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/*
* 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.
*/
package org.apache.spark.streaming.dstream
import org.apache.spark.{RDD, Partitioner}
import org.apache.spark.SparkContext._
import org.apache.spark.streaming.{Duration, DStream, Time}
private[streaming]
class ShuffledDStream[K: ClassManifest, V: ClassManifest, C: ClassManifest](
parent: DStream[(K,V)],
createCombiner: V => C,
mergeValue: (C, V) => C,
mergeCombiner: (C, C) => C,
partitioner: Partitioner
) extends DStream [(K,C)] (parent.ssc) {
override def dependencies = List(parent)
override def slideDuration: Duration = parent.slideDuration
override def compute(validTime: Time): Option[RDD[(K,C)]] = {
parent.getOrCompute(validTime) match {
case Some(rdd) =>
Some(rdd.combineByKey[C](createCombiner, mergeValue, mergeCombiner, partitioner))
case None => None
}
}
}
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