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https://issues.apache.org/jira/browse/PHOENIX-2784?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15265928#comment-15265928
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Nick Dimiduk commented on PHOENIX-2784:
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I'm not following the intended use-case here. Date, Time, and Timestamp are all
different types with different precisions. Instead of overriding the meaning
through configuration, the type information in the schema should be preserved
throughout. If you want Timestamp, use it in your schema.
> phoenix-spark: Allow coercion of DATE fields to TIMESTAMP when loading
> DataFrames
> ---------------------------------------------------------------------------------
>
> Key: PHOENIX-2784
> URL: https://issues.apache.org/jira/browse/PHOENIX-2784
> Project: Phoenix
> Issue Type: Improvement
> Affects Versions: 4.7.0
> Reporter: Josh Mahonin
> Assignee: Josh Mahonin
> Priority: Minor
> Attachments: PHOENIX-2784.patch
>
>
> The Phoenix DATE type is internally represented as an 8 bytes, which can
> store a full 'yyyy-MM-dd hh:mm:ss' time component. However, Spark SQL follows
> the SQL Date spec and keeps only the 'yyyy-MM-dd' portion as a 4 byte type.
> When loading Phoenix DATE columns using the Spark DataFrame API, the
> 'hh:mm:ss' component is lost.
> This patch allows setting a new 'dateAsTimestamp' option when loading a
> DataFrame, which will coerce the underlying Date object to a Timestamp so
> that the full time component is loaded.
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