HyukjinKwon commented on code in PR #36871:
URL: https://github.com/apache/spark/pull/36871#discussion_r898692164
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
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@@ -169,6 +174,14 @@ class CSVInferSchema(val options: CSVOptions) extends
Serializable {
private def tryParseDouble(field: String): DataType = {
if ((allCatch opt field.toDouble).isDefined || isInfOrNan(field)) {
DoubleType
+ } else {
+ tryParseDateTime(field)
+ }
+ }
+
+ private def tryParseDateTime(field: String): DataType = {
+ if ((allCatch opt dateFormatter.parse(field)).isDefined) {
Review Comment:
We should probably 1. add either SQL configuration or an option e.g.,
`infersDate` (like `prefersDecimal` in JSON options), or 2. only infers date
types when `dateFormat` is specified. The main idea is to avoid perf
regression in schema inference by adding this.
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