problem24

scala> val a = sc.parallelize(List("dog", "salmon", "salmon", "rat", "elephant"), 3)
a: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at parallelize at <console>:27

scala> val b = a.keyBy(_.length)
b: org.apache.spark.rdd.RDD[(Int, String)] = MapPartitionsRDD[1] at keyBy at <console>:29

scala> val c = sc.parallelize(List("dog","cat","gnu","salmon","rabbit","turkey","woif","bear","bee"), 3)
c: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[2] at parallelize at <console>:27
scala> val d = c.keyBy(_.length)
d: org.apache.spark.rdd.RDD[(Int, String)] = MapPartitionsRDD[3] at keyBy at <console>:29
res0: Array[(Int, (String, String))] = Array((6,(salmon,salmon)), (6,(salmon,rabbit)), (6,(salmon,turkey)), (6,(salmon,salmon)), (6,(salmon,rabbit)), (6,(salmon,turkey)), (3,(dog,dog)), (3,(dog,cat)), (3,(dog,gnu)), (3,(dog,bee)), (3,(rat,dog)), (3,(rat,cat)), (3,(rat,gnu)), (3,(rat,bee)))

// join
join [Pair]: Performs an inner join using two key-value RDDs. Please note that the keys must be generally comparable to make this work. keyBy : Constructs two-component tuples
(key-value pairs) by applying a function on each data item. The result of the function becomes the data item becomes the key and the original value of the newly created tuples.