[jira] [Resolved] (SPARK-22250) Be less restrictive on type checking

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22250?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-22250.
----------------------------------
    Resolution: Incomplete

> Be less restrictive on type checking
> ------------------------------------
>
>                 Key: SPARK-22250
>                 URL: https://issues.apache.org/jira/browse/SPARK-22250
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.0.0
>            Reporter: Fernando Pereira
>            Priority: Minor
>              Labels: bulk-closed
>
> I find types.py._verify_type() often too restrictive. E.g. 
> {code}
> TypeError: FloatType can not accept object 0 in type <type 'int'>
> {code}
> I believe it would be globally acceptable to fill a float field with an int, especially since in some formats (json) you don't have a way of inferring the type correctly.
> Another situation relates to other equivalent numerical types, like array.array or numpy. A numpy scalar int is not accepted as an int, and these arrays have always to be converted down to plain lists, which can be prohibitively large and computationally expensive.
> Any thoughts?



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