime.isZero)
-
-  def toFormattedString = beginTime.toFormattedString + "-" + endTime.toFormattedString
-
-  override def toString = "[" + beginTime + ", " + endTime + "]" 
 }
 
 object Interval {
-  def zero() = new Interval (Time.zero, Time.zero)
+  def currentInterval(duration: Duration): Interval  = {
-
+    val time = new Time(System.currentTimeMillis)
-  def currentInterval(intervalDuration: Time): Interval  = {
+    val intervalBegin = time.floor(duration)
-    val time = Time(System.currentTimeMillis)
+    new Interval(intervalBegin, intervalBegin + duration)
-    val intervalBegin = time.floor(intervalDuration) 
-    Interval(intervalBegin, intervalBegin + intervalDuration) 
   }
 }
 

streaming/src/main/scala/spark/streaming/PairDStreamFunctions.scala

@@ -69,21 +69,21 @@ extends Serializable {
     self.map(x => (x._1, 1L)).reduceByKey((x: Long, y: Long) => x + y, numPartitions)
   }
 
-  def groupByKeyAndWindow(windowTime: Time, slideTime: Time): DStream[(K, Seq[V])] = {
+  def groupByKeyAndWindow(windowTime: Duration, slideTime: Duration): DStream[(K, Seq[V])] = {
     groupByKeyAndWindow(windowTime, slideTime, defaultPartitioner())
   }
 
   def groupByKeyAndWindow(
-      windowTime: Time, 
+      windowTime: Duration,
-      slideTime: Time, 
+      slideTime: Duration,
       numPartitions: Int
     ): DStream[(K, Seq[V])] = {
     groupByKeyAndWindow(windowTime, slideTime, defaultPartitioner(numPartitions))
   }
 
   def groupByKeyAndWindow(
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time,
+      slideTime: Duration,
       partitioner: Partitioner
     ): DStream[(K, Seq[V])] = {
     self.window(windowTime, slideTime).groupByKey(partitioner)
@@ -91,23 +91,23 @@ extends Serializable {
 
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V,
-      windowTime: Time
+      windowTime: Duration
     ): DStream[(K, V)] = {
     reduceByKeyAndWindow(reduceFunc, windowTime, self.slideTime, defaultPartitioner())
   }
 
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V, 
-      windowTime: Time, 
+      windowTime: Duration,
-      slideTime: Time
+      slideTime: Duration
     ): DStream[(K, V)] = {
     reduceByKeyAndWindow(reduceFunc, windowTime, slideTime, defaultPartitioner())
   }
 
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V, 
-      windowTime: Time, 
+      windowTime: Duration,
-      slideTime: Time, 
+      slideTime: Duration,
       numPartitions: Int
     ): DStream[(K, V)] = {
     reduceByKeyAndWindow(reduceFunc, windowTime, slideTime, defaultPartitioner(numPartitions))
@@ -115,8 +115,8 @@ extends Serializable {
 
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V,
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time,
+      slideTime: Duration,
       partitioner: Partitioner
     ): DStream[(K, V)] = {
     val cleanedReduceFunc = ssc.sc.clean(reduceFunc)
@@ -134,8 +134,8 @@ extends Serializable {
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V,
       invReduceFunc: (V, V) => V,
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time
+      slideTime: Duration
     ): DStream[(K, V)] = {
 
     reduceByKeyAndWindow(
@@ -145,8 +145,8 @@ extends Serializable {
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V,
       invReduceFunc: (V, V) => V,
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time,
+      slideTime: Duration,
       numPartitions: Int
     ): DStream[(K, V)] = {
 
@@ -157,8 +157,8 @@ extends Serializable {
   def reduceByKeyAndWindow(
       reduceFunc: (V, V) => V,
       invReduceFunc: (V, V) => V,
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time,
+      slideTime: Duration,
       partitioner: Partitioner
     ): DStream[(K, V)] = {
 
@@ -169,8 +169,8 @@ extends Serializable {
   }
 
   def countByKeyAndWindow(
-      windowTime: Time,
+      windowTime: Duration,
-      slideTime: Time,
+      slideTime: Duration,
       numPartitions: Int = self.ssc.sc.defaultParallelism
     ): DStream[(K, Long)] = {
 

streaming/src/main/scala/spark/streaming/Scheduler.scala

@@ -22,7 +22,8 @@ class Scheduler(ssc: StreamingContext) extends Logging {
 
   val clockClass = System.getProperty("spark.streaming.clock", "spark.streaming.util.SystemClock")
   val clock = Class.forName(clockClass).newInstance().asInstanceOf[Clock]
-  val timer = new RecurringTimer(clock, ssc.graph.batchDuration.milliseconds, generateRDDs(_))
+  val timer = new RecurringTimer(clock, ssc.graph.batchDuration.milliseconds,
+    longTime => generateRDDs(new Time(longTime)))
 
   def start() {
     // If context was started from checkpoint, then restart timer such that
@@ -41,7 +42,7 @@ class Scheduler(ssc: StreamingContext) extends Logging {
       timer.restart(graph.zeroTime.milliseconds)
       logInfo("Scheduler's timer restarted")
     } else {
-      val firstTime = Time(timer.start())
+      val firstTime = new Time(timer.start())
       graph.start(firstTime - ssc.graph.batchDuration)
       logInfo("Scheduler's timer started")
     }

streaming/src/main/scala/spark/streaming/StreamingContext.scala

@@ -26,7 +26,7 @@ import java.util.UUID
 class StreamingContext private (
     sc_ : SparkContext,
     cp_ : Checkpoint,
-    batchDur_ : Time
+    batchDur_ : Duration
   ) extends Logging {
 
   /**
@@ -34,7 +34,7 @@ class StreamingContext private (
    * @param sparkContext Existing SparkContext
    * @param batchDuration The time interval at which streaming data will be divided into batches
    */
-  def this(sparkContext: SparkContext, batchDuration: Time) = this(sparkContext, null, batchDuration)
+  def this(sparkContext: SparkContext, batchDuration: Duration) = this(sparkContext, null, batchDuration)
 
   /**
    * Creates a StreamingContext by providing the details necessary for creating a new SparkContext.
@@ -42,7 +42,7 @@ class StreamingContext private (
    * @param frameworkName A name for your job, to display on the cluster web UI
    * @param batchDuration The time interval at which streaming data will be divided into batches
    */
-  def this(master: String, frameworkName: String, batchDuration: Time) =
+  def this(master: String, frameworkName: String, batchDuration: Duration) =
     this(StreamingContext.createNewSparkContext(master, frameworkName), null, batchDuration)
 
   /**
@@ -96,7 +96,7 @@ class StreamingContext private (
     }
   }
 
-  protected[streaming] var checkpointInterval: Time = if (isCheckpointPresent) cp_.checkpointInterval else null
+  protected[streaming] var checkpointInterval: Duration = if (isCheckpointPresent) cp_.checkpointInterval else null
   protected[streaming] var receiverJobThread: Thread = null
   protected[streaming] var scheduler: Scheduler = null
 
@@ -107,7 +107,7 @@ class StreamingContext private (
    * if the developer wishes to query old data outside the DStream computation).
    * @param duration Minimum duration that each DStream should remember its RDDs
    */
-  def remember(duration: Time) {
+  def remember(duration: Duration) {
     graph.remember(duration)
   }
 
@@ -117,7 +117,7 @@ class StreamingContext private (
    * @param directory HDFS-compatible directory where the checkpoint data will be reliably stored
    * @param interval checkpoint interval
    */
-  def checkpoint(directory: String, interval: Time = null) {
+  def checkpoint(directory: String, interval: Duration = null) {
     if (directory != null) {
       sc.setCheckpointDir(StreamingContext.getSparkCheckpointDir(directory))
       checkpointDir = directory

streaming/src/main/scala/spark/streaming/Time.scala

@@ -7,7 +7,7 @@ package spark.streaming
  * @param millis Time in UTC.
  */
 
-case class Time(private val millis: Long) {
+class Time(private val millis: Long) {
   
   def < (that: Time): Boolean = (this.millis < that.millis)
 
@@ -17,63 +17,32 @@ case class Time(private val millis: Long) {
   
   def >= (that: Time): Boolean = (this.millis >= that.millis)
 
-  def + (that: Time): Time = Time(millis + that.millis)
+  def + (that: Duration): Time = new Time(millis + that.milliseconds)
-  
-  def - (that: Time): Time = Time(millis - that.millis)
-  
-  def * (times: Int): Time = Time(millis * times)
 
-  def / (that: Time): Long = millis / that.millis
+  def - (that: Time): Duration = new Duration(millis - that.millis)
 
-  def floor(that: Time): Time = {
+  def - (that: Duration): Time = new Time(millis - that.milliseconds)
-    val t = that.millis
+
+  def floor(that: Duration): Time = {
+    val t = that.milliseconds
     val m = math.floor(this.millis / t).toLong 
-    Time(m * t)
+    new Time(m * t)
   }
 
-  def isMultipleOf(that: Time): Boolean = 
+  def isMultipleOf(that: Duration): Boolean =
-    (this.millis % that.millis == 0)
+    (this.millis % that.milliseconds == 0)
 
   def min(that: Time): Time = if (this < that) this else that
 
   def max(that: Time): Time = if (this > that) this else that
 
-  def isZero: Boolean = (this.millis == 0)
-
   override def toString: String = (millis.toString + " ms")
 
-  def toFormattedString: String = millis.toString
-  
   def milliseconds: Long = millis
 }
 
-private[streaming] object Time {
+/*private[streaming] object Time {
-  val zero = Time(0)
-
   implicit def toTime(long: Long) = Time(long)
 }
-
+*/
-/**
- * Helper object that creates instance of [[spark.streaming.Time]] representing
- * a given number of milliseconds.
- */
-object Milliseconds {
-  def apply(milliseconds: Long) = Time(milliseconds)
-}
-
-/**
- * Helper object that creates instance of [[spark.streaming.Time]] representing
- * a given number of seconds.
- */
-object Seconds {
-  def apply(seconds: Long) = Time(seconds * 1000)
-}
-
-/**
- * Helper object that creates instance of [[spark.streaming.Time]] representing
- * a given number of minutes.
- */
-object Minutes {
-  def apply(minutes: Long) = Time(minutes * 60000)
-}
 

streaming/src/main/scala/spark/streaming/dstream/CoGroupedDStream.scala

@@ -2,7 +2,7 @@ package spark.streaming.dstream
 
 import spark.{RDD, Partitioner}
 import spark.rdd.CoGroupedRDD
-import spark.streaming.{Time, DStream}
+import spark.streaming.{Time, DStream, Duration}
 
 private[streaming]
 class CoGroupedDStream[K : ClassManifest](
@@ -24,7 +24,7 @@ class CoGroupedDStream[K : ClassManifest](
 
   override def dependencies = parents.toList
 
-  override def slideTime = parents.head.slideTime
+  override def slideTime: Duration = parents.head.slideTime
 
   override def compute(validTime: Time): Option[RDD[(K, Seq[Seq[_]])]] = {
     val part = partitioner

streaming/src/main/scala/spark/streaming/dstream/FilteredDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 
 private[streaming]
@@ -11,7 +11,7 @@ class FilteredDStream[T: ClassManifest](
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[T]] = {
     parent.getOrCompute(validTime).map(_.filter(filterFunc))

streaming/src/main/scala/spark/streaming/dstream/FlatMapValuedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 import spark.SparkContext._
 
@@ -12,7 +12,7 @@ class FlatMapValuedDStream[K: ClassManifest, V: ClassManifest, U: ClassManifest]
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[(K, U)]] = {
     parent.getOrCompute(validTime).map(_.flatMapValues[U](flatMapValueFunc))

streaming/src/main/scala/spark/streaming/dstream/FlatMappedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 
 private[streaming]
@@ -11,7 +11,7 @@ class FlatMappedDStream[T: ClassManifest, U: ClassManifest](
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[U]] = {
     parent.getOrCompute(validTime).map(_.flatMap(flatMapFunc))

streaming/src/main/scala/spark/streaming/dstream/ForEachDStream.scala

@@ -1,7 +1,7 @@
 package spark.streaming.dstream
 
 import spark.RDD
-import spark.streaming.{DStream, Job, Time}
+import spark.streaming.{Duration, DStream, Job, Time}
 
 private[streaming]
 class ForEachDStream[T: ClassManifest] (
@@ -11,7 +11,7 @@ class ForEachDStream[T: ClassManifest] (
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[Unit]] = None
 

streaming/src/main/scala/spark/streaming/dstream/GlommedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 
 private[streaming]
@@ -9,7 +9,7 @@ class GlommedDStream[T: ClassManifest](parent: DStream[T])
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[Array[T]]] = {
     parent.getOrCompute(validTime).map(_.glom())

streaming/src/main/scala/spark/streaming/dstream/InputDStream.scala

@@ -1,13 +1,13 @@
 package spark.streaming.dstream
 
-import spark.streaming.{StreamingContext, DStream}
+import spark.streaming.{Duration, StreamingContext, DStream}
 
 abstract class InputDStream[T: ClassManifest] (@transient ssc_ : StreamingContext)
   extends DStream[T](ssc_) {
 
   override def dependencies = List()
 
-  override def slideTime = {
+  override def slideTime: Duration = {
     if (ssc == null) throw new Exception("ssc is null")
     if (ssc.graph.batchDuration == null) throw new Exception("batchDuration is null")
     ssc.graph.batchDuration

streaming/src/main/scala/spark/streaming/dstream/MapPartitionedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 
 private[streaming]
@@ -12,7 +12,7 @@ class MapPartitionedDStream[T: ClassManifest, U: ClassManifest](
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[U]] = {
     parent.getOrCompute(validTime).map(_.mapPartitions[U](mapPartFunc, preservePartitioning))

streaming/src/main/scala/spark/streaming/dstream/MapValuedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 import spark.SparkContext._
 
@@ -12,7 +12,7 @@ class MapValuedDStream[K: ClassManifest, V: ClassManifest, U: ClassManifest](
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[(K, U)]] = {
     parent.getOrCompute(validTime).map(_.mapValues[U](mapValueFunc))

streaming/src/main/scala/spark/streaming/dstream/MappedDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 
 private[streaming]
@@ -11,7 +11,7 @@ class MappedDStream[T: ClassManifest, U: ClassManifest] (
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[U]] = {
     parent.getOrCompute(validTime).map(_.map[U](mapFunc))

streaming/src/main/scala/spark/streaming/dstream/ReducedWindowedDStream.scala

@@ -9,15 +9,15 @@ import spark.SparkContext._
 import spark.storage.StorageLevel
 
 import scala.collection.mutable.ArrayBuffer
-import spark.streaming.{Interval, Time, DStream}
+import spark.streaming.{Duration, Interval, Time, DStream}
 
 private[streaming]
 class ReducedWindowedDStream[K: ClassManifest, V: ClassManifest](
     parent: DStream[(K, V)],
     reduceFunc: (V, V) => V,
     invReduceFunc: (V, V) => V, 
-    _windowTime: Time,
+    _windowTime: Duration,
-    _slideTime: Time,
+    _slideTime: Duration,
     partitioner: Partitioner
   ) extends DStream[(K,V)](parent.ssc) {
 
@@ -39,15 +39,15 @@ class ReducedWindowedDStream[K: ClassManifest, V: ClassManifest](
   super.persist(StorageLevel.MEMORY_ONLY_SER)
   reducedStream.persist(StorageLevel.MEMORY_ONLY_SER)
 
-  def windowTime: Time =  _windowTime
+  def windowTime: Duration =  _windowTime
 
   override def dependencies = List(reducedStream)
 
-  override def slideTime: Time = _slideTime
+  override def slideTime: Duration = _slideTime
 
   override val mustCheckpoint = true
 
-  override def parentRememberDuration: Time = rememberDuration + windowTime
+  override def parentRememberDuration: Duration = rememberDuration + windowTime
 
   override def persist(storageLevel: StorageLevel): DStream[(K,V)] = {
     super.persist(storageLevel)
@@ -55,7 +55,7 @@ class ReducedWindowedDStream[K: ClassManifest, V: ClassManifest](
     this
   }
 
-  override def checkpoint(interval: Time): DStream[(K, V)] = {
+  override def checkpoint(interval: Duration): DStream[(K, V)] = {
     super.checkpoint(interval)
     //reducedStream.checkpoint(interval)
     this
@@ -66,7 +66,7 @@ class ReducedWindowedDStream[K: ClassManifest, V: ClassManifest](
     val invReduceF = invReduceFunc
 
     val currentTime = validTime
-    val currentWindow = Interval(currentTime - windowTime + parent.slideTime, currentTime)
+    val currentWindow = new Interval(currentTime - windowTime + parent.slideTime, currentTime)
     val previousWindow = currentWindow - slideTime
 
     logDebug("Window time = " + windowTime)

streaming/src/main/scala/spark/streaming/dstream/ShuffledDStream.scala

@@ -2,7 +2,7 @@ package spark.streaming.dstream
 
 import spark.{RDD, Partitioner}
 import spark.SparkContext._
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 
 private[streaming]
 class ShuffledDStream[K: ClassManifest, V: ClassManifest, C: ClassManifest](
@@ -15,7 +15,7 @@ class ShuffledDStream[K: ClassManifest, V: ClassManifest, C: ClassManifest](
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[(K,C)]] = {
     parent.getOrCompute(validTime) match {

streaming/src/main/scala/spark/streaming/dstream/StateDStream.scala

@@ -4,7 +4,7 @@ import spark.RDD
 import spark.Partitioner
 import spark.SparkContext._
 import spark.storage.StorageLevel
-import spark.streaming.{Time, DStream}
+import spark.streaming.{Duration, Time, DStream}
 
 private[streaming]
 class StateDStream[K: ClassManifest, V: ClassManifest, S <: AnyRef : ClassManifest](
@@ -18,7 +18,7 @@ class StateDStream[K: ClassManifest, V: ClassManifest, S <: AnyRef : ClassManife
 
   override def dependencies = List(parent)
 
-  override def slideTime = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override val mustCheckpoint = true
 

streaming/src/main/scala/spark/streaming/dstream/TransformedDStream.scala

@@ -1,7 +1,7 @@
 package spark.streaming.dstream
 
 import spark.RDD
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 
 private[streaming]
 class TransformedDStream[T: ClassManifest, U: ClassManifest] (
@@ -11,7 +11,7 @@ class TransformedDStream[T: ClassManifest, U: ClassManifest] (
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = parent.slideTime
+  override def slideTime: Duration = parent.slideTime
 
   override def compute(validTime: Time): Option[RDD[U]] = {
     parent.getOrCompute(validTime).map(transformFunc(_, validTime))

streaming/src/main/scala/spark/streaming/dstream/UnionDStream.scala

@@ -1,6 +1,6 @@
 package spark.streaming.dstream
 
-import spark.streaming.{DStream, Time}
+import spark.streaming.{Duration, DStream, Time}
 import spark.RDD
 import collection.mutable.ArrayBuffer
 import spark.rdd.UnionRDD
@@ -23,7 +23,7 @@ class UnionDStream[T: ClassManifest](parents: Array[DStream[T]])
 
   override def dependencies = parents.toList
 
-  override def slideTime: Time = parents.head.slideTime
+  override def slideTime: Duration = parents.head.slideTime
 
   override def compute(validTime: Time): Option[RDD[T]] = {
     val rdds = new ArrayBuffer[RDD[T]]()

streaming/src/main/scala/spark/streaming/dstream/WindowedDStream.scala

@@ -3,13 +3,13 @@ package spark.streaming.dstream
 import spark.RDD
 import spark.rdd.UnionRDD
 import spark.storage.StorageLevel
-import spark.streaming.{Interval, Time, DStream}
+import spark.streaming.{Duration, Interval, Time, DStream}
 
 private[streaming]
 class WindowedDStream[T: ClassManifest](
     parent: DStream[T],
-    _windowTime: Time,
+    _windowTime: Duration,
-    _slideTime: Time) 
+    _slideTime: Duration)
   extends DStream[T](parent.ssc) {
 
   if (!_windowTime.isMultipleOf(parent.slideTime))
@@ -22,16 +22,16 @@ class WindowedDStream[T: ClassManifest](
 
   parent.persist(StorageLevel.MEMORY_ONLY_SER)
 
-  def windowTime: Time =  _windowTime
+  def windowTime: Duration =  _windowTime
 
   override def dependencies = List(parent)
 
-  override def slideTime: Time = _slideTime
+  override def slideTime: Duration = _slideTime
 
-  override def parentRememberDuration: Time = rememberDuration + windowTime
+  override def parentRememberDuration: Duration = rememberDuration + windowTime
 
   override def compute(validTime: Time): Option[RDD[T]] = {
-    val currentWindow = Interval(validTime - windowTime + parent.slideTime, validTime)
+    val currentWindow = new Interval(validTime - windowTime + parent.slideTime, validTime)
     Some(new UnionRDD(ssc.sc, parent.slice(currentWindow)))
   }
 }