[GitHub] [spark] HyukjinKwon commented on a change in pull request #34596: [SPARK-37326][SQL] Support TimestampNTZ in CSV data source

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HyukjinKwon commented on a change in pull request #34596:
URL: https://github.com/apache/spark/pull/34596#discussion_r758979898



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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 +169,17 @@ 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)
+    }
+  }
+
+  private def tryParseTimestampNTZ(field: String): DataType = {
+    // We can only parse the value as TimestampNTZType if it does not have zone-offset or
+    // time-zone component and can be parsed with the timestamp formatter.
+    // Otherwise, it is likely to be a timestamp with timezone.
+    if ((allCatch opt timestampNTZFormatter.parseWithoutTimeZone(field, true)).isDefined) {

Review comment:
       Should maybe we skip the parsing if `SQLConf.get.timestampType` is set to `TIMESTAMP_LTZ` since parsing is non-trivial op?




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