GitHub user navis opened a pull request:
https://github.com/apache/phoenix/pull/124
PHOENIX-2288 Phoenix-Spark: PDecimal precision and scale aren't carried
through to Spark DataFrame
from jira description
>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.
It seemed enough just for current usage in spark-interagation. But in long
term, PDataType should contain meta information like maxLength or precision,
etc.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/navis/phoenix PHOENIX-2288
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/phoenix/pull/124.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #124
----
commit 25fa16bcef4e4fcbc9fcf07d935839ed563a9b52
Author: navis.ryu <[email protected]>
Date: 2015-10-22T02:32:30Z
PHOENIX-2288 Phoenix-Spark: PDecimal precision and scale aren't carried
through to Spark DataFrame
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