Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/13138#discussion_r63450908
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/GenericArrayData.scala
---
@@ -37,6 +37,11 @@ class GenericArrayData(val array: Array[Any]) extends
ArrayData {
def this(primitiveArray: Array[Byte]) = this(primitiveArray.toSeq)
def this(primitiveArray: Array[Boolean]) = this(primitiveArray.toSeq)
+ def this(seqOrArray: Any) = this(seqOrArray match {
--- End diff --
We don't. For `RowEncoder`, we only have the schema when we build it, no
type info. Actually there are 3 special cases overall, one is array type, we
support both seq and array. One is decimal type, we support both java/scala
`BigDecimal` and `Decimal`. One is struct type, we support both `Row` and
`Product`. They all use runtime reflection
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