You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:42:15 UTC
[jira] [Resolved] (SPARK-21199) Its not possible to impute Vector
types
[ https://issues.apache.org/jira/browse/SPARK-21199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-21199.
----------------------------------
Resolution: Incomplete
> Its not possible to impute Vector types
> ---------------------------------------
>
> Key: SPARK-21199
> URL: https://issues.apache.org/jira/browse/SPARK-21199
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.0.0, 2.1.1
> Reporter: Franklyn Dsouza
> Priority: Major
> Labels: bulk-closed
>
> There are cases where nulls end up in vector columns in dataframes. Currently there is no way to fill in these nulls because its not possible to create a literal vector column expression using lit().
> Also the entire pyspark ml api will fail when they encounter nulls so this makes it hard to work with the data.
> I think that either vector support should be added to the imputer or vectors should be supported in column expressions so they can be used in a coalesce.
> [~mlnick]
--
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