icexelloss commented on code in PR #35514:
URL: https://github.com/apache/arrow/pull/35514#discussion_r1221691124
##########
python/pyarrow/src/arrow/python/udf.cc:
##########
@@ -234,6 +351,56 @@ Status RegisterTabularFunction(PyObject* user_function,
UdfWrapperCallback wrapp
wrapper, options, registry);
}
+Status AddAggKernel(std::shared_ptr<compute::KernelSignature> sig,
compute::KernelInit init,
+ compute::ScalarAggregateFunction* func) {
+
+ compute::ScalarAggregateKernel kernel(std::move(sig), std::move(init),
AggregateUdfConsume, AggregateUdfMerge, AggregateUdfFinalize,
/*ordered=*/false);
+ RETURN_NOT_OK(func->AddKernel(std::move(kernel)));
+ return Status::OK();
+}
+
+Status RegisterAggregateFunction(PyObject* agg_function, UdfWrapperCallback
agg_wrapper,
+ const UdfOptions& options,
+ compute::FunctionRegistry*
registry) {
+ if (!PyCallable_Check(agg_function)) {
+ return Status::TypeError("Expected a callable Python object.");
+ }
+
+ if (registry == NULLPTR) {
+ registry = compute::GetFunctionRegistry();
+ }
+
+ static auto default_scalar_aggregate_options =
compute::ScalarAggregateOptions::Defaults();
+ auto aggregate_func = std::make_shared<compute::ScalarAggregateFunction>(
+ options.func_name, options.arity, options.func_doc,
&default_scalar_aggregate_options);
+
+ Py_INCREF(agg_function);
Review Comment:
I looked into this more and observed the following.
The refcount of Python function is 2 before registering with Arrow, and is 3
after registering. After invoking the function with arrow compute, the refcount
doesn't increase. (still 3) So I believe the code is correct.
On the other hand, I did observe scalar UDF might have a refcount leaking (I
observed the refcount increases by 1 after calling the function with arrow
compute). Which I can look into separately.
In summary, my understanding is that every time we wrap the PyObject* into a
OwnedRef, we need to increase the refcount by 1 so the refcount doesn't change
after the destructor of OwnedRef gets invoked. I am 90% certain this is correct
understanding of how it should work but happy to hear more thoughts @westonpace
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