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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.rdd
import org.apache.spark.{TaskContext, Partition}
private[spark]
class FlatMappedValuesRDD[K, V, U](prev: RDD[_ <: Product2[K, V]], f: V => TraversableOnce[U])
extends RDD[(K, U)](prev) {
override def getPartitions = firstParent[Product2[K, V]].partitions
override val partitioner = firstParent[Product2[K, V]].partitioner
override def compute(split: Partition, context: TaskContext) = {
firstParent[Product2[K, V]].iterator(split, context).flatMap { case Product2(k, v) =>
f(v).map(x => (k, x))
}
}
}
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