cloud-fan commented on code in PR #52016:
URL: https://github.com/apache/spark/pull/52016#discussion_r2416927216
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TableOutputResolver.scala:
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@@ -471,29 +403,20 @@ object TableOutputResolver extends SQLConfHelper with
Logging {
expectedType: ArrayType,
byName: Boolean,
conf: SQLConf,
- addError: String => Unit,
- colPath: Seq[String]): Option[NamedExpression] = {
- val nullCheckedInput = checkNullability(input, expected, conf, colPath)
+ colPath: Seq[String]): Expression = {
+ val nullCheckedInput = withNullabilityChecked(input, expected, conf,
colPath)
val param = NamedLambdaVariable("element", inputType.elementType,
inputType.containsNull)
val fakeAttr =
AttributeReference("element", expectedType.elementType,
expectedType.containsNull)()
- val res = if (byName) {
- reorderColumnsByName(tableName, Seq(param), Seq(fakeAttr), conf,
addError, colPath)
+ val res = resolveColumns(tableName, Seq(param), Seq(fakeAttr),
+ conf, byName, fillDefaultValue = false, colPath)
+ if (res.head == param) {
+ // If the element type is the same, we can reuse the input array
directly.
+ nullCheckedInput
} else {
- resolveColumnsByPosition(tableName, Seq(param), Seq(fakeAttr), conf,
addError, colPath)
- }
- if (res.length == 1) {
- val castedArray =
- if (res.head == param) {
- // If the element type is the same, we can reuse the input array
directly.
- nullCheckedInput
- } else {
- val func = LambdaFunction(res.head, Seq(param))
- ArrayTransform(nullCheckedInput, func)
- }
- Some(applyColumnMetadata(castedArray, expected))
- } else {
- None
+ // todo: can't we just use a cast here?
Review Comment:
array cast does the same thing essentially: traverse each element and do the
cast.
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