You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2021/01/06 20:30:00 UTC
[jira] [Assigned] (SPARK-34033) SparkR Daemon Initialization
[ https://issues.apache.org/jira/browse/SPARK-34033?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-34033:
------------------------------------
Assignee: (was: Apache Spark)
> SparkR Daemon Initialization
> ----------------------------
>
> Key: SPARK-34033
> URL: https://issues.apache.org/jira/browse/SPARK-34033
> Project: Spark
> Issue Type: Improvement
> Components: R, SparkR
> Affects Versions: 3.2.0
> Environment: tested on centos 7 & spark 2.3.1 and on my mac & spark at master
> Reporter: Tom Howland
> Priority: Major
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> Provide a way for users to initialize the sparkR daemon before it forks.
> Described in detail in [docs/sparkr.md|https://github.com/WamBamBoozle/spark/blob/daemon_init/docs/sparkr.md#daemon-initialization]
> I'm a contractor to Target, where we have several projects doing ML with sparkR. The changes proposed here results in weeks of compute-time saved with every run.
> (40000 partitions) * (5 seconds to load our R libraries) * (2 calls to gapply in our app) / 60 / 60 = 111 hours.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org