cloud-fan commented on a change in pull request #28645:
URL: https://github.com/apache/spark/pull/28645#discussion_r430521074
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala
##########
@@ -103,17 +102,31 @@ case class ScalaUDF(
}
}
- private def createToScalaConverter(i: Int, dataType: DataType): Any => Any =
{
+ private def scalaConverter(i: Int, dataType: DataType): Any => Any = {
if (inputEncoders.isEmpty) {
// for untyped Scala UDF
- CatalystTypeConverters.createToScalaConverter(dataType)
+ createToScalaConverter(dataType)
+ } else if (isPrimitive(dataType)) {
+ identity
} else {
val encoder = inputEncoders(i)
- if (encoder.isDefined && encoder.get.isSerializedAsStructForTopLevel) {
- val fromRow = encoder.get.resolveAndBind().createDeserializer()
- row: Any => fromRow(row.asInstanceOf[InternalRow])
- } else {
- CatalystTypeConverters.createToScalaConverter(dataType)
+ encoder match {
+ case Some(enc) =>
+ if (enc.isSerializedAsStructForTopLevel) {
+ val fromRow = enc.resolveAndBind().createDeserializer()
+ row: Any => fromRow(row.asInstanceOf[InternalRow])
+ } else {
+ val child = children(i)
+ val attrs = new StructType().add(s"$child",
child.dataType).toAttributes
Review comment:
`child.toString` can be expensive. how about `"child"`? The name doesn't
matter anyway.
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala
##########
@@ -103,17 +102,31 @@ case class ScalaUDF(
}
}
- private def createToScalaConverter(i: Int, dataType: DataType): Any => Any =
{
+ private def scalaConverter(i: Int, dataType: DataType): Any => Any = {
if (inputEncoders.isEmpty) {
// for untyped Scala UDF
- CatalystTypeConverters.createToScalaConverter(dataType)
+ createToScalaConverter(dataType)
+ } else if (isPrimitive(dataType)) {
+ identity
} else {
val encoder = inputEncoders(i)
- if (encoder.isDefined && encoder.get.isSerializedAsStructForTopLevel) {
- val fromRow = encoder.get.resolveAndBind().createDeserializer()
- row: Any => fromRow(row.asInstanceOf[InternalRow])
- } else {
- CatalystTypeConverters.createToScalaConverter(dataType)
+ encoder match {
+ case Some(enc) =>
+ if (enc.isSerializedAsStructForTopLevel) {
+ val fromRow = enc.resolveAndBind().createDeserializer()
Review comment:
to be consistent, shall we bind with
`child.dataType.asInstanceOf[StructType].toAttributes`?
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala
##########
@@ -581,4 +581,40 @@ class UDFSuite extends QueryTest with SharedSparkSession {
.toDF("col1", "col2")
checkAnswer(df.select(myUdf(Column("col1"), Column("col2"))), Row(2020) ::
Nil)
}
+
+ test("case class as element type of Seq/Array") {
Review comment:
can we also test some special cases:
1. the catalyst schema has more fields than the case class. e.g.
`struct<key: int, value: string, col: int>` and `case class TestData(key: Int,
value: String)`
2. the fields order doesn't match, e.g. `struct<value: string, key: int>`
and `case class TestData(key: Int, value: String)`
3. the catalyst schema has missing fields, e.g. `struct<key: int>` and `case
class TestData(key: Int, value: String)`
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