Shark's in-memory format is already serialized (it's compressed and column-based).
On Tue, Jul 8, 2014 at 9:50 AM, Mridul Muralidharan <mri...@gmail.com> wrote: > You are ignoring serde costs :-) > > - Mridul > > On Tue, Jul 8, 2014 at 8:48 PM, Aaron Davidson <ilike...@gmail.com> wrote: > > Tachyon should only be marginally less performant than memory_only, > because > > we mmap the data from Tachyon's ramdisk. We do not have to, say, transfer > > the data over a pipe from Tachyon; we can directly read from the buffers > in > > the same way that Shark reads from its in-memory columnar format. > > > > > > > > On Tue, Jul 8, 2014 at 1:18 AM, qingyang li <liqingyang1...@gmail.com> > > wrote: > > > >> hi, when i create a table, i can point the cache strategy using > >> shark.cache, > >> i think "shark.cache=memory_only" means data are managed by spark, and > >> data are in the same jvm with excutor; while "shark.cache=tachyon" > >> means data are managed by tachyon which is off heap, and data are not > in > >> the same jvm with excutor, so spark will load data from tachyon for > each > >> query sql , so, is tachyon less efficient than memory_only cache > strategy > >> ? > >> if yes, can we let spark load all data once from tachyon for all sql > query > >> if i want to use tachyon cache strategy since tachyon is more HA than > >> memory_only ? > >> >
