should not be the reason.
My question is. Does Spark and especially GraphX adapt its behavior to
the available network transfer rate? Does anybody have an idea how a
faster network could decrease the performance?
Thank you very much!
Kind regards,
Niklas Wilcke
)
}
On 10.01.2015 06:56, Xiangrui Meng wrote:
sample 2 * n tuples, split them into two parts, balance the sizes of
these parts by filtering some tuples out
How do you guarantee that the two RDDs have the same size?
-Xiangrui
On Fri, Jan 9, 2015 at 3:40 AM, Niklas Wilcke
1wil
Hi Spark community,
I have a problem with zipping two RDDs of the same size and same number
of partitions.
The error message says that zipping is only allowed on RDDs which are
partitioned into chunks of exactly the same sizes.
How can I assure this? My workaround at the moment is to repartition
Hi Jao,
I don't really know why this doesn't work but I have two hints.
You don't need to override hashCode and equals. The modifier case is
doing that for you. Writing
case class PersonID(id: String)
would be enough to get the class you want I think.
If I change the type of the id param to Int
