Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/20023#discussion_r158207539
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/DecimalType.scala ---
@@ -136,10 +137,54 @@ object DecimalType extends AbstractDataType {
case DoubleType => DoubleDecimal
}
+ private[sql] def forLiteral(literal: Literal): DecimalType =
literal.value match {
+ case v: Short => fromBigDecimal(BigDecimal(v))
+ case v: Int => fromBigDecimal(BigDecimal(v))
+ case v: Long => fromBigDecimal(BigDecimal(v))
+ case _ => forType(literal.dataType)
+ }
+
+ private[sql] def fromBigDecimal(d: BigDecimal): DecimalType = {
+ DecimalType(Math.max(d.precision, d.scale), d.scale)
+ }
+
private[sql] def bounded(precision: Int, scale: Int): DecimalType = {
DecimalType(min(precision, MAX_PRECISION), min(scale, MAX_SCALE))
}
+ // scalastyle:off line.size.limit
+ /**
+ * Decimal implementation is based on Hive's one, which is itself
inspired to SQLServer's one.
+ * In particular, when a result precision is greater than {@link
#MAX_PRECISION}, the
+ * corresponding scale is reduced to prevent the integral part of a
result from being truncated.
+ *
+ * For further reference, please see
+ *
https://blogs.msdn.microsoft.com/sqlprogrammability/2006/03/29/multiplication-and-division-with-numerics/.
--- End diff --
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