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https://issues.apache.org/jira/browse/SPARK-17916?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15649039#comment-15649039
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Eric Liang commented on SPARK-17916:
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We're hitting this as a regression from 2.0 as well.
Ideally, we don't want the empty string to be treated specially in any
scenario. The only logic that converts it to nulls should be due to the
nullValue option.
> CSV data source treats empty string as null no matter what nullValue option is
> ------------------------------------------------------------------------------
>
> Key: SPARK-17916
> URL: https://issues.apache.org/jira/browse/SPARK-17916
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.1
> Reporter: Hossein Falaki
>
> When user configures {{nullValue}} in CSV data source, in addition to those
> values, all empty string values are also converted to null.
> {code}
> data:
> col1,col2
> 1,"-"
> 2,""
> {code}
> {code}
> spark.read.format("csv").option("nullValue", "-")
> {code}
> We will find a null in both rows.
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