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From "James Taylor (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (PHOENIX-2288) Phoenix-Spark: PDecimal precision and scale aren't carried through to Spark DataFrame
Date Sat, 26 Sep 2015 19:53:04 GMT

    [ https://issues.apache.org/jira/browse/PHOENIX-2288?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14909444#comment-14909444
] 

James Taylor commented on PHOENIX-2288:
---------------------------------------

+1 to exposing scale and maxLength (precision for Decimal and max characters for CHAR) in
ColumnInfo.

> Phoenix-Spark: PDecimal precision and scale aren't carried through to Spark DataFrame
> -------------------------------------------------------------------------------------
>
>                 Key: PHOENIX-2288
>                 URL: https://issues.apache.org/jira/browse/PHOENIX-2288
>             Project: Phoenix
>          Issue Type: Bug
>    Affects Versions: 4.5.2
>            Reporter: Josh Mahonin
>
> When loading a Spark dataframe from a Phoenix table with a 'DECIMAL' type, the underlying
precision and scale aren't carried forward to Spark.
> The Spark catalyst schema converter should load these from the underlying column. These
appear to be exposed in the ResultSetMetaData, but if there was a way to expose these somehow
through ColumnInfo, it would be cleaner.
> I'm not sure if Pig has the same issues or not, but I suspect it may.



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