Spark - Random Number Generation

Question

I have written a method that must consider a random number to simulate a Bernoulli distribution. I am using random.nextDouble to generate a number between 0 and

Answer 1

The reason why the same sequence is repeated is that the random generator is created and initialized with a seed before the data is partitioned. Each partition then starts from the same random seed. Maybe not the most efficient way to do it, but the following should work:

val myClass = new MyClass()
val M = 3

for (m <- 1 to M) {
  val newDF = sqlContext.createDataFrame(myDF
    .map{ 
       val rand = scala.util.Random
       row => RowFactory
      .create(row.getString(0),
        myClass.myMethod(row.getString(2), rand.nextDouble())
    }, myDF.schema)
}