Github user MaxGekk commented on a diff in the pull request: https://github.com/apache/spark/pull/23201#discussion_r240000411 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JsonInferSchema.scala --- @@ -121,7 +122,26 @@ private[sql] class JsonInferSchema(options: JSONOptions) extends Serializable { DecimalType(bigDecimal.precision, bigDecimal.scale) } decimalTry.getOrElse(StringType) - case VALUE_STRING => StringType + case VALUE_STRING => + val stringValue = parser.getText --- End diff -- The order can be matter if you have the same pattern (or similar) for dates and timestamps. `DateType` can be preferable because it requires less memory. It seems reasonable to move from `DateType` to `TimestampType` during schema inferring since opposite one is impossible without loosing info.
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