Github user sureshthalamati commented on a diff in the pull request:
https://github.com/apache/spark/pull/12904#discussion_r84373258
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVOptions.scala
---
@@ -90,6 +90,7 @@ private[csv] class CSVOptions(@transient private val
parameters: Map[String, Str
val permissive = ParseModes.isPermissiveMode(parseMode)
val nullValue = parameters.getOrElse("nullValue", "")
+ val emptyValue = parameters.getOrElse("emptyValue", "")
--- End diff --
Yes, null and empty can not be differentiated when they are set to same
value. Currently null value check has higher precedence than the empty value.
input.csv
1,
2,ââ
Output will be:
1, null
2, null
I think this behavior is ok. By default Univocity CSV parser used in
spark also returns null for empty strings.
I agree we should document this behavior.
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