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Helena Edelson edited comment on SPARK-2593 at 10/13/14 11:58 AM: ------------------------------------------------------------------ [~matei], [~pwendell] Yes I see the pain point here now. I just created a ticket ( https://issues.apache.org/jira/browse/SPARK-3924 ) to upgrade Akka and thus Typesafe Config versions because I am now locked into 2.2.3 and have binary incompatibility with using latest Akka 2.3.6 / config 1.2.1. Makes me very sad. I think I would throw in the towel on this one if you can make it completely separate so that a user with it's own AkkaSystem and Config versions are not affected? Tricky because when deploying, spark needs its version (provided?) and the user app needs the other. was (Author: helena_e): [~matei], [~pwendell] Yes I see the pain point here now. I just created a ticket 9https://issues.apache.org/jira/browse/SPARK-3924) to upgrade Akka and thus Typesafe Config versions because I am now locked into 2.2.3 and have binary incompatibility with using latest Akka 2.3.6 / config 1.2.1. Makes me very sad. I think I would throw in the towel on this one if you can make it completely separate so that a user with it's own AkkaSystem and Config versions are not affected? Tricky because when deploying, spark needs its version (provided?) and the user app needs the other. > Add ability to pass an existing Akka ActorSystem into Spark > ----------------------------------------------------------- > > Key: SPARK-2593 > URL: https://issues.apache.org/jira/browse/SPARK-2593 > Project: Spark > Issue Type: Improvement > Components: Spark Core > Reporter: Helena Edelson > > As a developer I want to pass an existing ActorSystem into StreamingContext > in load-time so that I do not have 2 actor systems running on a node in an > Akka application. > This would mean having spark's actor system on its own named-dispatchers as > well as exposing the new private creation of its own actor system. > > -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org