vinodkc commented on code in PR #53370:
URL: https://github.com/apache/spark/pull/53370#discussion_r2616433239
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala:
##########
@@ -897,6 +897,102 @@ object DateTimeUtils extends SparkDateTimeUtils {
}
}
+ private def withTimeConversionErrorHandling(f: => Long): Long = {
+ try {
+ val nanos = f
+ if (nanos < 0 || nanos >= NANOS_PER_DAY) {
+ throw new DateTimeException(
+ s"Invalid TIME value: must be between 00:00:00 and
23:59:59.999999999, " +
+ s"but got $nanos nanoseconds")
+ }
+ nanos
+ } catch {
+ case e: DateTimeException =>
+ throw
QueryExecutionErrors.ansiDateTimeArgumentOutOfRangeWithoutSuggestion(e)
+ case e: ArithmeticException =>
+ throw
QueryExecutionErrors.ansiDateTimeArgumentOutOfRangeWithoutSuggestion(
+ new DateTimeException("Overflow in TIME conversion", e))
+ }
+ }
+
+ /**
+ * Creates a TIME value from seconds since midnight (integral types).
+ * @param seconds Seconds (0 to 86399)
+ * @return Nanoseconds since midnight
+ */
+ def timeFromSeconds(seconds: Long): Long = withTimeConversionErrorHandling {
+ Math.multiplyExact(seconds, NANOS_PER_SECOND)
+ }
+
+ /**
+ * Creates a TIME value from seconds since midnight (decimal type).
+ * @param seconds Seconds (0 to 86399.999999)
+ * @return Nanoseconds since midnight
+ */
+ def timeFromSeconds(seconds: Decimal): Long =
withTimeConversionErrorHandling {
+ val operand = new java.math.BigDecimal(NANOS_PER_SECOND)
+ seconds.toJavaBigDecimal.multiply(operand).longValueExact()
+ }
+
+ /**
+ * Creates a TIME value from seconds since midnight (floating point type).
+ * @param seconds Seconds (0 to 86399.999999)
+ * @return Nanoseconds since midnight
+ */
+ def timeFromSeconds(seconds: Double): Long = withTimeConversionErrorHandling
{
+ if (seconds.isNaN || seconds.isInfinite) {
+ throw new DateTimeException("Cannot convert NaN or Infinite value to
TIME")
+ }
+ (seconds * NANOS_PER_SECOND).toLong
Review Comment:
Double.toLong can produce overflow results (when the Double is too
large/small):
Large values → Long.MaxValue
Small values → Long.MinValue
How it's handled: The range check `(nanos < 0 || nanos >= NANOS_PER_DAY)` in
`withTimeConversionErrorHandling` detects these overflow values and throws
`SparkDateTimeException`.
I tested with -1e199 , 1e200
```
scala>spark.conf.set("spark.sql.timeType.enabled", "true")
scala>spark.sql("SELECT time_from_seconds(-1e199)").show()
```
```
org.apache.spark.SparkDateTimeException:
[DATETIME_FIELD_OUT_OF_BOUNDS.WITHOUT_SUGGESTION] Invalid TIME value: must be
between 00:00:00 and 23:59:59.999999999, but got -9223372036854775808
nanoseconds. SQLSTATE: 22023
```
```
scala>spark.sql("SELECT time_from_seconds(1e200)").show()
```
```
org.apache.spark.SparkDateTimeException:
[DATETIME_FIELD_OUT_OF_BOUNDS.WITHOUT_SUGGESTION] Invalid TIME value: must be
between 00:00:00 and 23:59:59.999999999, but got 9223372036854775807
nanoseconds. SQLSTATE: 22023
```
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