There's no standard way to calculate the memory requirement for driver. It
depends on your app, e.g if you want to fetch large data into driver, then
you'd better to set a large value for driver memory.
Regarding running paragraphs simultaneously, for scala/python/r code, the
execution in one para
I use version 0.7.3. I have been trying to investigate the reasons for the
timeouts. I was trying to tune the number of cores available. Now that
you've mentioned the driver memory issue, I'll try it out again and let you
know if that solves the problem. What would be a back-of-the-envelope
calcula
HI Ajay,
Thanks for the reporting, which version do you use ? One know issue of
spark scoped mode is that each spark repl will occupy large memory and
won't be released, one workaround is to increase the driver memory.
https://jira.apache.org/jira/browse/ZEPPELIN-3389
Ajay Viswanathan 于2018年11月
This is an issue even I am facing in my project currently. By running the
spark interpreter in Scoped + Per Note mode, I do manage to execute
paragraphs in parallel, but it becomes very resource intensive and times
out if I run more than 3-4 jobs in parallel on a 4-core cloud instance.
Typically a
Which version do you use ? This seems a bug. Each note should have its own
scheduler in scoped per note mode.
于2018年11月9日周五 上午1:56写道：
> Hi
>
> We use zeppelin in multi-user environment, the interpreter scope mode
> seems to allow notebook execution in serial only. If multiple users are
> running
Hi
We use zeppelin in multi-user environment, the interpreter scope mode seems to
allow notebook execution in serial only. If multiple users are running their
notebooks concurrently, these notebooks are queued for serial execution. If one
notebook takes a long time to complete, it basically bl
