cloud-fan commented on a change in pull request #28576:
URL: https://github.com/apache/spark/pull/28576#discussion_r427980379
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeFormatterHelper.scala
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@@ -31,17 +31,50 @@ import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.internal.SQLConf.LegacyBehaviorPolicy._
trait DateTimeFormatterHelper {
+ private def getOrDefault(accessor: TemporalAccessor, field: ChronoField,
default: Int): Int = {
+ if (accessor.isSupported(field)) {
+ accessor.get(field)
+ } else {
+ default
+ }
+ }
+
+ protected def toLocalDate(accessor: TemporalAccessor, allowMissingYear:
Boolean): LocalDate = {
+ val year = if (accessor.isSupported(ChronoField.YEAR)) {
+ accessor.get(ChronoField.YEAR)
+ } else if (allowMissingYear) {
+ // To keep backward compatibility with Spark 2.x, we pick 1970 as the
default value of year.
+ 1970
+ } else {
+ throw new SparkUpgradeException("3.0",
+ "Year must be given in the date/timestamp string to be parsed. You can
set " +
+ SQLConf.LEGACY_ALLOW_MISSING_YEAR_DURING_PARSING.key + " to true, to
pick 1970 as " +
+ "the default value of year.", null)
+ }
+ val month = getOrDefault(accessor, ChronoField.MONTH_OF_YEAR, 1)
Review comment:
unfortunately datetime functions don't respect the ANSI flag at all.
Maybe we should keep everything the same as Spark 2.4 (return null when parsing
Feb 29 because 1970-02-29 is invalid), and implement ANSI behavior in Spark 3.1?
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