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Posted to issues@spark.apache.org by "Liang-Chi Hsieh (JIRA)" <ji...@apache.org> on 2015/05/01 09:04:07 UTC
[jira] [Comment Edited] (SPARK-7196) decimal precision lost when
loading DataFrame from JDBC
[ https://issues.apache.org/jira/browse/SPARK-7196?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14522855#comment-14522855 ]
Liang-Chi Hsieh edited comment on SPARK-7196 at 5/1/15 7:04 AM:
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[~kgeis] I can't reproduce this problem too. Would you mind provide more information, such as the schema of amounts? Are you using "org.apache.spark.sql.parquet" as your defaultDataSourceName?
was (Author: viirya):
[~kgeis] I can't reproduce this problem too. Would you mind provide more information, such as the schema of amounts? Are you using {code}"org.apache.spark.sql.parquet"{code} as {code}defaultDataSourceName{code}?
> decimal precision lost when loading DataFrame from JDBC
> -------------------------------------------------------
>
> Key: SPARK-7196
> URL: https://issues.apache.org/jira/browse/SPARK-7196
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: Ken Geis
> Assignee: Liang-Chi Hsieh
> Fix For: 1.3.2, 1.4.0
>
>
> I have a decimal database field that is defined as 10.2 (i.e. ##########.##). When I load it into Spark via sqlContext.jdbc(..), the type of the corresponding field in the DataFrame is DecimalType, with precisionInfo None. Because of that loss of precision information, SPARK-4176 is triggered when I try to .saveAsTable(..).
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