fix: Fix Spark slice function Null type to GenericListArray casting issue

[erenavsarogullari]

Which issue does this PR close?

• Closes Fix Spark slice function Null type to GenericListArray casting issue #20466.

Rationale for this change

Currently, Spark slice function accepts Null Arrays and return Null for this particular queries. DataFusion-Spark slice function also needs to return NULL when Null Array is set.
Spark Behavior (tested with latest Spark master):

> SELECT slice(NULL, 1, 2);
+-----------------+
|slice(NULL, 1, 2)|
+-----------------+
|             null|
+-----------------+

DF Behaviour:
Current:

query error
SELECT slice(NULL, 1, 2);
----
DataFusion error: Internal error: could not cast array of type Null to arrow_array::array::list_array::GenericListArray<i32>.
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

New:

query ?
SELECT slice(NULL, 1, 2);
----
NULL

What changes are included in this PR?

Explained under first section.

Are these changes tested?

Added new UT cases for both slice.rs and slice.slt.

Are there any user-facing changes?

Yes, currently, slice function returns error message for Null Array inputs, however, expected behavior is to be returned NULL so end-user will get expected result instead of error message.

[Jefffrey]

Does Spark return null (void) or an array of null (void)?

I tested on PySpark 4.1.1

>>> spark.sql("select slice(NULL, 1, 2) as a").printSchema()
root
 |-- a: array (nullable = true)
 |    |-- element: void (containsNull = true)

• Seems to suggest the latter?

[erenavsarogullari]

Spark returns Array as (nullable = true / false) and there are 2 representations as follows in terms of input array so it returns input array for both cases as either NULL or [NULL]:
Case1: input array is null (array (nullable = true)):

+-----------------+
|slice(NULL, 1, 2)|
+-----------------+
|             NULL|
+-----------------+

root
 |-- slice(NULL, 1, 2): array (nullable = true)
 |    |-- element: void (containsNull = true)

Case2: input array has null element (array (nullable = false)):

+------------------------+
|slice(array(NULL), 1, 2)|
+------------------------+
|                  [NULL]|
+------------------------+

root
 |-- slice(array(NULL), 1, 2): array (nullable = false)
 |    |-- element: void (containsNull = true)

[Jefffrey]

This seems to suggest return type should be list of nulls instead of just null

[martin-g]

Is there a need of the turbofish here ?

Suggested change

	return Ok::<ColumnarValue, DataFusionError>(func_args.args[0].clone());
	return Ok(func_args.args[0].clone());

This will also make the new import of DataFusionError not needed

[martin-g]

Suggested change

	};
	}

[martin-g]

Suggested change

	assert!(result.to_array(1).unwrap() == Arc::new(NullArray::new(1)));
	assert_eq!(result.to_array(1).unwrap(), Arc::new(NullArray::new(1)));

[martin-g]

Suggested change

	args: input_args.to_owned(),
	args: input_args,

[martin-g]

Suggested change

	List(FieldRef::new(Field::new("", DataType::Int64, true))),
	List(FieldRef::new(Field::new("f", DataType::Int64, true))),

It looks weird to use an empty name for a field.

[martin-g]

Suggested change

	number_rows: 0,
	number_rows: 1,

to match with the length of NullArray::new(1)