fix: spark array return type mismatch when inner data type is LargeList (apache#18485)

## Which issue does this PR close?

<!--
We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes apache#123` indicates that this PR will close issue apache#123.
-->

- This PR came up as part of apache#17964.

## Rationale for this change

<!--
Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
your changes and offer better suggestions for fixes.
-->

This PR is intended to fix return type mismatch of spark `array` when
inner data type is `LargeList`, e.g.
```
query error
SELECT array(arrow_cast(array(1), 'LargeList(Int64)'))
----
DataFusion error: Internal error: Function 'array' returned value of type 'LargeList(Field { name: "element", data_type: LargeList(Field { data_type: Int64, nullable: true }), nullable: true })' while the following type was promised at planning time and expected: 'List(Field { name: "element", data_type: LargeList(Field { data_type: Int64, nullable: true }), nullable: true })'.
This issue was likely caused by a bug in DataFusion's code. Please help us to resolve this by filing a bug report in our issue tracker: https://github.com/apache/datafusion/issues
```

## What changes are included in this PR?

<!--
There is no need to duplicate the description in the issue here but it
is sometimes worth providing a summary of the individual changes in this
PR.
-->

- Return `List` regardless of whether inner data type is `LargeList` or
not. This aligns with the behavior of datafusion `make_array` function.
- Remove `return_field_from_args` as `return_type` is already defined
and is invoked internally.

## Are these changes tested?

<!--
We typically require tests for all PRs in order to:
1. Prevent the code from being accidentally broken by subsequent changes
2. Serve as another way to document the expected behavior of the code

If tests are not included in your PR, please explain why (for example,
are they covered by existing tests)?
-->

Yes

## Are there any user-facing changes?

<!--
If there are user-facing changes then we may require documentation to be
updated before approving the PR.
-->

<!--
If there are any breaking changes to public APIs, please add the `api
change` label.
-->

No.

---------

Co-authored-by: Michael Kleen <mkleen@gmail.com>
Co-authored-by: Sergey Zhukov <62326549+cj-zhukov@users.noreply.github.com>
Co-authored-by: Sergey Zhukov <szhukov@aligntech.com>
Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
Co-authored-by: bubulalabu <bubulalabububu@gmail.com>
Co-authored-by: Vegard Stikbakke <vegard.stikbakke@gmail.com>

Author: 7 people

datafusion/spark/src/function/array/spark_array.rs

@@ -24,7 +24,7 @@ use arrow::array::{
 use arrow::buffer::OffsetBuffer;
 use arrow::datatypes::{DataType, Field, FieldRef};
 use datafusion_common::utils::SingleRowListArrayBuilder;
-use datafusion_common::{plan_datafusion_err, plan_err, Result};
+use datafusion_common::{internal_err, plan_datafusion_err, plan_err, Result};
 use datafusion_expr::type_coercion::binary::comparison_coercion;
 use datafusion_expr::{
     ColumnarValue, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDFImpl, Signature,
@@ -72,9 +72,20 @@ impl ScalarUDFImpl for SparkArray {
         &self.signature
     }
 
-    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
+    fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
+        internal_err!("return_field_from_args should be used instead")
+    }
+
+    fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> {
+        let data_types = args
+            .arg_fields
+            .iter()
+            .map(|f| f.data_type())
+            .cloned()
+            .collect::<Vec<_>>();
+
         let mut expr_type = DataType::Null;
-        for arg_type in arg_types {
+        for arg_type in &data_types {
             if !arg_type.equals_datatype(&DataType::Null) {
                 expr_type = arg_type.clone();
                 break;
@@ -85,21 +96,12 @@ impl ScalarUDFImpl for SparkArray {
             expr_type = DataType::Int32;
         }
 
-        Ok(DataType::List(Arc::new(Field::new(
+        let return_type = DataType::List(Arc::new(Field::new(
             ARRAY_FIELD_DEFAULT_NAME,
             expr_type,
             true,
-        ))))
-    }
+        )));
 
-    fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> {
-        let data_types = args
-            .arg_fields
-            .iter()
-            .map(|f| f.data_type())
-            .cloned()
-            .collect::<Vec<_>>();
-        let return_type = self.return_type(&data_types)?;
         Ok(Arc::new(Field::new(
             "this_field_name_is_irrelevant",
             return_type,
@@ -166,7 +168,6 @@ pub fn make_array_inner(arrays: &[ArrayRef]) -> Result<ArrayRef> {
                     .build_list_array(),
             ))
         }
-        DataType::LargeList(..) => array_array::<i64>(arrays, data_type),
         _ => array_array::<i32>(arrays, data_type),
     }
 }

datafusion/sqllogictest/test_files/spark/array/array.slt

@@ -70,3 +70,18 @@ query ?
 SELECT array(array(1,2));
 ----
 [[1, 2]]
+
+query ?
+SELECT array(arrow_cast(array(1), 'LargeList(Int64)'));
+----
+[[1]]
+
+query ?
+SELECT array(arrow_cast(array(1), 'LargeList(Int64)'), arrow_cast(array(), 'LargeList(Int64)'));
+----
+[[1], []]
+
+query ?
+SELECT array(arrow_cast(array(1,2), 'LargeList(Int64)'), array(3));
+----
+[[1, 2], [3]]