Hi,
As I understand, by default in Spark a fraction of the executor memory
(60%) is reserved for RDD caching. So if there's no explicit caching in the
code (eg. rdd.cache() etc.), or if we persist RDD with
StorageLevel.DISK_ONLY, is this part of memory wasted? Does Spark allocates
the RDD cache me
Hi,
I'm modifying the ec2 script for the new r3 instance support, but there's a
problem with the instance storage.
For example, `r3.large` has a single 32GB SSD disk, the problem is that
it's a SSD with TRIM technology and is not automatically formatted and
mounted, `lsblk` gives me this after ec
