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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