Jonathancui123 commented on code in PR #36871:
URL: https://github.com/apache/spark/pull/36871#discussion_r905350901
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
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@@ -117,8 +123,19 @@ class CSVInferSchema(val options: CSVOptions) extends
Serializable {
case LongType => tryParseLong(field)
case _: DecimalType => tryParseDecimal(field)
case DoubleType => tryParseDouble(field)
- case TimestampNTZType => tryParseTimestampNTZ(field)
- case TimestampType => tryParseTimestamp(field)
+ case DateType => tryParseDateTime(field)
Review Comment:
Consider the column of a TimestampType followed by a DateType entry. We
would expect this column to be inferred as a TimestampType column.
`typeSoFar` will be `Timestamp` when `inferField` is called on the second
entry which is DateType. We need logic in `inferField` to try and parse Date
type even when `typeSoFar` is `Timestamp`
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