mbutrovich commented on code in PR #1169:
URL: https://github.com/apache/datafusion-comet/pull/1169#discussion_r1887706616


##########
native/spark-expr/src/cast.rs:
##########
@@ -642,70 +872,66 @@ fn cast_array(
     let eval_mode = cast_options.eval_mode;
 
     let cast_result = match (from_type, to_type) {
-        (DataType::Utf8, DataType::Boolean) => 
spark_cast_utf8_to_boolean::<i32>(&array, eval_mode),
-        (DataType::LargeUtf8, DataType::Boolean) => {
-            spark_cast_utf8_to_boolean::<i64>(&array, eval_mode)
-        }
-        (DataType::Utf8, DataType::Timestamp(_, _)) => {
+        (Utf8, Boolean) => spark_cast_utf8_to_boolean::<i32>(&array, 
eval_mode),
+        (LargeUtf8, Boolean) => spark_cast_utf8_to_boolean::<i64>(&array, 
eval_mode),
+        (Utf8, Timestamp(_, _)) => {
             cast_string_to_timestamp(&array, to_type, eval_mode, 
&cast_options.timezone)
         }
-        (DataType::Utf8, DataType::Date32) => cast_string_to_date(&array, 
to_type, eval_mode),
-        (DataType::Int64, DataType::Int32)
-        | (DataType::Int64, DataType::Int16)
-        | (DataType::Int64, DataType::Int8)
-        | (DataType::Int32, DataType::Int16)
-        | (DataType::Int32, DataType::Int8)
-        | (DataType::Int16, DataType::Int8)
+        (Utf8, Date32) => cast_string_to_date(&array, to_type, eval_mode),
+        (Int64, Int32)
+        | (Int64, Int16)
+        | (Int64, Int8)
+        | (Int32, Int16)
+        | (Int32, Int8)
+        | (Int16, Int8)
             if eval_mode != EvalMode::Try =>
         {
             spark_cast_int_to_int(&array, eval_mode, from_type, to_type)
         }
-        (DataType::Utf8, DataType::Int8 | DataType::Int16 | DataType::Int32 | 
DataType::Int64) => {
+        (Utf8, Int8 | Int16 | Int32 | Int64) => {
             cast_string_to_int::<i32>(to_type, &array, eval_mode)
         }
-        (
-            DataType::LargeUtf8,
-            DataType::Int8 | DataType::Int16 | DataType::Int32 | 
DataType::Int64,
-        ) => cast_string_to_int::<i64>(to_type, &array, eval_mode),
-        (DataType::Float64, DataType::Utf8) => 
spark_cast_float64_to_utf8::<i32>(&array, eval_mode),
-        (DataType::Float64, DataType::LargeUtf8) => {
-            spark_cast_float64_to_utf8::<i64>(&array, eval_mode)
-        }
-        (DataType::Float32, DataType::Utf8) => 
spark_cast_float32_to_utf8::<i32>(&array, eval_mode),
-        (DataType::Float32, DataType::LargeUtf8) => {
-            spark_cast_float32_to_utf8::<i64>(&array, eval_mode)
-        }
-        (DataType::Float32, DataType::Decimal128(precision, scale)) => {
+        (LargeUtf8, Int8 | Int16 | Int32 | Int64) => {
+            cast_string_to_int::<i64>(to_type, &array, eval_mode)
+        }
+        (Float64, Utf8) => spark_cast_float64_to_utf8::<i32>(&array, 
eval_mode),
+        (Float64, LargeUtf8) => spark_cast_float64_to_utf8::<i64>(&array, 
eval_mode),
+        (Float32, Utf8) => spark_cast_float32_to_utf8::<i32>(&array, 
eval_mode),
+        (Float32, LargeUtf8) => spark_cast_float32_to_utf8::<i64>(&array, 
eval_mode),
+        (Float32, Decimal128(precision, scale)) => {
             cast_float32_to_decimal128(&array, *precision, *scale, eval_mode)
         }
-        (DataType::Float64, DataType::Decimal128(precision, scale)) => {
+        (Float64, Decimal128(precision, scale)) => {
             cast_float64_to_decimal128(&array, *precision, *scale, eval_mode)
         }
-        (DataType::Float32, DataType::Int8)
-        | (DataType::Float32, DataType::Int16)
-        | (DataType::Float32, DataType::Int32)
-        | (DataType::Float32, DataType::Int64)
-        | (DataType::Float64, DataType::Int8)
-        | (DataType::Float64, DataType::Int16)
-        | (DataType::Float64, DataType::Int32)
-        | (DataType::Float64, DataType::Int64)
-        | (DataType::Decimal128(_, _), DataType::Int8)
-        | (DataType::Decimal128(_, _), DataType::Int16)
-        | (DataType::Decimal128(_, _), DataType::Int32)
-        | (DataType::Decimal128(_, _), DataType::Int64)
+        (Float32, Int8)
+        | (Float32, Int16)
+        | (Float32, Int32)
+        | (Float32, Int64)
+        | (Float64, Int8)
+        | (Float64, Int16)
+        | (Float64, Int32)
+        | (Float64, Int64)
+        | (Decimal128(_, _), Int8)
+        | (Decimal128(_, _), Int16)
+        | (Decimal128(_, _), Int32)
+        | (Decimal128(_, _), Int64)
             if eval_mode != EvalMode::Try =>
         {
             spark_cast_nonintegral_numeric_to_integral(&array, eval_mode, 
from_type, to_type)
         }
-        (DataType::Struct(_), DataType::Utf8) => {
-            Ok(casts_struct_to_string(array.as_struct(), cast_options)?)
-        }
-        (DataType::Struct(_), DataType::Struct(_)) => Ok(cast_struct_to_struct(
+        (Struct(_), Utf8) => Ok(casts_struct_to_string(array.as_struct(), 
cast_options)?),
+        (Struct(_), Struct(_)) => Ok(cast_struct_to_struct(
             array.as_struct(),
             from_type,
             to_type,
             cast_options,
         )?),
+        (UInt8 | UInt16 | UInt32 | UInt64, Int8 | Int16 | Int32 | Int64)
+            if cast_options.allow_cast_unsigned_ints =>
+        {
+            Ok(cast_with_options(&array, to_type, &CAST_OPTIONS)?)

Review Comment:
   We'll probably need to split this logic out from cast.rs in the future, but 
basically we need to handle types coming out of Parquet that then get converted 
to Arrow types. I think the logic can actually be different than Spark's 
casting rules.



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