refactor: Refactor spark width bucket signature away from user defined (#19065)

## 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 #123` indicates that this PR will close issue #123.
-->

- Part of #12725 

## Rationale for this change

- As per the goal stated that we should avoid using the user_defined in
useful places

<!--
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.
-->

## What changes are included in this PR?

- Refactor the `user_defined` in spark width_bucket

<!--
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.
-->

## 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)?
-->

## 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.
-->

---------

Co-authored-by: Jeffrey Vo <[email protected]>

Author: kumarUjjawal

datafusion/common/src/types/builtin.rs

@@ -16,6 +16,7 @@
 // under the License.
 
 use arrow::datatypes::IntervalUnit::*;
+use arrow::datatypes::TimeUnit::*;
 
 use crate::types::{LogicalTypeRef, NativeType};
 use std::sync::{Arc, LazyLock};
@@ -82,3 +83,17 @@ singleton_variant!(
     Interval,
     MonthDayNano
 );
+
+singleton_variant!(
+    LOGICAL_INTERVAL_YEAR_MONTH,
+    logical_interval_year_month,
+    Interval,
+    YearMonth
+);
+
+singleton_variant!(
+    LOGICAL_DURATION_MICROSECOND,
+    logical_duration_microsecond,
+    Duration,
+    Microsecond
+);

datafusion/spark/src/function/math/width_bucket.rs

@@ -18,7 +18,6 @@
 use std::any::Any;
 use std::sync::Arc;
 
-use crate::function::error_utils::unsupported_data_types_exec_err;
 use arrow::array::{
     Array, ArrayRef, DurationMicrosecondArray, Float64Array, IntervalMonthDayNanoArray,
     IntervalYearMonthArray,
@@ -30,14 +29,21 @@ use datafusion_common::cast::{
     as_duration_microsecond_array, as_float64_array, as_int32_array,
     as_interval_mdn_array, as_interval_ym_array,
 };
-use datafusion_common::{exec_err, Result};
+use datafusion_common::types::{
+    logical_duration_microsecond, logical_float64, logical_int32, logical_interval_mdn,
+    logical_interval_year_month, NativeType,
+};
+use datafusion_common::{exec_err, internal_err, Result};
 use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
-use datafusion_expr::type_coercion::is_signed_numeric;
-use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature};
+use datafusion_expr::{
+    ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, TypeSignature,
+    TypeSignatureClass,
+};
 use datafusion_functions::utils::make_scalar_function;
 
 use arrow::array::{Int32Array, Int32Builder};
 use arrow::datatypes::TimeUnit::Microsecond;
+use datafusion_expr::Coercion;
 use datafusion_expr::Volatility::Immutable;
 
 #[derive(Debug, PartialEq, Eq, Hash)]
@@ -53,8 +59,59 @@ impl Default for SparkWidthBucket {
 
 impl SparkWidthBucket {
     pub fn new() -> Self {
+        let numeric = Coercion::new_implicit(
+            TypeSignatureClass::Native(logical_float64()),
+            vec![TypeSignatureClass::Numeric],
+            NativeType::Float64,
+        );
+        let duration = Coercion::new_implicit(
+            TypeSignatureClass::Native(logical_duration_microsecond()),
+            vec![TypeSignatureClass::Duration],
+            NativeType::Duration(Microsecond),
+        );
+        let interval_ym = Coercion::new_exact(TypeSignatureClass::Native(
+            logical_interval_year_month(),
+        ));
+        let interval_mdn =
+            Coercion::new_exact(TypeSignatureClass::Native(logical_interval_mdn()));
+        let bucket = Coercion::new_implicit(
+            TypeSignatureClass::Native(logical_int32()),
+            vec![TypeSignatureClass::Integer],
+            NativeType::Int32,
+        );
+        let type_signature = Signature::one_of(
+            vec![
+                TypeSignature::Coercible(vec![
+                    numeric.clone(),
+                    numeric.clone(),
+                    numeric.clone(),
+                    bucket.clone(),
+                ]),
+                TypeSignature::Coercible(vec![
+                    duration.clone(),
+                    duration.clone(),
+                    duration.clone(),
+                    bucket.clone(),
+                ]),
+                TypeSignature::Coercible(vec![
+                    interval_ym.clone(),
+                    interval_ym.clone(),
+                    interval_ym.clone(),
+                    bucket.clone(),
+                ]),
+                TypeSignature::Coercible(vec![
+                    interval_mdn.clone(),
+                    interval_mdn.clone(),
+                    interval_mdn.clone(),
+                    bucket.clone(),
+                ]),
+            ],
+            Immutable,
+        )
+        .with_parameter_names(vec!["expr", "min", "max", "num_buckets"])
+        .expect("valid parameter names");
         Self {
-            signature: Signature::user_defined(Immutable),
+            signature: type_signature,
         }
     }
 }
@@ -88,63 +145,6 @@ impl ScalarUDFImpl for SparkWidthBucket {
             Ok(SortProperties::default())
         }
     }
-
-    fn coerce_types(&self, types: &[DataType]) -> Result<Vec<DataType>> {
-        use DataType::*;
-
-        let (v, lo, hi, n) = (&types[0], &types[1], &types[2], &types[3]);
-
-        match (v, lo, hi, n) {
-            (a, b, c, &(Int8 | Int16 | Int32 | Int64))
-                if is_signed_numeric(a)
-                    && is_signed_numeric(b)
-                    && is_signed_numeric(c) =>
-            {
-                Ok(vec![Float64, Float64, Float64, Int32])
-            }
-            (
-                &Duration(_),
-                &Duration(_),
-                &Duration(_),
-                &(Int8 | Int16 | Int32 | Int64),
-            ) => Ok(vec![
-                Duration(Microsecond),
-                Duration(Microsecond),
-                Duration(Microsecond),
-                Int32,
-            ]),
-            (
-                &Interval(MonthDayNano),
-                &Interval(MonthDayNano),
-                &Interval(MonthDayNano),
-                &(Int8 | Int16 | Int32 | Int64),
-            ) => Ok(vec![
-                Interval(MonthDayNano),
-                Interval(MonthDayNano),
-                Interval(MonthDayNano),
-                Int32,
-            ]),
-            (
-                &Interval(YearMonth),
-                &Interval(YearMonth),
-                &Interval(YearMonth),
-                &(Int8 | Int16 | Int32 | Int64),
-            ) => Ok(vec![
-                Interval(YearMonth),
-                Interval(YearMonth),
-                Interval(YearMonth),
-                Int32,
-            ]),
-
-            _ => exec_err!(
-                "width_bucket expects a numeric argument, got {} {} {} {}",
-                types[0],
-                types[1],
-                types[2],
-                types[3]
-            ),
-        }
-    }
 }
 
 fn width_bucket_kern(args: &[ArrayRef]) -> Result<ArrayRef> {
@@ -182,20 +182,18 @@ fn width_bucket_kern(args: &[ArrayRef]) -> Result<ArrayRef> {
             let min = as_interval_mdn_array(minv)?;
             let max = as_interval_mdn_array(maxv)?;
             let n_bucket = as_int32_array(nb)?;
-            Ok(Arc::new(width_bucket_interval_mdn_exact(v, min, max, n_bucket)))
+            Ok(Arc::new(width_bucket_interval_mdn_exact(
+                v, min, max, n_bucket,
+            )))
         }
 
-
-        other => Err(unsupported_data_types_exec_err(
-            "width_bucket",
-            "Float/Decimal OR Duration OR Interval(YearMonth) for first 3 args; Int for 4th",
-            &[
-                other.clone(),
-                minv.data_type().clone(),
-                maxv.data_type().clone(),
-                nb.data_type().clone(),
-            ],
-        )),
+        other => internal_err!(
+            "width_bucket received unexpected data types: {:?}, {:?}, {:?}, {:?}",
+            other,
+            minv.data_type(),
+            maxv.data_type(),
+            nb.data_type()
+        ),
     }
 }
 
@@ -780,8 +778,7 @@ mod tests {
         let err = width_bucket_kern(&[v, lo, hi, n]).unwrap_err();
         let msg = format!("{err}");
         assert!(
-            msg.contains("unsupported data types")
-                || msg.contains("Float/Decimal OR Duration OR Interval(YearMonth)"),
+            msg.contains("width_bucket received unexpected data types"),
             "unexpected error: {msg}"
         );
     }