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Posted to issues@spark.apache.org by "Paulo Costa (JIRA)" <ji...@apache.org> on 2016/03/05 19:53:40 UTC

[jira] [Updated] (SPARK-13700) Rdd.mapAsync(): Easily mix Spark and asynchroneous transformation

     [ https://issues.apache.org/jira/browse/SPARK-13700?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Paulo Costa updated SPARK-13700:
--------------------------------
    Description: 
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.

  was:
Spark is great for synchronous operations.

But sometimes I need to call a web 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.


> 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
>    Affects Versions: 1.6.0
>            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.



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