Pi estimation - Compute heavy problem

pi estimation compute heavy process

parallelize : across machines

val rdd1 = sc.parallelize(1 to 100000)
//independent of input number
val rdd2 = rdd1.filter { _ =>
    val x = math.random
    val y = math.random
    x*x+y*y < 1

}
val count = rdd2.count()
println(s"Pi is roughly ${4.0*count/100000}")

circle equation is  x*x+y*y = 1 so, we are checking what all points which are falling
within the circle


scala> val rdd1 = sc.parallelize(1 to 100000)
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[10] at parallelize at :27

scala> //independent of input number

scala> val rdd2 = rdd1.filter { _ =>
     |     val x = math.random
     |     val y = math.random
     |     x*x+y*y < 1
     |
     | }
rdd2: org.apache.spark.rdd.RDD[Int] = MapPartitionsRDD[11] at filter at :29

scala> val count = rdd2.count()
count: Long = 78668

scala> println(s"Pi is roughly ${4.0*count/100000}")
Pi is roughly 3.14672

scala>