If you set concurrentJobs flag to 2, then it lets you run two jobs
parallel. It will be a bit hard for you predict the application behavior
with this flag thus debugging would be a headache.
Thanks
Best Regards
On Sun, Aug 23, 2015 at 10:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com
wrote:
Hi
Hmm for a singl core VM you will have to run it in local mode(specifying
master= local[4]). The flag is available in all the versions of spark i
guess.
On Aug 22, 2015 5:04 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote:
Thanks Akhil. Does this mean that the executor running in the VM can
Hi Rishitesh,
We are not using any RDD's to parallelize the processing and all of the
algorithm runs on a single core (and in a single thread). The parallelism
is done at the user level
The disk can be started in a separate IO, but then the executor will not be
able to take up more jobs, since
Hi Akhil,
Think of the scenario as running a piece of code in normal Java with
multiple threads. Lets say there are 4 threads spawned by a Java process to
handle reading from database, some processing and storing to database. In
this process, while a thread is performing a database I/O, the CPU
Thanks Akhil. Does this mean that the executor running in the VM can spawn
two concurrent jobs on the same core? If this is the case, this is what we
are looking for. Also, which version of Spark is this flag in?
Thanks,
Sateesh
On Sat, Aug 22, 2015 at 1:44 AM, Akhil Das
Hi,
My scenario goes like this:
I have an algorithm running in Spark streaming mode on a 4 core virtual
machine. Majority of the time, the algorithm does disk I/O and database
I/O. Question is, during the I/O, where the CPU is not considerably loaded,
is it possible to run any other task/thread
Hi Sateesh,
It is interesting to know , how did you determine that the Dstream runs on
a single core. Did you mean receivers?
Coming back to your question, could you not start disk io in a separate
thread, so that the sceduler can go ahead and assign other tasks ?
On 21 Aug 2015 16:06, Sateesh
You can look at the spark.streaming.concurrentJobs by default it runs a
single job. If set it to 2 then it can run 2 jobs parallely. Its an
experimental flag, but go ahead and give it a try.
On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote:
Hi,
My scenario goes like this: