cloud-fan commented on a change in pull request #26134: [SPARK-29486][SQL]
CalendarInterval should have 3 fields: months, days and microseconds
URL: https://github.com/apache/spark/pull/26134#discussion_r339666167
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
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@@ -2610,25 +2610,33 @@ object Sequence {
override val defaultStep: DefaultStep = new DefaultStep(
(dt.ordering.lteq _).asInstanceOf[LessThanOrEqualFn],
CalendarIntervalType,
- new CalendarInterval(0, MICROS_PER_DAY))
+ new CalendarInterval(0, 1, 0))
private val backedSequenceImpl = new IntegralSequenceImpl[T](dt)
- private val microsPerMonth = 28 * CalendarInterval.MICROS_PER_DAY
+ private val microsPerDay = 24 * CalendarInterval.MICROS_PER_HOUR
+ private val microsPerMonth = 28 * microsPerDay
override def eval(input1: Any, input2: Any, input3: Any): Array[T] = {
val start = input1.asInstanceOf[T]
val stop = input2.asInstanceOf[T]
val step = input3.asInstanceOf[CalendarInterval]
val stepMonths = step.months
+ val stepDays = step.days
val stepMicros = step.microseconds
- if (stepMonths == 0) {
- backedSequenceImpl.eval(start, stop, fromLong(stepMicros / scale))
+ if (stepMonths == 0 && stepMicros == 0 && scale == MICROS_PER_DAY) {
+ backedSequenceImpl.eval(start, stop, fromLong(stepDays))
+
+ } else if (stepMonths == 0 && stepDays == 0 && scale == 1) {
+ backedSequenceImpl.eval(start, stop, fromLong(stepMicros))
} else {
// To estimate the resulted array length we need to make assumptions
- // about a month length in microseconds
- val intervalStepInMicros = stepMicros + stepMonths * microsPerMonth
+ // about a month length in days and a day length in microseconds
+ // We choose a minimum days(28) in one month to make sure the estimated
Review comment:
can we move this comment to
https://github.com/apache/spark/pull/26134/files#diff-9853dcf5ce3d2ac1e94d473197ff5768R2617
?
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