Spark Console Action functions in Scala

scala spark action examples

scala> val names1 = sc.parallelize(List("abe", "abby", "apple"))
names1: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at parallelize at <console>:12

scala> names1.reduce((t1,t2) => t1 + t2)
res0: String = abbyappleabe

scala> names1.flatMap(k => List(k.size) ).reduce((t1,t2) => t1 + t2)
res1: Int = 12

scala> val names2 = sc.parallelize(List("apple", "beatty", "beatrice")).map(a => (a, a.size))
names2: org.apache.spark.rdd.RDD[(String, Int)] = MappedRDD[3] at map at <console>:12

scala> names2.flatMap(t => Array(t._2)).reduce(_ + _)
res2: Int = 19

scala> sc.parallelize(List(1,2,3)).flatMap(x=>List(x,x,x)).collect
res3: Array[Int] = Array(1, 1, 1, 2, 2, 2, 3, 3, 3)

scala> names2.count
res4: Long = 3

scala> 

scala> names2.first
res5: (String, Int) = (apple,5)

scala> names2.take(2)
res6: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res7: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res8: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res9: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res10: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res11: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res12: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res13: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res14: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res15: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> names2.take(2)
res16: Array[(String, Int)] = Array((apple,5), (beatty,6))

scala> val teams = sc.parallelize(List("twins", "brewers", "cubs", "white sox", "indians", "bad news bears"))
teams: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[7] at parallelize at <console>:12

scala> teams.takeSample(true, 3) 
res17: Array[String] = Array(white sox, twins, brewers)

scala> teams.takeSample(true, 3) 
res18: Array[String] = Array(white sox, bad news bears, brewers)

scala> teams.takeSample(true, 3) 
res19: Array[String] = Array(indians, cubs, white sox)

scala> teams.takeSample(true, 3) 
res20: Array[String] = Array(bad news bears, brewers, cubs)

scala> teams.takeSample(true, 3) 
res21: Array[String] = Array(white sox, white sox, indians)

scala> teams.takeSample(true, 3) 
res22: Array[String] = Array(bad news bears, twins, bad news bears)

scala> val hockeyTeams = sc.parallelize(List("wild", "blackhawks", "red wings", "wild", "oilers", "whalers", "jets", "wild"))
hockeyTeams: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[14] at parallelize at <console>:12

scala> hockeyTeams.map(k => (k,1)).countByKey
res23: scala.collection.Map[String,Long] = Map(jets -> 1, blackhawks -> 1, red wings -> 1, oilers -> 1, whalers -> 1, wild -> 3)