def partitionBy(partitioner: Partitioner): RDD[(K, V)]
该函数根据partitioner函数生成新的ShuffleRDD，将原RDD重新分区。
scala> var rdd1 = sc.makeRDD(Array((1,"A"),(2,"B"),(3,"C"),(4,"D")),2)rdd1: org.apache.spark.rdd.RDD[(Int, String)] = ParallelCollectionRDD[23] at makeRDD at :21 scala> rdd1.partitions.sizeres20: Int = 2 //查看rdd1中每个分区的元素scala> rdd1.mapPartitionsWithIndex{ | (partIdx,iter) => { | var part_map = scala.collection.mutable.Map[String,List[(Int,String)]]() | while(iter.hasNext){ | var part_name = "part_" + partIdx; | var elem = iter.next() | if(part_map.contains(part_name)) { | var elems = part_map(part_name) | elems ::= elem | part_map(part_name) = elems | } else { | part_map(part_name) = List[(Int,String)]{elem} | } | } | part_map.iterator | | } | }.collectres22: Array[(String, List[(Int, String)])] = Array((part_0,List((2,B), (1,A))), (part_1,List((4,D), (3,C))))//(2,B),(1,A)在part_0中，(4,D),(3,C)在part_1中 //使用partitionBy重分区scala> var rdd2 = rdd1.partitionBy(new org.apache.spark.HashPartitioner(2))rdd2: org.apache.spark.rdd.RDD[(Int, String)] = ShuffledRDD[25] at partitionBy at :23 scala> rdd2.partitions.sizeres23: Int = 2 //查看rdd2中每个分区的元素scala> rdd2.mapPartitionsWithIndex{ | (partIdx,iter) => { | var part_map = scala.collection.mutable.Map[String,List[(Int,String)]]() | while(iter.hasNext){ | var part_name = "part_" + partIdx; | var elem = iter.next() | if(part_map.contains(part_name)) { | var elems = part_map(part_name) | elems ::= elem | part_map(part_name) = elems | } else { | part_map(part_name) = List[(Int,String)]{elem} | } | } | part_map.iterator | } | }.collectres24: Array[(String, List[(Int, String)])] = Array((part_0,List((4,D), (2,B))), (part_1,List((3,C), (1,A))))//(4,D),(2,B)在part_0中，(3,C),(1,A)在part_1中def mapValues[U](f: (V) => U): RDD[(K, U)]
同基本转换操作中的map，只不过mapValues是针对[K,V]中的V值进行map操作。
scala> var rdd1 = sc.makeRDD(Array((1,"A"),(2,"B"),(3,"C"),(4,"D")),2)rdd1: org.apache.spark.rdd.RDD[(Int, String)] = ParallelCollectionRDD[27] at makeRDD at :21 scala> rdd1.mapValues(x => x + "_").collectres26: Array[(Int, String)] = Array((1,A_), (2,B_), (3,C_), (4,D_))def flatMapValues[U](f: (V) => TraversableOnce[U]): RDD[(K, U)]
同基本转换操作中的flatMap，只不过flatMapValues是针对[K,V]中的V值进行flatMap操作。
scala> rdd1.flatMapValues(x => x + "_").collectres36: Array[(Int, Char)] = Array((1,A), (1,_), (2,B), (2,_), (3,C), (3,_), (4,D), (4,_))