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Split up unique_count.cu to improve build time (#13169)
Moves the `column_view` overload out of `cpp/src/stream_compaction/unique_count.cu` and into the new file `cpp/src/stream_compaction/unique_count_column.cu` to help improve overall build time. Compiling these two in parallel roughly speeds up their build time by 2x. The `unique_count.cu` is one of the files that takes over 20 minutes to build in CI. Also cleaned up much of the include statements. Authors: - David Wendt (https://github.com/davidwendt) Approvers: - Vyas Ramasubramani (https://github.com/vyasr) - Vukasin Milovanovic (https://github.com/vuule) URL: #13169
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * Copyright (c) 2023, 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. | ||
| */ | ||
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| #include <cudf/column/column_device_view.cuh> | ||
| #include <cudf/column/column_factories.hpp> | ||
| #include <cudf/column/column_view.hpp> | ||
| #include <cudf/detail/nvtx/ranges.hpp> | ||
| #include <cudf/detail/stream_compaction.hpp> | ||
| #include <cudf/stream_compaction.hpp> | ||
| #include <cudf/table/experimental/row_operators.cuh> | ||
| #include <cudf/table/table_view.hpp> | ||
| #include <cudf/utilities/default_stream.hpp> | ||
| #include <cudf/utilities/type_dispatcher.hpp> | ||
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| #include <rmm/cuda_stream_view.hpp> | ||
| #include <rmm/exec_policy.hpp> | ||
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| #include <thrust/count.h> | ||
| #include <thrust/execution_policy.h> | ||
| #include <thrust/iterator/counting_iterator.h> | ||
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| #include <cmath> | ||
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| namespace cudf { | ||
| namespace detail { | ||
| namespace { | ||
| /** | ||
| * @brief A functor to be used along with device type_dispatcher to check if | ||
| * the row `index` of `column_device_view` is `NaN`. | ||
| */ | ||
| struct check_nan { | ||
| // Check if a value is `NaN` for floating point type columns | ||
| template <typename T, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr> | ||
| __device__ inline bool operator()(column_device_view const& input, size_type index) | ||
| { | ||
| return std::isnan(input.data<T>()[index]); | ||
| } | ||
| // Non-floating point type columns can never have `NaN`, so it will always return false. | ||
| template <typename T, std::enable_if_t<not std::is_floating_point_v<T>>* = nullptr> | ||
| __device__ inline bool operator()(column_device_view const&, size_type) | ||
| { | ||
| return false; | ||
| } | ||
| }; | ||
| } // namespace | ||
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| cudf::size_type unique_count(column_view const& input, | ||
| null_policy null_handling, | ||
| nan_policy nan_handling, | ||
| rmm::cuda_stream_view stream) | ||
| { | ||
| auto const num_rows = input.size(); | ||
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| if (num_rows == 0 or num_rows == input.null_count()) { return 0; } | ||
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| auto const count_nulls = null_handling == null_policy::INCLUDE; | ||
| auto const nan_is_null = nan_handling == nan_policy::NAN_IS_NULL; | ||
| auto const should_check_nan = cudf::is_floating_point(input.type()); | ||
| auto input_device_view = cudf::column_device_view::create(input, stream); | ||
| auto device_view = *input_device_view; | ||
| auto input_table_view = table_view{{input}}; | ||
| auto table_ptr = cudf::table_device_view::create(input_table_view, stream); | ||
| row_equality_comparator comp(nullate::DYNAMIC{cudf::has_nulls(input_table_view)}, | ||
| *table_ptr, | ||
| *table_ptr, | ||
| null_equality::EQUAL); | ||
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| return thrust::count_if( | ||
| rmm::exec_policy(stream), | ||
| thrust::counting_iterator<cudf::size_type>(0), | ||
| thrust::counting_iterator<cudf::size_type>(num_rows), | ||
| [count_nulls, nan_is_null, should_check_nan, device_view, comp] __device__(cudf::size_type i) { | ||
| auto const is_null = device_view.is_null(i); | ||
| auto const is_nan = nan_is_null and should_check_nan and | ||
| cudf::type_dispatcher(device_view.type(), check_nan{}, device_view, i); | ||
| if (not count_nulls and (is_null or (nan_is_null and is_nan))) { return false; } | ||
| if (i == 0) { return true; } | ||
| if (count_nulls and nan_is_null and (is_nan or is_null)) { | ||
| auto const prev_is_nan = | ||
| should_check_nan and | ||
| cudf::type_dispatcher(device_view.type(), check_nan{}, device_view, i - 1); | ||
| return not(prev_is_nan or device_view.is_null(i - 1)); | ||
| } | ||
| return not comp(i, i - 1); | ||
| }); | ||
| } | ||
| } // namespace detail | ||
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| cudf::size_type unique_count(column_view const& input, | ||
| null_policy null_handling, | ||
| nan_policy nan_handling) | ||
| { | ||
| CUDF_FUNC_RANGE(); | ||
| return detail::unique_count(input, null_handling, nan_handling, cudf::get_default_stream()); | ||
| } | ||
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| } // namespace cudf |