Hi Ankur, For this specific test, I'm only running the few lines of code that are pasted. Nothing else is cached in the cluster.
Thanks, Arash On Mon, Mar 7, 2016 at 4:07 PM, Ankur Srivastava <ankur.srivast...@gmail.com > wrote: > Hi, > > We have a use case where we broadcast ~4GB of data and we are on > m3.2xlarge so your object size is not an issue. Also based on your > explanation does not look like a broadcast issue as it works when your > partition size is small. > > Are you caching any other data? Because boradcast variable use the cache > memory. > > Thanks > Ankur > > On Mon, Mar 7, 2016 at 3:34 PM, Jeff Zhang <zjf...@gmail.com> wrote: > >> Any reason why do you broadcast such large variable ? It doesn't make >> sense to me >> >> On Tue, Mar 8, 2016 at 7:29 AM, Arash <aras...@gmail.com> wrote: >> >>> Hello all, >>> >>> I'm trying to broadcast a variable of size ~1G to a cluster of 20 nodes >>> but haven't been able to make it work so far. >>> >>> It looks like the executors start to run out of memory during >>> deserialization. This behavior only shows itself when the number of >>> partitions is above a few 10s, the broadcast does work for 10 or 20 >>> partitions. >>> >>> I'm using the following setup to observe the problem: >>> >>> val tuples: Array[((String, String), (String, String))] // ~ 10M >>> tuples >>> val tuplesBc = sc.broadcast(tuples) >>> val numsRdd = sc.parallelize(1 to 5000, 100) >>> numsRdd.map(n => tuplesBc.value.head).count() >>> >>> If I set the number of partitions for numsRDD to 20, the count goes >>> through successfully, but at 100, I'll start to get errors such as: >>> >>> 16/03/07 19:35:32 WARN scheduler.TaskSetManager: Lost task 77.0 in stage >>> 1.0 (TID 1677, xxx.ec2.internal): java.lang.OutOfMemoryError: Java heap >>> space >>> at >>> java.io.ObjectInputStream$HandleTable.grow(ObjectInputStream.java:3472) >>> at >>> java.io.ObjectInputStream$HandleTable.assign(ObjectInputStream.java:3278) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1789) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370) >>> at >>> scala.collection.immutable.HashMap$SerializationProxy.readObject(HashMap.scala:516) >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>> at >>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >>> at >>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>> at java.lang.reflect.Method.invoke(Method.java:606) >>> at >>> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1897) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) >>> at >>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) >>> at >>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) >>> at >>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997) >>> at >>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921) >>> >>> >>> I'm using spark 1.5.2. Cluster nodes are amazon r3.2xlarge. The spark >>> property maximizeResourceAllocation is set to true (executor.memory = 48G >>> according to spark ui environment). We're also using kryo serialization and >>> Yarn is the resource manager. >>> >>> Any ideas as what might be going wrong and how to debug this? >>> >>> Thanks, >>> Arash >>> >>> >> >> >> -- >> Best Regards >> >> Jeff Zhang >> > >
