Yep .. I tried that too earlier. Doesn't make a difference. Are you able to replicate on your side?
On Sun, Aug 30, 2015 at 12:08 PM Ted Yu <yuzhih...@gmail.com> wrote: > I see. > > What about using the following in place of variable a ? > > http://spark.apache.org/docs/latest/programming-guide.html#broadcast-variables > > Cheers > > On Sun, Aug 30, 2015 at 8:54 AM, Ashish Shrowty <ashish.shro...@gmail.com> > wrote: > >> @Sean - Agree that there is no action, but I still get the >> stackoverflowerror, its very weird >> >> @Ted - Variable a is just an int - val a = 10 ... The error happens when >> I try to pass a variable into the closure. The example you have above works >> fine since there is no variable being passed into the closure from the >> shell. >> >> -Ashish >> >> On Sun, Aug 30, 2015 at 9:55 AM Ted Yu <yuzhih...@gmail.com> wrote: >> >>> Using Spark shell : >>> >>> scala> import scala.collection.mutable.MutableList >>> import scala.collection.mutable.MutableList >>> >>> scala> val lst = MutableList[(String,String,Double)]() >>> lst: scala.collection.mutable.MutableList[(String, String, Double)] = >>> MutableList() >>> >>> scala> Range(0,10000).foreach(i=>lst+=(("10","10",i:Double))) >>> >>> scala> val rdd=sc.makeRDD(lst).map(i=> if(a==10) 1 else 0) >>> <console>:27: error: not found: value a >>> val rdd=sc.makeRDD(lst).map(i=> if(a==10) 1 else 0) >>> ^ >>> >>> scala> val rdd=sc.makeRDD(lst).map(i=> if(i._1==10) 1 else 0) >>> rdd: org.apache.spark.rdd.RDD[Int] = MapPartitionsRDD[1] at map at >>> <console>:27 >>> >>> scala> rdd.count() >>> ... >>> 15/08/30 06:53:40 INFO DAGScheduler: Job 0 finished: count at >>> <console>:30, took 0.478350 s >>> res1: Long = 10000 >>> >>> Ashish: >>> Please refine your example to mimic more closely what your code actually >>> did. >>> >>> Thanks >>> >>> On Sun, Aug 30, 2015 at 12:24 AM, Sean Owen <so...@cloudera.com> wrote: >>> >>>> That can't cause any error, since there is no action in your first >>>> snippet. Even calling count on the result doesn't cause an error. You >>>> must be executing something different. >>>> >>>> On Sun, Aug 30, 2015 at 4:21 AM, ashrowty <ashish.shro...@gmail.com> >>>> wrote: >>>> > I am running the Spark shell (1.2.1) in local mode and I have a simple >>>> > RDD[(String,String,Double)] with about 10,000 objects in it. I get a >>>> > StackOverFlowError each time I try to run the following code (the code >>>> > itself is just representative of other logic where I need to pass in a >>>> > variable). I tried broadcasting the variable too, but no luck .. >>>> missing >>>> > something basic here - >>>> > >>>> > val rdd = sc.makeRDD(List(<Data read from file>) >>>> > val a=10 >>>> > rdd.map(r => if (a==10) 1 else 0) >>>> > This throws - >>>> > >>>> > java.lang.StackOverflowError >>>> > at java.io.ObjectStreamClass.lookup(ObjectStreamClass.java:318) >>>> > at >>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1133) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) >>>> > at >>>> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1177) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1547) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1508) >>>> > at >>>> > >>>> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1431) >>>> > ... >>>> > ... >>>> > >>>> > More experiments .. this works - >>>> > >>>> > val lst = Range(0,10000).map(i=>("10","10",i:Double)).toList >>>> > sc.makeRDD(lst).map(i=> if(a==10) 1 else 0) >>>> > >>>> > But below doesn't and throws the StackoverflowError - >>>> > >>>> > val lst = MutableList[(String,String,Double)]() >>>> > Range(0,10000).foreach(i=>lst+=(("10","10",i:Double))) >>>> > sc.makeRDD(lst).map(i=> if(a==10) 1 else 0) >>>> > >>>> > Any help appreciated! >>>> > >>>> > Thanks, >>>> > Ashish >>>> > >>>> > >>>> > >>>> > -- >>>> > View this message in context: >>>> http://apache-spark-user-list.1001560.n3.nabble.com/Spark-shell-and-StackOverFlowError-tp24508.html >>>> > Sent from the Apache Spark User List mailing list archive at >>>> Nabble.com. >>>> > >>>> > --------------------------------------------------------------------- >>>> > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>>> > For additional commands, e-mail: user-h...@spark.apache.org >>>> > >>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>>> For additional commands, e-mail: user-h...@spark.apache.org >>>> >>>> >>> >
