Ben Kietzman created ARROW-17446:
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Summary: [R] Allow unrecognized R expressions to be callable as
compute::Functions
Key: ARROW-17446
URL: https://issues.apache.org/jira/browse/ARROW-17446
Project: Apache Arrow
Issue Type: Bug
Components: R
Reporter: Ben Kietzman
Currently, if an R expression is not entirely supported by the arrow compute
engine, the entire input will be pulled into memory for native R to operate on.
It would be possible to instead provide add a custom compute function to the
registry (inside {{R_init_arrow}}, probably) which evaluates any sub
expressions which couldn't be translated to native arrow compute expressions.
This would for example allow a filter expression including a call to an R
function {{baz}} to evaluate on a dataset larger than memory and with predicate
and projection pushdown as normal using the expressions which *are*
translatable. The resulting expression might look something like this in c++:
{code}
call("and_kleene", {
call("greater", {field_ref("a"), scalar(1)}),
call("r_expr", {field_ref("b")},
/*options=*/RexprOptions{cpp11::function(baz_sexp)}),
});
{code}
In this case although the "r_expr" function is opaque to compute and datasets,
we would still recognize that only fields "a" and "b" need to be materialized.
Furthermore, the first member of the filter's conjunction is {{a > 1}}, which
*is* translatable and could be used for predicate pushdown, for checking
against parquet statistics, etc.
Since R is not multithreaded, the compute function would need to take a global
lock to ensure only a single thread of R execution. This might be untenable
since it would also lock the interpreter. Still, it seems like a worthwhile
option to consider
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