[
https://issues.apache.org/jira/browse/SPARK-13700?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15183027#comment-15183027
]
Sean Owen commented on SPARK-13700:
-----------------------------------
Yes, I know {{AsyncRDDActions}} is for async driver operations. Yes, I assume
you want to launch N operations that are "expensive" but not for the Spark
task. I don't know what Spark can or even should do to support this use case.
Scala and the JDK let you implement these types of thing easily with full
control. I think it can be simpler than your POC, and in Java 8 shorter still,
and in Scala it's about a 1-liner when used with mapPartitions. Hence I just
don't think Spark can add much.
> Rdd.mapAsync(): Easily mix Spark and asynchroneous transformation
> -----------------------------------------------------------------
>
> Key: SPARK-13700
> URL: https://issues.apache.org/jira/browse/SPARK-13700
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Reporter: Paulo Costa
> Priority: Minor
> Labels: async, features, rdd, transform
>
> Spark is great for synchronous operations.
> But sometimes I need to call a database/web server/etc from my transform, and
> the Spark pipeline stalls waiting for it.
> Avoiding that would be great!
> I suggest we add a new method RDD.mapAsync(), which can execute these
> operations concurrently, avoiding the bottleneck.
> I've written a quick'n'dirty implementation of what I have in mind:
> https://gist.github.com/paulo-raca/d121cf27905cfb1fafc3
> What do you think?
> If you agree with this feature, I can work on a pull request.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
