Optimize performance of math::trunc (~2.5x faster)
#12909
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simonvandel
reviewed
Oct 13, 2024
| 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| { |
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Is this the same function as this? https://docs.rs/arrow/latest/arrow/compute/fn.binary.html
If so you could remove the new dependency (although it is in the dependency closure anyway already)
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@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!
Signed-off-by: Tai Le Manh <[email protected]>
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tlm365
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math::trunc (~2.5x faster)
alamb
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Oct 15, 2024
findepi
reviewed
Oct 15, 2024
| 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!( |
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I've broadened #12923 to cover this too
|
I merged up from main to resolve a conflict on this branch |
|
🚀 thanks again |
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Rationale for this change
Same idea as #12881. Using the
unary/binaryfunctions allow faster processing (most likely auto-vectorized code) by avoiding branching on nulls.What changes are included in this PR?
unaryandbinaryAre these changes tested?
Existing testcases.
Are there any user-facing changes?
No.
**BENCHMARK RESULT
