cloud-fan commented on code in PR #44800:
URL: https://github.com/apache/spark/pull/44800#discussion_r1459232548
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala:
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@@ -199,14 +201,13 @@ class CSVInferSchema(val options: CSVOptions) extends
Serializable {
}
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.
- val timestampType = SQLConf.get.timestampType
- if ((SQLConf.get.legacyTimeParserPolicy == LegacyBehaviorPolicy.LEGACY ||
- timestampType == TimestampNTZType) &&
- timestampNTZFormatter.parseWithoutTimeZoneOptional(field,
false).isDefined) {
- timestampType
Review Comment:
Schema inference is incremental. If we infer LTZ here, the next value will
be parsed by `tryParseTimestamp` instead of `tryParseTimestampNTZ`. This is
very confusing as the first value matters for the final inferred type.
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