jorisvandenbossche commented on issue #40874:
URL: https://github.com/apache/arrow/issues/40874#issuecomment-2025511001
Looking into the inner loop in both Arrow and numpy, it seems to be quite
similar. In numpy, almost all time is spent in
`_aligned_contig_cast_long_to_double`, which essentially boils down to:
```c
npy_intp N = dimensions[0];
char *src = args[0], *dst = args[1];
while (N--) {
*(npy_double *)dst = ((npy_double)(*(npy_long *)src));
dst += sizeof(npy_double);
src += sizeof(npy_long);
}
```
and in Arrow, almost all time is spent in `CastPrimitive`, which essentially
does:
https://github.com/apache/arrow/blob/cf832b8b5dd91ca1b70519fa544f0a44ebdb3bce/cpp/src/arrow/compute/kernels/scalar_cast_internal.cc#L40-L46
Anybody any insight in why our templated C++ code is so much slower than
numpy's C code? Logically it looks very similar, or would there be something in
our code that prevents optimizations?
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