Comments (3)
These decorators just provide information that mist uses to know what type of context function takes.
So, you want to call the function directly from python, you need to create and pass sparkContext into it.
from mist.
Oh ok thanks @dos65 , then how do we share the same context across the applications.
My requirment is to share Dataframe object across applications for interactive requests. Is it possible to do this using Mist?
Thanks,
Bala
from mist.
Unfortunately, there aren't any built-in feature to share anything except context. Technically, it is possible to cache data on the worker process, but you need to do it on your own.
A context can be shared between several function invocation - there is shared
worker-mode
option for it (details: 1, 2) Actually, it means that Mist tries to reuse worker processes to not to start a new one per every function invocation.
from mist.
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