如何使用scala在spark中并行执行多个函数？

Question

How to execute multiple functions in parallel in spark batch using scala?

 def main(args: Array[String]) {
 def func1() {
 // dataframe 1 write to oracle database table 1
 }
 def func2() {
 // dataframe 2 write to oracle database table 2
 }
 def func3() { 
 // dataframe 3 write to oracle database table 3
 }
}

Answer 1

In general concurrency can be achieved using Futures... following the example below you can try on your own...

see Concurrency in Spark

/** A singleton object that controls the parallelism on a Single Executor JVM, Using the GlobalContext **/
object ConcurrentContext {
  import scala.util._
  import scala.concurrent._
  import scala.concurrent.ExecutionContext.Implicits.global
  /** Wraps a code block in a Future and returns the future */
  def executeAsync[T](f: => T): Future[T] = {
    Future(f)
  }
}

and then

scala> sc.parallelize( 1 to 10).map(fastFoo).map(x => ConcurrentContext.executeAsync(slowFoo(x))).collect
fastFoo(1)
fastFoo(2)
fastFoo(3)
fastFoo(4)
slowFoo start (2)
slowFoo start (1)
fastFoo(5)
slowFoo start (3)
  ...
res6: Array[scala.concurrent.Future[Int]] = Array(List(), List(), List(), List(), List(), List(), List(), List(), List(), List())

scala>  // Our request returns
//Then 5 seconds later
slowFoo end(1)
slowFoo end(7)
slowFoo end(8)
slowFoo end(4)
slowFoo start (10)
slowFoo end(5)