rolling.hpp

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/*
 * Copyright (c) 2019-2025, NVIDIA CORPORATION.
 *
 * Licensed 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 <cudf/aggregation.hpp>
#include <cudf/rolling/range_window_bounds.hpp>
#include <cudf/types.hpp>
#include <cudf/utilities/default_stream.hpp>
#include <cudf/utilities/export.hpp>
#include <cudf/utilities/memory_resource.hpp>
 
#include <rmm/resource_ref.hpp>
 
#include <memory>
#include <optional>
#include <variant>
 
namespace CUDF_EXPORT cudf {
struct bounded_closed {
  cudf::scalar const& delta_;  
 
  cudf::scalar const* delta() const noexcept { return &delta_; }
};
 
struct bounded_open {
  cudf::scalar const& delta_;  
 
  cudf::scalar const* delta() const noexcept { return &delta_; }
};
 
struct unbounded {
  constexpr cudf::scalar const* delta() const noexcept { return nullptr; }
};
struct current_row {
  constexpr cudf::scalar const* delta() const noexcept { return nullptr; }
};
 
using range_window_type = std::variant<unbounded, current_row, bounded_closed, bounded_open>;
 
std::pair<std::unique_ptr<column>, std::unique_ptr<column>> make_range_windows(
  table_view const& group_keys,
  column_view const& orderby,
  order order,
  null_order null_order,
  range_window_type preceding,
  range_window_type following,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> rolling_window(
  column_view const& input,
  size_type preceding_window,
  size_type following_window,
  size_type min_periods,
  rolling_aggregation const& agg,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> rolling_window(
  column_view const& input,
  column_view const& default_outputs,
  size_type preceding_window,
  size_type following_window,
  size_type min_periods,
  rolling_aggregation const& agg,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
struct window_bounds {
 public:
  static window_bounds get(size_type value) { return window_bounds(false, value); }
 
  static window_bounds unbounded()
  {
    return window_bounds(true, std::numeric_limits<cudf::size_type>::max());
  }
 
  [[nodiscard]] bool is_unbounded() const { return _is_unbounded; }
 
  [[nodiscard]] size_type value() const { return _value; }
 
 private:
  explicit window_bounds(bool is_unbounded_, size_type value_ = 0)
    : _is_unbounded{is_unbounded_}, _value{value_}
  {
  }
 
  bool const _is_unbounded;  
  size_type const _value;    
};
 
std::unique_ptr<column> grouped_rolling_window(
  table_view const& group_keys,
  column_view const& input,
  size_type preceding_window,
  size_type following_window,
  size_type min_periods,
  rolling_aggregation const& aggr,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> grouped_rolling_window(
  table_view const& group_keys,
  column_view const& input,
  window_bounds preceding_window,
  window_bounds following_window,
  size_type min_periods,
  rolling_aggregation const& aggr,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> grouped_rolling_window(
  table_view const& group_keys,
  column_view const& input,
  column_view const& default_outputs,
  size_type preceding_window,
  size_type following_window,
  size_type min_periods,
  rolling_aggregation const& aggr,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> grouped_rolling_window(
  table_view const& group_keys,
  column_view const& input,
  column_view const& default_outputs,
  window_bounds preceding_window,
  window_bounds following_window,
  size_type min_periods,
  rolling_aggregation const& aggr,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> grouped_range_rolling_window(
  table_view const& group_keys,
  column_view const& orderby_column,
  cudf::order const& order,
  column_view const& input,
  range_window_bounds const& preceding,
  range_window_bounds const& following,
  size_type min_periods,
  rolling_aggregation const& aggr,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
 
std::unique_ptr<column> rolling_window(
  column_view const& input,
  column_view const& preceding_window,
  column_view const& following_window,
  size_type min_periods,
  rolling_aggregation const& agg,
  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
  rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());
  // end of group
}  // namespace CUDF_EXPORT cudf