Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/16320#discussion_r94358365
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala
---
@@ -85,7 +85,9 @@ private[csv] object CSVInferSchema {
case NullType => tryParseInteger(field, options)
case IntegerType => tryParseInteger(field, options)
case LongType => tryParseLong(field, options)
- case _: DecimalType => tryParseDecimal(field, options)
+ case _: DecimalType =>
+ // DecimalTypes have different precisions and scales, so we try
to find the common type.
+ findTightestCommonType(typeSoFar, tryParseDecimal(field,
options)).getOrElse(NullType)
--- End diff --
Thank you for review, @cloud-fan . I used `NullType` since `mergeRowTypes`
does.
```scala
def mergeRowTypes(first: Array[DataType], second: Array[DataType]):
Array[DataType] = {
first.zipAll(second, NullType, NullType).map { case (a, b) =>
findTightestCommonType(a, b).getOrElse(NullType)
}
}
```
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