Hi We are running Zeppelin (0.5) on our YARN managed cluster. To allow for multiple concurrent users, without sharing the spark context, we simply setup one interpreter for every user. This works pretty OK, however, at some point we seem to hit the limit of how many concurrent (spark) interpreters the Zeppelin (daemon) service can handle. Now with the “new” (0.6) feature of isolated notebooks, this topic should pop up with other users as well. So, I was wondering: what are your experiences with multiple concurrent interpreters? What are determining factors for the question how many concurrent interpreters can run (besides from cluster resources to actually be able to start the multiple interpreters)? Any experiences on that? For us it seems that 2-3 is OK, 4-5 get’s critical, but that also depends on the load of the jobs it seems. Thx.
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