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RDD基本转换操作(4)–union、intersection、subtract

union

def union(other: RDD[T]): RDD[T]

该函数比较简单，就是将两个RDD进行合并，不去重。 

     
  1.  scala> var rdd1 = sc.makeRDD(1 to 2,1)       
    2.       
  2.  rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[45] at makeRDD at :21       
    3.           
  3.  scala> rdd1.collect       
    4.       
  4.  res42: Array[Int] = Array(1, 2)       
    5.           
  5.  scala> var rdd2 = sc.makeRDD(2 to 3,1)       
    6.       
  6.  rdd2: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[46] at makeRDD at :21       
    7.           
  7.  scala> rdd2.collect       
    8.       
  8.  res43: Array[Int] = Array(2, 3)       
    9.           
  9.  scala> rdd1.union(rdd2).collect       
    10.       
  10.  res44: Array[Int] = Array(1, 2, 2, 3)       
    11.

intersection

def intersection(other: RDD[T]): RDD[T]

def intersection(other: RDD[T], numPartitions: Int): RDD[T]

def intersection(other: RDD[T], partitioner: Partitioner)(implicit ord: Ordering[T] = null): RDD[T]

该函数返回两个RDD的交集，并且去重。

参数numPartitions指定返回的RDD的分区数。

参数partitioner用于指定分区函数

     
  1.  scala> var rdd1 = sc.makeRDD(1 to 2,1)       
    2.       
  2.  rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[45] at makeRDD at :21       
    3.           
  3.  scala> rdd1.collect       
    4.       
  4.  res42: Array[Int] = Array(1, 2)       
    5.           
  5.  scala> var rdd2 = sc.makeRDD(2 to 3,1)       
    6.       
  6.  rdd2: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[46] at makeRDD at :21       
    7.           
  7.  scala> rdd2.collect       
    8.       
  8.  res43: Array[Int] = Array(2, 3)       
    9.           
  9.  scala> rdd1.intersection(rdd2).collect       
    10.       
  10.  res45: Array[Int] = Array(2)       
    11.           
  11.  scala> var rdd3 = rdd1.intersection(rdd2)       
    12.       
  12.  rdd3: org.apache.spark.rdd.RDD[Int] = MapPartitionsRDD[59] at intersection at :25       
    13.           
  13.  scala> rdd3.partitions.size       
    14.       
  14.  res46: Int = 1       
    15.           
  15.  scala> var rdd3 = rdd1.intersection(rdd2,2)       
    16.       
  16.  rdd3: org.apache.spark.rdd.RDD[Int] = MapPartitionsRDD[65] at intersection at :25       
    17.           
  17.  scala> rdd3.partitions.size       
    18.       
  18.  res47: Int = 2       
    19.

subtract

def subtract(other: RDD[T]): RDD[T]

def subtract(other: RDD[T], numPartitions: Int): RDD[T]

def subtract(other: RDD[T], partitioner: Partitioner)(implicit ord: Ordering[T] = null): RDD[T]

该函数类似于intersection，但返回在RDD中出现，并且不在otherRDD中出现的元素，不去重。

参数含义同intersection

     
  1.  scala> var rdd1 = sc.makeRDD(Seq(1,2,2,3))       
    2.       
  2.  rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[66] at makeRDD at :21       
    3.           
  3.  scala> rdd1.collect       
    4.       
  4.  res48: Array[Int] = Array(1, 2, 2, 3)       
    5.           
  5.  scala> var rdd2 = sc.makeRDD(3 to 4)       
    6.       
  6.  rdd2: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[67] at makeRDD at :21       
    7.           
  7.  scala> rdd2.collect       
    8.       
  8.  res49: Array[Int] = Array(3, 4)       
    9.           
  9.  scala> rdd1.subtract(rdd2).collect       
    10.       
  10.  res50: Array[Int] = Array(1, 2, 2)       
    11.
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