Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14777#discussion_r76104663
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala
---
@@ -251,8 +251,21 @@ case class Literal (value: Any, dataType: DataType)
extends LeafExpression with
case (v: Short, ShortType) => v + "S"
case (v: Long, LongType) => v + "L"
// Float type doesn't have a suffix
- case (v: Float, FloatType) => s"CAST($v AS ${FloatType.sql})"
- case (v: Double, DoubleType) => v + "D"
+ case (v: Float, FloatType) =>
+ val castedValue = v match {
+ case _ if v.isNaN => "'NaN'"
+ case Float.PositiveInfinity => "'Infinity'"
+ case Float.NegativeInfinity => "'-Infinity'"
+ case _ => v
+ }
+ s"CAST($castedValue AS ${FloatType.sql})"
+ case (v: Double, DoubleType) =>
+ v match {
+ case _ if v.isNaN => s"CAST('NaN' AS ${DoubleType.sql})"
+ case Double.PositiveInfinity => s"CAST('Infinity' AS
${DoubleType.sql})"
+ case Double.NegativeInfinity => s"CAST('-Infinity' AS
${DoubleType.sql})"
+ case _ => v + "D"
--- End diff --
I think you'd have to use `CAST(x as DOUBLE PRECISION)`, but Spark doesn't
seem to support `DOUBLE PRECISION` and neither does Hive (AFAIK).
Postgres doesn't understand the `D` suffix and instead treats it as a
column name.
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