SubhamSinghal commented on code in PR #20189:
URL: https://github.com/apache/datafusion/pull/20189#discussion_r2805221674
##########
datafusion/spark/src/function/math/negative.rs:
##########
@@ -96,37 +95,80 @@ impl ScalarUDFImpl for SparkNegative {
}
fn invoke_with_args(&self, args: ScalarFunctionArgs) ->
Result<ColumnarValue> {
- spark_negative(&args.args)
+ spark_negative(&args.args,
args.config_options.execution.enable_ansi_mode)
}
}
/// Core implementation of Spark's negative function
-fn spark_negative(args: &[ColumnarValue]) -> Result<ColumnarValue> {
+fn spark_negative(
+ args: &[ColumnarValue],
+ enable_ansi_mode: bool,
+) -> Result<ColumnarValue> {
let [arg] = take_function_args("negative", args)?;
match arg {
ColumnarValue::Array(array) => match array.data_type() {
DataType::Null => Ok(arg.clone()),
- // Signed integers - use wrapping negation (Spark legacy mode
behavior)
+ // Signed integers - use checked negation in ANSI mode, wrapping
in legacy mode
DataType::Int8 => {
let array = array.as_primitive::<Int8Type>();
- let result: PrimitiveArray<Int8Type> = array.unary(|x|
x.wrapping_neg());
+ let result: PrimitiveArray<Int8Type> = if enable_ansi_mode {
+ array.try_unary(|x| {
+ x.checked_neg().ok_or_else(|| {
+ ArrowError::ComputeError(format!(
Review Comment:
@comphead I was looking at
[this](https://github.com/apache/datafusion/blob/main/datafusion/spark/src/function/math/abs.rs#L100)
which throw Arrow::ComputeError. Do we need to throw `exec_err! `instead?
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