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Remove UNKNOWN_NULL_COUNT #13372

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May 24, 2023
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17 changes: 0 additions & 17 deletions cpp/include/cudf/column/column_view.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -160,11 +160,6 @@ class column_view_base {
/**
* @brief Returns the count of null elements
*
* @note If the column was constructed with `UNKNOWN_NULL_COUNT`, or if at any
* point `set_null_count(UNKNOWN_NULL_COUNT)` was invoked, then the
* first invocation of `null_count()` will compute and store the count of null
* elements indicated by the `null_mask` (if it exists).
*
* @return The count of null elements
*/
[[nodiscard]] size_type null_count() const;
Expand Down Expand Up @@ -263,10 +258,6 @@ class column_view_base {
*
* If `null_count()` is zero, `null_mask` is optional.
*
* If the null count of the `null_mask` is not specified, it defaults to
* `UNKNOWN_NULL_COUNT`. The first invocation of `null_count()` will then
* compute the null count if `null_mask` exists.
*
* If `type` is `EMPTY`, the specified `null_count` will be ignored and
* `null_count()` will always return the same value as `size()`
*
Expand Down Expand Up @@ -357,10 +348,6 @@ class column_view : public detail::column_view_base {
*
* If `null_count()` is zero, `null_mask` is optional.
*
* If the null count of the `null_mask` is not specified, it defaults to
* `UNKNOWN_NULL_COUNT`. The first invocation of `null_count()` will then
* compute the null count if `null_mask` exists.
*
* If `type` is `EMPTY`, the specified `null_count` will be ignored and
* `null_count()` will always return the same value as `size()`
*
Expand Down Expand Up @@ -511,10 +498,6 @@ class mutable_column_view : public detail::column_view_base {
* @brief Construct a `mutable_column_view` from pointers to device memory for
*the elements and bitmask of the column.
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* If the null count of the `null_mask` is not specified, it defaults to
* `UNKNOWN_NULL_COUNT`. The first invocation of `null_count()` will then
* compute the null count.
*
* If `type` is `EMPTY`, the specified `null_count` will be ignored and
* `null_count()` will always return the same value as `size()`
*
Expand Down
5 changes: 0 additions & 5 deletions cpp/include/cudf/detail/copy_range.cuh
Original file line number Diff line number Diff line change
Expand Up @@ -154,11 +154,6 @@ void copy_range(SourceValueIterator source_value_begin,
auto grid = cudf::detail::grid_1d{num_items, block_size, 1};

if (target.nullable()) {
// TODO: if null_count is UNKNOWN_NULL_COUNT, no need to update null
// count (if null_count is UNKNOWN_NULL_COUNT, invoking null_count()
// will scan the entire bitmask array, and this can be surprising
// in performance if the copy range is small and the column size is
// large).
rmm::device_scalar<size_type> null_count(target.null_count(), stream);

auto kernel =
Expand Down
8 changes: 0 additions & 8 deletions cpp/include/cudf/types.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -97,14 +97,6 @@ size_type distance(T f, T l)
return static_cast<size_type>(std::distance(f, l));
}

/**
* @brief Indicates an unknown null count.
*
* Use this value when constructing any column-like object to indicate that
* the null count should be computed on the first invocation of `null_count()`.
*/
static constexpr size_type UNKNOWN_NULL_COUNT{-1};

/**
* @brief Indicates the order in which elements should be sorted.
*/
Expand Down
25 changes: 2 additions & 23 deletions cpp/src/column/column.cu
Original file line number Diff line number Diff line change
Expand Up @@ -117,37 +117,16 @@ mutable_column_view column::mutable_view()
child_views.emplace_back(*c);
}

// Store the old null count before resetting it. By accessing the value
// directly instead of calling `this->null_count()`, we can avoid a potential
// invocation of `cudf::detail::null_count()`. This does however mean that
// calling `this->null_count()` on the resulting mutable view could still
// potentially invoke `cudf::detail::null_count()`.
auto current_null_count = _null_count;

// The elements of a column could be changed through a `mutable_column_view`, therefore the
// existing `null_count` is no longer valid. Reset it to `UNKNOWN_NULL_COUNT` forcing it to be
// recomputed on the next invocation of `this->null_count()`.
set_null_count(cudf::UNKNOWN_NULL_COUNT);

return mutable_column_view{type(),
size(),
_data.data(),
static_cast<bitmask_type*>(_null_mask.data()),
current_null_count,
_null_count,
0,
child_views};
}

// If the null count is known, return it. Else, compute and return it
size_type column::null_count() const
{
CUDF_FUNC_RANGE();
if (_null_count <= cudf::UNKNOWN_NULL_COUNT) {
_null_count = cudf::detail::null_count(
static_cast<bitmask_type const*>(_null_mask.data()), 0, size(), cudf::get_default_stream());
}
return _null_count;
}
size_type column::null_count() const { return _null_count; }
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void column::set_null_mask(rmm::device_buffer&& new_null_mask, size_type new_null_count)
{
Expand Down
12 changes: 2 additions & 10 deletions cpp/src/column/column_view.cpp
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
/*
* Copyright (c) 2019-2022, NVIDIA CORPORATION.
* Copyright (c) 2019-2023, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -63,15 +63,7 @@ column_view_base::column_view_base(data_type type,
}
}

// If null count is known, returns it. Else, compute and return it
size_type column_view_base::null_count() const
{
if (_null_count <= cudf::UNKNOWN_NULL_COUNT) {
_null_count = cudf::detail::null_count(
null_mask(), offset(), offset() + size(), cudf::get_default_stream());
}
return _null_count;
}
size_type column_view_base::null_count() const { return _null_count; }
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size_type column_view_base::null_count(size_type begin, size_type end) const
{
Expand Down
39 changes: 27 additions & 12 deletions cpp/src/groupby/sort/group_std.cu
Original file line number Diff line number Diff line change
Expand Up @@ -20,12 +20,14 @@
#include <cudf/column/column_factories.hpp>
#include <cudf/column/column_view.hpp>
#include <cudf/detail/aggregation/aggregation.hpp>
#include <cudf/detail/null_mask.hpp>
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#include <cudf/dictionary/detail/iterator.cuh>
#include <cudf/dictionary/dictionary_column_view.hpp>
#include <cudf/utilities/span.hpp>
#include <cudf/utilities/type_dispatcher.hpp>

#include <rmm/cuda_stream_view.hpp>
#include <rmm/device_scalar.hpp>
#include <rmm/device_uvector.hpp>
#include <rmm/exec_policy.hpp>

Expand Down Expand Up @@ -131,18 +133,31 @@ struct var_functor {
}

// set nulls
auto result_view = mutable_column_device_view::create(*result, stream);
thrust::for_each_n(rmm::exec_policy(stream),
thrust::make_counting_iterator(0),
group_sizes.size(),
[d_result = *result_view, d_group_sizes, ddof] __device__(size_type i) {
size_type group_size = d_group_sizes[i];
if (group_size == 0 or group_size - ddof <= 0)
d_result.set_null(i);
else
d_result.set_valid(i);
});

auto result_view = mutable_column_device_view::create(*result, stream);
auto null_count = rmm::device_scalar<cudf::size_type>(0, stream, mr);
auto d_null_count = null_count.data();
thrust::for_each_n(
rmm::exec_policy(stream),
thrust::make_counting_iterator(0),
group_sizes.size(),
[d_result = *result_view, d_group_sizes, ddof, d_null_count] __device__(size_type i) {
size_type group_size = d_group_sizes[i];
if (group_size == 0 or group_size - ddof <= 0) {
d_result.set_null(i);
// Assuming that typical data does not have too many nulls this
// atomic shouldn't serialize the code too much. The alternatives
// would be 1) writing a more complex kernel using cub/shmem to
// increase parallelism, or 2) calling `cudf::count_nulls` after the
// fact. (1) is more work than it's worth without benchmarking, and
// this approach should outperform (2) unless large amounts of the
// data is null.
atomicAdd(d_null_count, 1);
} else {
d_result.set_valid(i);
}
});

result->set_null_count(null_count.value(stream));
return result;
}

Expand Down
3 changes: 3 additions & 0 deletions cpp/src/transform/compute_column.cu
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
#include <cudf/ast/expressions.hpp>
#include <cudf/column/column_device_view.cuh>
#include <cudf/column/column_factories.hpp>
#include <cudf/detail/null_mask.hpp>
#include <cudf/detail/nvtx/ranges.hpp>
#include <cudf/detail/transform.hpp>
#include <cudf/detail/utilities/cuda.cuh>
Expand Down Expand Up @@ -128,6 +129,8 @@ std::unique_ptr<column> compute_column(table_view const& table,
*table_device, device_expression_data, *mutable_output_device);
}
CUDF_CHECK_CUDA(stream.value());
output_column->set_null_count(
cudf::detail::null_count(mutable_output_device->null_mask(), 0, output_column->size(), stream));
return output_column;
}

Expand Down
18 changes: 4 additions & 14 deletions cpp/tests/copying/utility_tests.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -194,15 +194,7 @@ TYPED_TEST(AllocateLikeTest, ColumnNumericTestSameSize)
input = make_numeric_column(
cudf::data_type{cudf::type_to_id<TypeParam>()}, size, cudf::mask_state::ALL_VALID);
got = cudf::allocate_like(input->view());
EXPECT_EQ(input->type(), got->type());
EXPECT_EQ(input->size(), got->size());
EXPECT_EQ(input->nullable(), got->nullable());
EXPECT_EQ(input->num_children(), got->num_children());
// CUDF_TEST_EXPECT_COLUMN_PROPERTIES_EQUAL includes checking the null-count property.
// This value will be incorrect since the null mask will contain uninitialized bits
// and the null-count set to UNKNOWN_NULL_COUNT on return from allocate_like().
// This means any subsequent call to null_count() will try to compute the null-count
// using the uninitialized null-mask.
CUDF_TEST_EXPECT_COLUMN_PROPERTIES_EQUAL(*input, *got);
}

TYPED_TEST(AllocateLikeTest, ColumnNumericTestSpecifiedSize)
Expand All @@ -221,15 +213,13 @@ TYPED_TEST(AllocateLikeTest, ColumnNumericTestSpecifiedSize)
input = make_numeric_column(
cudf::data_type{cudf::type_to_id<TypeParam>()}, size, cudf::mask_state::ALL_VALID);
got = cudf::allocate_like(input->view(), specified_size);
// Can't use CUDF_TEST_EXPECT_COLUMN_PROPERTIES_EQUAL because the sizes of
// the two columns are different.
EXPECT_EQ(input->type(), got->type());
EXPECT_EQ(specified_size, got->size());
EXPECT_EQ(0, got->null_count());
EXPECT_EQ(input->nullable(), got->nullable());
EXPECT_EQ(input->num_children(), got->num_children());
// CUDF_TEST_EXPECT_COLUMN_PROPERTIES_EQUAL includes checking the null-count property.
// This value will be incorrect since the null mask will contain uninitialized bits
// and the null-count set to UNKNOWN_NULL_COUNT on return from allocate_like().
// This means any subsequent call to null_count() will try to compute the null-count
// using the uninitialized null-mask.
}

CUDF_TEST_PROGRAM_MAIN()
31 changes: 31 additions & 0 deletions cpp/tests/groupby/var_tests.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -167,3 +167,34 @@ TYPED_TEST(groupby_var_test, dictionary)
expect_vals,
cudf::make_variance_aggregation<cudf::groupby_aggregation>());
}

// This test ensures that the same results are produced by the sort-based and
// hash-based implementations of groupby-variance.
TYPED_TEST(groupby_var_test, sort_vs_hash)
{
using K = int32_t;
using V = double;

cudf::test::fixed_width_column_wrapper<K> keys{50, 30, 90, 80};
cudf::test::fixed_width_column_wrapper<V> vals{380.0, 370.0, 24.0, 26.0};

cudf::groupby::groupby gb_obj(cudf::table_view({keys}));

auto agg1 = cudf::make_variance_aggregation<cudf::groupby_aggregation>();

std::vector<cudf::groupby::aggregation_request> requests;
requests.emplace_back();
requests[0].values = vals;
requests[0].aggregations.push_back(std::move(agg1));

auto result1 = gb_obj.aggregate(requests);

// This agg forces a sort groupby.
auto agg2 = cudf::make_quantile_aggregation<cudf::groupby_aggregation>({0.25});
requests[0].aggregations.push_back(std::move(agg2));

auto result2 = gb_obj.aggregate(requests);

EXPECT_EQ(result1.second[0].results[0]->null_count(), result2.second[0].results[0]->null_count());
CUDF_TEST_EXPECT_COLUMNS_EQUAL(*result1.second[0].results[0], *result2.second[0].results[0]);
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}