MaxGekk commented on a change in pull request #27710: [SPARK-30960][SQL] add
back the legacy date/timestamp format support in CSV/JSON parser
URL: https://github.com/apache/spark/pull/27710#discussion_r384584040
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/UnivocityParser.scala
##########
@@ -175,10 +175,30 @@ class UnivocityParser(
}
case _: TimestampType => (d: String) =>
- nullSafeDatum(d, name, nullable, options)(timestampFormatter.parse)
+ nullSafeDatum(d, name, nullable, options) { datum =>
+ try {
+ timestampFormatter.parse(datum)
+ } catch {
+ case NonFatal(e) =>
+ // If fails to parse, then tries the way used in 2.0 and 1.x for
backwards
+ // compatibility.
+ val str = UTF8String.fromString(datum)
+ DateTimeUtils.stringToTimestamp(str,
options.zoneId).getOrElse(throw e)
Review comment:
Looking at what was removed there
https://github.com/apache/spark/pull/23150/files#diff-c82e4b74d2a51fed29069745ce4f9e96L164
, `DateTimeUtils.stringToTime` and `DateTimeUtils.stringToTimestamp` are 2
different functions, see
https://github.com/MaxGekk/spark/blob/60c0974261c947c0838457c40f4fe0e64d17ca15/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala#L173-L191
`stringToTime` has a few problems - it doesn't respect to Spark's session
time zone, and parses in the combined calendar. If you use it as a fallback,
you can get parsed values in different calendars.
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