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Merge branch 'branch-24.08' into pylibcudf-io-writers
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@lithomas1
lithomas1 authored Jun 18, 2024
2 parents e0901dd + dcc153b commit d22953f
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Showing 24 changed files with 749 additions and 360 deletions.
10 changes: 6 additions & 4 deletions cpp/benchmarks/join/conditional_join.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,8 @@

#include "join_common.hpp"

auto const CONDITIONAL_JOIN_SIZE_RANGE = std::vector<nvbench::int64_t>{1000, 100'000};

template <typename Key, bool Nullable>
void nvbench_conditional_inner_join(nvbench::state& state,
nvbench::type_list<Key, nvbench::enum_type<Nullable>>)
Expand Down Expand Up @@ -46,12 +48,12 @@ NVBENCH_BENCH_TYPES(nvbench_conditional_inner_join,
NVBENCH_TYPE_AXES(JOIN_KEY_TYPE_RANGE, JOIN_NULLABLE_RANGE))
.set_name("conditional_inner_join")
.set_type_axes_names({"Key", "Nullable"})
.add_int64_axis("left_size", JOIN_SIZE_RANGE)
.add_int64_axis("right_size", JOIN_SIZE_RANGE);
.add_int64_axis("left_size", CONDITIONAL_JOIN_SIZE_RANGE)
.add_int64_axis("right_size", CONDITIONAL_JOIN_SIZE_RANGE);

NVBENCH_BENCH_TYPES(nvbench_conditional_left_join,
NVBENCH_TYPE_AXES(JOIN_KEY_TYPE_RANGE, JOIN_NULLABLE_RANGE))
.set_name("conditional_left_join")
.set_type_axes_names({"Key", "Nullable"})
.add_int64_axis("left_size", JOIN_SIZE_RANGE)
.add_int64_axis("right_size", JOIN_SIZE_RANGE);
.add_int64_axis("left_size", CONDITIONAL_JOIN_SIZE_RANGE)
.add_int64_axis("right_size", CONDITIONAL_JOIN_SIZE_RANGE);
20 changes: 20 additions & 0 deletions cpp/include/cudf/rolling.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@ namespace cudf {
* @param[in] min_periods Minimum number of observations in window required to have a value,
* otherwise element `i` is null.
* @param[in] agg The rolling window aggregation type (SUM, MAX, MIN, etc.)
* @param[in] stream CUDA stream used for device memory operations and kernel launches
* @param[in] mr Device memory resource used to allocate the returned column's device memory
*
* @returns A nullable output column containing the rolling window results
Expand All @@ -67,6 +68,7 @@ std::unique_ptr<column> rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand All @@ -77,6 +79,7 @@ std::unique_ptr<column> rolling_window(
* size_type following_window,
* size_type min_periods,
* rolling_aggregation const& agg,
* rmm::cuda_stream_view stream,
* rmm::device_async_resource_ref mr)
*
* @param default_outputs A column of per-row default values to be returned instead
Expand All @@ -90,6 +93,7 @@ std::unique_ptr<column> rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand Down Expand Up @@ -227,6 +231,7 @@ struct window_bounds {
* @param[in] min_periods Minimum number of observations in window required to have a value,
* otherwise element `i` is null.
* @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.)
* @param[in] stream CUDA stream used for device memory operations and kernel launches
* @param[in] mr Device memory resource used to allocate the returned column's device memory
*
* @returns A nullable output column containing the rolling window results
Expand All @@ -238,6 +243,7 @@ std::unique_ptr<column> grouped_rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand All @@ -249,6 +255,7 @@ std::unique_ptr<column> grouped_rolling_window(
* size_type following_window,
* size_type min_periods,
* rolling_aggregation const& aggr,
* rmm::cuda_stream_view stream,
* rmm::device_async_resource_ref mr)
*/
std::unique_ptr<column> grouped_rolling_window(
Expand All @@ -258,6 +265,7 @@ std::unique_ptr<column> grouped_rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand All @@ -269,6 +277,7 @@ std::unique_ptr<column> grouped_rolling_window(
* size_type following_window,
* size_type min_periods,
* rolling_aggregation const& aggr,
* rmm::cuda_stream_view stream,,
* rmm::device_async_resource_ref mr)
*
* @param default_outputs A column of per-row default values to be returned instead
Expand All @@ -283,6 +292,7 @@ std::unique_ptr<column> grouped_rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand All @@ -295,6 +305,7 @@ std::unique_ptr<column> grouped_rolling_window(
* size_type following_window,
* size_type min_periods,
* rolling_aggregation const& aggr,
* rmm::cuda_stream_view stream,
* rmm::device_async_resource_ref mr)
*/
std::unique_ptr<column> grouped_rolling_window(
Expand All @@ -305,6 +316,7 @@ std::unique_ptr<column> grouped_rolling_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 = rmm::mr::get_current_device_resource());

/**
Expand Down Expand Up @@ -387,6 +399,7 @@ std::unique_ptr<column> grouped_rolling_window(
* @param[in] min_periods Minimum number of observations in window required to have a value,
* otherwise element `i` is null.
* @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.)
* @param[in] stream CUDA stream used for device memory operations and kernel launches
* @param[in] mr Device memory resource used to allocate the returned column's device memory
*
* @returns A nullable output column containing the rolling window results
Expand All @@ -400,6 +413,7 @@ std::unique_ptr<column> grouped_time_range_rolling_window(
size_type following_window_in_days,
size_type min_periods,
rolling_aggregation const& aggr,
rmm::cuda_stream_view stream = cudf::get_default_stream(),
rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource());

/**
Expand All @@ -415,6 +429,7 @@ std::unique_ptr<column> grouped_time_range_rolling_window(
* size_type following_window_in_days,
* size_type min_periods,
* rolling_aggregation const& aggr,
* rmm::cuda_stream_view stream,
* rmm::device_async_resource_ref mr)
*
* The `preceding_window_in_days` and `following_window_in_days` are specified as a `window_bounds`
Expand All @@ -429,6 +444,7 @@ std::unique_ptr<column> grouped_time_range_rolling_window(
window_bounds following_window_in_days,
size_type min_periods,
rolling_aggregation const& aggr,
rmm::cuda_stream_view stream = cudf::get_default_stream(),
rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource());

/**
Expand Down Expand Up @@ -536,6 +552,7 @@ std::unique_ptr<column> grouped_time_range_rolling_window(
* @param[in] min_periods Minimum number of observations in window required to have a value,
* otherwise element `i` is null.
* @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.)
* @param[in] stream CUDA stream used for device memory operations and kernel launches
* @param[in] mr Device memory resource used to allocate the returned column's device memory
*
* @returns A nullable output column containing the rolling window results
Expand All @@ -549,6 +566,7 @@ std::unique_ptr<column> grouped_range_rolling_window(
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 = rmm::mr::get_current_device_resource());

/**
Expand Down Expand Up @@ -582,6 +600,7 @@ std::unique_ptr<column> grouped_range_rolling_window(
* @param[in] min_periods Minimum number of observations in window required to have a value,
* otherwise element `i` is null.
* @param[in] agg The rolling window aggregation type (sum, max, min, etc.)
* @param[in] stream CUDA stream used for device memory operations and kernel launches
* @param[in] mr Device memory resource used to allocate the returned column's device memory
*
* @returns A nullable output column containing the rolling window results
Expand All @@ -592,6 +611,7 @@ std::unique_ptr<column> rolling_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 = rmm::mr::get_current_device_resource());

/** @} */ // end of group
Expand Down
16 changes: 12 additions & 4 deletions cpp/include/cudf/rolling/range_window_bounds.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -56,18 +56,22 @@ struct range_window_bounds {
* @brief Factory method to construct a bounded window boundary.
*
* @param boundary Finite window boundary
* @param stream CUDA stream used for device memory operations and kernel launches
* @return A bounded window boundary object
*/
static range_window_bounds get(scalar const& boundary);
static range_window_bounds get(scalar const& boundary,
rmm::cuda_stream_view stream = cudf::get_default_stream());

/**
* @brief Factory method to construct a window boundary
* limited to the value of the current row
*
* @param type The datatype of the window boundary
* @param stream CUDA stream used for device memory operations and kernel launches
* @return A "current row" window boundary object
*/
static range_window_bounds current_row(data_type type);
static range_window_bounds current_row(data_type type,
rmm::cuda_stream_view stream = cudf::get_default_stream());

/**
* @brief Whether or not the window is bounded to the current row
Expand All @@ -81,9 +85,11 @@ struct range_window_bounds {
* @brief Factory method to construct an unbounded window boundary.
*
* @param type The datatype of the window boundary
* @param stream CUDA stream used for device memory operations and kernel launches
* @return An unbounded window boundary object
*/
static range_window_bounds unbounded(data_type type);
static range_window_bounds unbounded(data_type type,
rmm::cuda_stream_view stream = cudf::get_default_stream());

/**
* @brief Whether or not the window is unbounded
Expand All @@ -107,7 +113,9 @@ struct range_window_bounds {
extent_type _extent{extent_type::UNBOUNDED};
std::shared_ptr<scalar> _range_scalar{nullptr}; // To enable copy construction/assignment.

range_window_bounds(extent_type extent_, std::unique_ptr<scalar> range_scalar_);
range_window_bounds(extent_type extent_,
std::unique_ptr<scalar> range_scalar_,
rmm::cuda_stream_view = cudf::get_default_stream());
};

/** @} */ // end of group
Expand Down
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