0lai0 commented on code in PR #5193:
URL: https://github.com/apache/datafusion-comet/pull/5193#discussion_r3699252707
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native/spark-expr/src/math_funcs/internal/make_decimal.rs:
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@@ -45,14 +47,41 @@ pub fn spark_make_decimal(
ColumnarValue::Array(a) => match a.data_type() {
DataType::Int64 => {
let arr = a.as_primitive::<Int64Type>();
- let mut result = Decimal128Builder::new();
- for v in arr.into_iter() {
- result.append_option(long_to_decimal(v, precision, scale,
fail_on_error)?)
- }
let result_type = DataType::Decimal128(precision, scale);
+ // The Int64 is already the unscaled Decimal128 value, so we
only reinterpret
+ // the bits (an Arrow Int64->Decimal cast would rescale the
value). Both arity
+ // helpers reuse the input null buffer and only invoke the
closure on valid rows.
+ let result: Decimal128Array = if fail_on_error {
Review Comment:
WIP
### `make_decimal` benchmark (8192 rows, target `Decimal128(18, 2)`)
Time per call (Criterion median). Lower is better.
| case | `main` (per-row loop) | `unary_opt` / `try_unary` | `unary` + scan
| speedup (main → best) |
|---|---|---|---|---|
| no nulls | 32.38 µs | 14.24 µs | TBD | TBD |
| sparse nulls (~10%) | 35.84 µs | 16.40 µs | TBD | TBD |
| dense nulls (~50%) | 35.44 µs | 10.41 µs | TBD | TBD |
| ansi no nulls | 31.81 µs | 21.61 µs | TBD | TBD |
| ansi sparse nulls (~10%) | 34.68 µs | 21.00 µs | TBD | TBD |
| ansi dense nulls (~50%) | 35.39 µs | 12.84 µs | TBD | TBD |
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