Jonathancui123 commented on code in PR #36871:
URL: https://github.com/apache/spark/pull/36871#discussion_r918142012
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
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@@ -117,7 +123,10 @@ class CSVInferSchema(val options: CSVOptions) extends
Serializable {
case LongType => tryParseLong(field)
case _: DecimalType => tryParseDecimal(field)
case DoubleType => tryParseDouble(field)
+ case DateType => tryParseDateTime(field)
+ case TimestampNTZType if options.inferDate => tryParseDateTime(field)
Review Comment:
Our expected behavior is that in a column with `TimestampType` entries and
then `DateType` entries, the column will be inferred as `TimestampType`.
Here, `tryParseTimestampNTZ` and `tryParseTimestamp` will not be able to
parse the `DateType` entries that show up later in the column and the column
will be promoted to string type. So we must use `tryParseDateTime` which will
give a chance for the date to be parsed.
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