jorisvandenbossche commented on code in PR #14106:
URL: https://github.com/apache/arrow/pull/14106#discussion_r977663050
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cpp/src/arrow/compute/kernels/scalar_cast_extension.cc:
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@@ -42,14 +42,17 @@ Status CastToExtension(KernelContext* ctx, const ExecSpan&
batch, ExecResult* ou
std::shared_ptr<CastFunction> GetCastToExtension(std::string name) {
auto func = std::make_shared<CastFunction>(std::move(name), Type::EXTENSION);
- for (auto types : {IntTypes(), FloatingPointTypes(), StringTypes(),
BinaryTypes()}) {
+ for (auto types : {PrimitiveTypes(), IntervalTypes(), TemporalTypes()}) {
for (auto in_ty : types) {
DCHECK_OK(
func->AddKernel(in_ty->id(), {in_ty}, kOutputTargetType,
CastToExtension));
}
}
- DCHECK_OK(func->AddKernel(Type::DICTIONARY, {InputType(Type::DICTIONARY)},
- kOutputTargetType, CastToExtension));
+ for (auto in_ty : {Type::DICTIONARY, Type::LIST, Type::LARGE_LIST,
+ Type::FIXED_SIZE_LIST, Type::EXTENSION}) {
Review Comment:
I am not sure we should special case extension->extension casts. For a given
extension type, there might be casts based on the storage type that _also_
don't make much sense, so it is hard for us to know in general what cast makes
sense or not.
For a specific use case, in the geometry types, we might have an extension
type backed by a nested type with float or double coordinate values. Being able
to cast from Extension(List<float>) <-> Extension(List<double>) would make
sense in our case.
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