cloud-fan commented on code in PR #32959:
URL: https://github.com/apache/spark/pull/32959#discussion_r884900931
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala:
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@@ -518,44 +516,55 @@ object DateTimeUtils {
* The return type is [[Option]] in order to distinguish between 0 and null.
The following
* formats are allowed:
*
- * `yyyy`
- * `yyyy-[m]m`
- * `yyyy-[m]m-[d]d`
- * `yyyy-[m]m-[d]d `
- * `yyyy-[m]m-[d]d *`
- * `yyyy-[m]m-[d]dT*`
+ * `[+-]yyyy*`
+ * `[+-]yyyy*-[m]m`
+ * `[+-]yyyy*-[m]m-[d]d`
+ * `[+-]yyyy*-[m]m-[d]d `
+ * `[+-]yyyy*-[m]m-[d]d *`
+ * `[+-]yyyy*-[m]m-[d]dT*`
*/
def stringToDate(s: UTF8String): Option[Int] = {
- if (s == null) {
+ def isValidDigits(segment: Int, digits: Int): Boolean = {
+ // An integer is able to represent a date within [+-]5 million years.
+ var maxDigitsYear = 7
Review Comment:
BTW, I don't think it's possible to add a Spark config to forbid large
datetime values. The literal is just one place, there are many other datetime
operations that may produce large datetime values, which have been there before
this PR.
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