sadikovi commented on a change in pull request #34596:
URL: https://github.com/apache/spark/pull/34596#discussion_r751910004
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala
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@@ -160,6 +169,15 @@ class CSVInferSchema(val options: CSVOptions) extends
Serializable {
private def tryParseDouble(field: String): DataType = {
if ((allCatch opt field.toDouble).isDefined || isInfOrNan(field)) {
DoubleType
+ } else {
+ tryParseTimestampNTZ(field)
Review comment:
Oh, there is a parsing chain in CSV. It used to be "DoubleType ->
TimestampType" and now it is "DoubleType -> TimestampNTZType -> TimestampType".
This is the order in which we infer columns. So if we cannot parse the
timestamp as TIMESTAMP_NTZ, we will try parsing it as a timestamp with
timezone. Does it answer your question?
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