[GitHub] [arrow] westonpace commented on a diff in pull request #12590: ARROW-15639 [C++][Python] UDF Scalar Function Implementation

[GitBox <gi...@apache.org>]

westonpace commented on code in PR #12590:
URL: https://github.com/apache/arrow/pull/12590#discussion_r842180632


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cpp/src/arrow/python/udf.h:
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@@ -0,0 +1,106 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#pragma once
+
+#include "arrow/python/platform.h"
+
+#include <cstdint>
+#include <memory>
+
+#include "arrow/compute/api_scalar.h"
+#include "arrow/compute/cast.h"
+#include "arrow/compute/exec.h"
+#include "arrow/compute/function.h"
+#include "arrow/compute/registry.h"
+#include "arrow/datum.h"
+#include "arrow/util/cpu_info.h"
+#include "arrow/util/logging.h"
+
+#include "arrow/python/common.h"
+#include "arrow/python/pyarrow.h"
+#include "arrow/python/visibility.h"
+
+namespace arrow {
+
+namespace py {
+
+// Exposing the UDFOptions: https://issues.apache.org/jira/browse/ARROW-16041
+class ARROW_PYTHON_EXPORT UdfOptions {
+ public:
+  UdfOptions(const compute::Function::Kind kind, const compute::Arity arity,
+             const compute::FunctionDoc func_doc,
+             const std::vector<compute::InputType> in_types,
+             const compute::OutputType out_type)
+      : kind_(kind),
+        arity_(arity),
+        func_doc_(func_doc),
+        in_types_(in_types),
+        out_type_(out_type) {}
+
+  compute::Function::Kind kind() { return kind_; }
+
+  const compute::Arity& arity() const { return arity_; }
+
+  const compute::FunctionDoc doc() const { return func_doc_; }
+
+  const std::vector<compute::InputType>& input_types() const { return in_types_; }
+
+  const compute::OutputType& output_type() const { return out_type_; }
+
+ private:
+  compute::Function::Kind kind_;
+  compute::Arity arity_;
+  const compute::FunctionDoc func_doc_;
+  std::vector<compute::InputType> in_types_;
+  compute::OutputType out_type_;
+};
+
+class ARROW_PYTHON_EXPORT ScalarUdfOptions : public UdfOptions {
+ public:
+  ScalarUdfOptions(const std::string func_name, const compute::Arity arity,
+                   const compute::FunctionDoc func_doc,
+                   const std::vector<compute::InputType> in_types,
+                   const compute::OutputType out_type)
+      : UdfOptions(compute::Function::SCALAR, arity, func_doc, in_types, out_type),
+        func_name_(func_name) {}

Review Comment:
   An "aggregate UDF" will have three "functions", "Init", "Update", and "Merge" (or something like that).  However, arity might not make sense for an aggregate UDF (I would think they'd all be unary).
   
   Maybe, instead of trying to predict what shape things will take right now, we can just have one class and call it `ScalarUdfOptions`.  Then we can introduce a base class and concrete subclasses once we actually have two instances.



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