I used the word "streaming" but I did not mean to refer to spark streaming. I meant if a partition containing 10 objects was kryo-serialized into a single buffer, then in a mapPartitions() call, as I call iter.next() 10 times to access these objects one at a time, does the deserialization happen
a) once to get all 10 objects,
b) 10 times "incrementally" to get an object at a time, or
c) 10 times to get 10 objects and discard the "wrong" 9 objects [ i doubt this would a design anyone would have adopted ]
I think your answer is option (a) and you refered to Spark streaming to indicate that there is no difference in its behavior from spark core...right?

If it is indeed option (a), I am happy with it and don't need to customize. If it is (b), I would like to have (a) instead.

I am also wondering if kryo is good at compression of strings and numbers. Often I have the data type as "Double" but it could be encoded in much fewer bits.

On Tue, Nov 4, 2014 at 1:02 PM, Tathagata Das <tathagata.das1565@gmail.com> wrote:
It it deserialized in a streaming manner as the iterator moves over the partition. This is a functionality of core Spark, and Spark Streaming just uses it as is. 
What do you want to customize it to? 

On Tue, Nov 4, 2014 at 9:22 AM, Mohit Jaggi <mohitjaggi@gmail.com> wrote:
If I have an RDD persisted in MEMORY_ONLY_SER mode and then it is needed for a transformation/action later, is the whole partition of the RDD deserialized into Java objects first before my transform/action code works on it? Or is it deserialized in a streaming manner as the iterator moves over the partition? Is this behavior customizable? I generally use the Kryo serializer.