spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Herman van Hovell (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-15505) Explode nested Array in DF Column into Multiple Columns
Date Thu, 26 Jan 2017 16:00:28 GMT

    [ https://issues.apache.org/jira/browse/SPARK-15505?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15839908#comment-15839908
] 

Herman van Hovell commented on SPARK-15505:
-------------------------------------------

Hmmmm.... This is will be quite bad in terms of performance. To me the usefulness also seems
a bit limited, you cannot really reason about the structure of the data frame after doing
this. Why would this be useful?

> Explode nested Array in DF Column into Multiple Columns 
> --------------------------------------------------------
>
>                 Key: SPARK-15505
>                 URL: https://issues.apache.org/jira/browse/SPARK-15505
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 1.6.1
>            Reporter: Jorge Machado
>            Priority: Minor
>
> At the moment if we have a DF like this : 
> {noformat}
> +------+---------+
> | Col1 | Col2    |
> +------+---------+
> |  1   |[2, 3, 4]|
> |  1   |[2, 3, 4]|
> +------+---------+
> {noformat}
> There is no way to directly transform it into : 
> {noformat}
> +------+------+------+------+
> | Col1 | Col2 | Col3 | Col4 |
> +------+------+------+------+
> |  1   |  2   |  3   |  4   |
> |  1   |  2   |  3   |  4   |
> +------+------+------+------+ 
> {noformat}
> I think this should be easy to implement
> More infos here : http://stackoverflow.com/questions/37391241/explode-spark-columns/37392793#37392793



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message