Parallel writing from same DataFrame in Spark -

let's have dataframe in spark , need write results of 2 databases, 1 stores original data frame other stores modified version (e.g. drops columns). since both operations can take few moments, possible/advisable run these operations in parallel or cause problems because spark working on same object in parallel?

import java.util.concurrent.executors import scala.concurrent._  implicit val ec = executioncontext.fromexecutor(executors.newfixedthreadpool(10))  def write1(){ //your save statement first dataframe }   def write2(){ //your save statement second dataframe }  def writealltables() { future{ write1()} future{ write2()} }