rdavis120 commented on issue #35604:
URL: https://github.com/apache/arrow/issues/35604#issuecomment-1553215854
Ok thanks, I think this works.
The reason to convert the columns to a struct was that since a udf can
support up to three argument, we can get around this by converting a table with
>3 columns to a struct, and then passing the struct as an argument to the udf,
which is before the collect().
library(arrow)
#
arrow::register_scalar_function(
"sum2",
function(context, x) {
rowSums(x, na.rm = T)
},
in_type = schema(x = struct(Sepal.Length = float64(), Sepal.Width =
float64(), Petal.Length = float64(), Petal.Width = float64())),
out_type = float64(),
auto_convert = T
)
#
arrow::write_dataset(iris, path = "iris.parquet")
x <- arrow::open_dataset("iris.parquet")
x |>
dplyr::mutate(x = data.frame(Sepal.Length, Sepal.Width, Petal.Length,
Petal.Width), .keep = "none") |>
dplyr::mutate(sum2 = sum2(x), .keep = "none") |>
dplyr::collect()
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