tlm365 commented on code in PR #12909:
URL: https://github.com/apache/datafusion/pull/12909#discussion_r1798363818
##########
datafusion/functions/src/math/trunc.rs:
##########
@@ -111,44 +111,66 @@ fn trunc(args: &[ArrayRef]) -> Result<ArrayRef> {
);
}
- //if only one arg then invoke toolchain trunc(num) and precision = 0 by
default
- //or then invoke the compute_truncate method to process precision
+ // If only one arg then invoke toolchain trunc(num) and precision = 0 by
default
+ // or then invoke the compute_truncate method to process precision
let num = &args[0];
let precision = if args.len() == 1 {
ColumnarValue::Scalar(Int64(Some(0)))
} else {
ColumnarValue::Array(Arc::clone(&args[1]))
};
- match args[0].data_type() {
+ match num.data_type() {
Float64 => match precision {
- ColumnarValue::Scalar(Int64(Some(0))) => Ok(Arc::new(
- make_function_scalar_inputs!(num, "num", Float64Array, {
f64::trunc }),
- ) as ArrayRef),
- ColumnarValue::Array(precision) =>
Ok(Arc::new(make_function_inputs2!(
- num,
- precision,
- "x",
- "y",
- Float64Array,
- Int64Array,
- { compute_truncate64 }
- )) as ArrayRef),
+ ColumnarValue::Scalar(Int64(Some(0))) => {
+ Ok(Arc::new(
+ args[0]
+ .as_primitive::<Float64Type>()
+ .unary::<_, Float64Type>(|x: f64| {
+ if x == 0_f64 {
+ 0_f64
+ } else {
+ x.trunc()
+ }
+ }),
+ ) as ArrayRef)
+ }
+ ColumnarValue::Array(precision) => {
+ let num_array = num.as_primitive::<Float64Type>();
+ let precision_array = precision.as_primitive::<Int64Type>();
+ let result: PrimitiveArray<Float64Type> =
+ arrow_arith::arity::binary(num_array, precision_array, |x,
y| {
+ compute_truncate64(x, y)
+ })?;
+
+ Ok(Arc::new(result) as ArrayRef)
+ }
_ => exec_err!("trunc function requires a scalar or array for
precision"),
},
Float32 => match precision {
- ColumnarValue::Scalar(Int64(Some(0))) => Ok(Arc::new(
- make_function_scalar_inputs!(num, "num", Float32Array, {
f32::trunc }),
- ) as ArrayRef),
- ColumnarValue::Array(precision) =>
Ok(Arc::new(make_function_inputs2!(
- num,
- precision,
- "x",
- "y",
- Float32Array,
- Int64Array,
- { compute_truncate32 }
- )) as ArrayRef),
+ ColumnarValue::Scalar(Int64(Some(0))) => {
+ Ok(Arc::new(
+ args[0]
+ .as_primitive::<Float32Type>()
+ .unary::<_, Float32Type>(|x: f32| {
+ if x == 0_f32 {
+ 0_f32
+ } else {
+ x.trunc()
+ }
+ }),
+ ) as ArrayRef)
+ }
+ ColumnarValue::Array(precision) => {
+ let num_array = num.as_primitive::<Float32Type>();
+ let precision_array = precision.as_primitive::<Int64Type>();
+ let result: PrimitiveArray<Float32Type> =
+ arrow_arith::arity::binary(num_array, precision_array, |x,
y| {
Review Comment:
@simonvandel Thanks so much for reviewing
> Is this the same function as this?
https://docs.rs/arrow/latest/arrow/compute/fn.binary.html
Oh, yes it is. Nice!
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org
For additional commands, e-mail: github-h...@datafusion.apache.org
