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https://issues.apache.org/jira/browse/PHOENIX-2288?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14987765#comment-14987765
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James Taylor commented on PHOENIX-2288:
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Thanks, [~jmahonin]. Have you addressed this feedback yet?
https://github.com/apache/phoenix/pull/124#discussion_r42823983
> 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
> Attachments: PHOENIX-2288.patch
>
>
> 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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