why more than more jobs in a batch in spark streaming ?

and reality. I have gone over the book and did some googling, but still I could not find the relationship between batch and jobs. Could anyone share insights? Thanks a lot! -- Regards, Shenghua (Daniel) Wan

Re: broadcast variable of Kafka producer throws ConcurrentModificationException

as Kafka producent is thread-safe you don't need any pool at all. >> Just share single producer on every executor. Please look at my blog post >> for more details. http://allegro.tech/spark-kafka-integration.html >> 19 sie 2015 2:00 AM "Shenghua(Daniel) Wan" >>

Re: broadcast variable of Kafka producer throws ConcurrentModificationException

fka producer to be serializable at all... among >> other things, it has a background thread >> >> On Tue, Aug 18, 2015 at 4:55 PM, Shenghua(Daniel) Wan < >> wansheng...@gmail.com> wrote: >> >>> Hi, >>> Did anyone see java.util.ConcurrentModificatio

broadcast variable of Kafka producer throws ConcurrentModificationException

llectionSerializer.java:67) at com.esotericsoftware.kryo.serializers.CollectionSerializer.write(CollectionSerializer.java:18) at com.esotericsoftware.kryo.Kryo.writeObject(Kryo.java:501) at com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.write(FieldSerializer.java:564) ... 41 more ​Thanks.​ -- Regards, Shenghua (Daniel) Wan