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column_utilities.cu
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column_utilities.cu
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/*
* Copyright (c) 2019-2022, 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.
*/
#include <cudf/column/column_view.hpp>
#include <cudf/detail/copy.hpp>
#include <cudf/detail/get_value.cuh>
#include <cudf/detail/iterator.cuh>
#include <cudf/detail/utilities/vector_factories.hpp>
#include <cudf/dictionary/dictionary_column_view.hpp>
#include <cudf/lists/lists_column_view.hpp>
#include <cudf/strings/convert/convert_datetime.hpp>
#include <cudf/structs/struct_view.hpp>
#include <cudf/structs/structs_column_view.hpp>
#include <cudf/table/row_operators.cuh>
#include <cudf/table/table_device_view.cuh>
#include <cudf/utilities/bit.hpp>
#include <cudf/utilities/default_stream.hpp>
#include <cudf/utilities/type_dispatcher.hpp>
#include <cudf_test/column_utilities.hpp>
#include <cudf_test/column_wrapper.hpp>
#include <cudf_test/cudf_gtest.hpp>
#include <cudf_test/detail/column_utilities.hpp>
#include <jit/type.hpp>
#include <rmm/exec_policy.hpp>
#include <thrust/copy.h>
#include <thrust/distance.h>
#include <thrust/equal.h>
#include <thrust/execution_policy.h>
#include <thrust/generate.h>
#include <thrust/iterator/counting_iterator.h>
#include <thrust/iterator/transform_iterator.h>
#include <thrust/logical.h>
#include <thrust/reduce.h>
#include <thrust/scan.h>
#include <thrust/scatter.h>
#include <thrust/sequence.h>
#include <thrust/transform.h>
#include <numeric>
#include <sstream>
namespace cudf {
namespace test {
namespace {
std::unique_ptr<column> generate_all_row_indices(size_type num_rows)
{
auto indices =
cudf::make_fixed_width_column(data_type{type_id::INT32}, num_rows, mask_state::UNALLOCATED);
thrust::sequence(rmm::exec_policy(cudf::default_stream_value),
indices->mutable_view().begin<size_type>(),
indices->mutable_view().end<size_type>(),
0);
return indices;
}
// generate the rows indices that should be checked for the child column of a list column.
//
// - if we are just checking for equivalence, we can skip any rows that are nulls. this allows
// things like non-empty rows that have been nullified after creation. they may actually contain
// values, but since the row is null they don't matter for equivalency.
//
// - if we are checking for exact equality, we need to check all rows.
//
// This allows us to differentiate between:
//
// List<int32_t>:
// Length : 1
// Offsets : 0, 4
// Null count: 1
// 0
// 0, 1, 2, 3
//
// List<int32_t>:
// Length : 1
// Offsets : 0, 0
// Null count: 1
// 0
//
std::unique_ptr<column> generate_child_row_indices(lists_column_view const& c,
column_view const& row_indices,
bool check_exact_equality)
{
// if we are checking for exact equality, we should be checking for "unsanitized" data that may
// be hiding underneath nulls. so check all rows instead of just non-null rows
if (check_exact_equality) {
return generate_all_row_indices(c.get_sliced_child(cudf::default_stream_value).size());
}
// Example input
// List<int32_t>:
// Length : 7
// Offsets : 0, 3, 6, 8, 11, 14, 16, 19
// | | <-- non-null input rows
// Null count: 5
// 0010100
// 1, 1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 7, 7, 7
// | | | | | <-- child rows of non-null rows
//
// Desired output: [6, 7, 11, 12, 13]
// compute total # of child row indices we will be emitting.
auto row_size_iter = cudf::detail::make_counting_transform_iterator(
0,
[row_indices = row_indices.begin<size_type>(),
validity = c.null_mask(),
offsets = c.offsets().begin<offset_type>(),
offset = c.offset()] __device__(int index) {
// both null mask and offsets data are not pre-sliced. so we need to add the column offset to
// every incoming index.
auto const true_index = row_indices[index] + offset;
return !validity || cudf::bit_is_set(validity, true_index)
? (offsets[true_index + 1] - offsets[true_index])
: 0;
});
auto const output_size = thrust::reduce(rmm::exec_policy(cudf::default_stream_value),
row_size_iter,
row_size_iter + row_indices.size());
// no output. done.
auto result =
cudf::make_fixed_width_column(data_type{type_id::INT32}, output_size, mask_state::UNALLOCATED);
if (output_size == 0) { return result; }
// for all input rows, what position in the output column they will start at.
//
// output_row_start = [0, 0, 0, 2, 2, 5, 5]
// | | <-- non-null input rows
//
auto output_row_start = cudf::make_fixed_width_column(
data_type{type_id::INT32}, row_indices.size(), mask_state::UNALLOCATED);
thrust::exclusive_scan(rmm::exec_policy(cudf::default_stream_value),
row_size_iter,
row_size_iter + row_indices.size(),
output_row_start->mutable_view().begin<size_type>());
// fill result column with 1s
//
// result = [1, 1, 1, 1, 1]
//
thrust::generate(rmm::exec_policy(cudf::default_stream_value),
result->mutable_view().begin<size_type>(),
result->mutable_view().end<size_type>(),
[] __device__() { return 1; });
// scatter the output row positions into result buffer
//
// result = [6, 1, 11, 1, 1]
//
auto output_row_iter = cudf::detail::make_counting_transform_iterator(
0,
[row_indices = row_indices.begin<size_type>(),
offsets = c.offsets().begin<offset_type>(),
offset = c.offset(),
first_offset = cudf::detail::get_value<offset_type>(
c.offsets(), c.offset(), cudf::default_stream_value)] __device__(int index) {
auto const true_index = row_indices[index] + offset;
return offsets[true_index] - first_offset;
});
thrust::scatter_if(rmm::exec_policy(cudf::default_stream_value),
output_row_iter,
output_row_iter + row_indices.size(),
output_row_start->view().begin<size_type>(),
row_size_iter,
result->mutable_view().begin<size_type>(),
[] __device__(auto row_size) { return row_size != 0; });
// generate keys for each output row
//
// result = [1, 1, 2, 2, 2]
//
auto keys =
cudf::make_fixed_width_column(data_type{type_id::INT32}, output_size, mask_state::UNALLOCATED);
thrust::generate(rmm::exec_policy(cudf::default_stream_value),
keys->mutable_view().begin<size_type>(),
keys->mutable_view().end<size_type>(),
[] __device__() { return 0; });
thrust::scatter_if(rmm::exec_policy(cudf::default_stream_value),
row_size_iter,
row_size_iter + row_indices.size(),
output_row_start->view().begin<size_type>(),
row_size_iter,
keys->mutable_view().begin<size_type>(),
[] __device__(auto row_size) { return row_size != 0; });
thrust::inclusive_scan(rmm::exec_policy(cudf::default_stream_value),
keys->view().begin<size_type>(),
keys->view().end<size_type>(),
keys->mutable_view().begin<size_type>());
// scan by key to generate final child row indices.
// input
// result = [6, 1, 11, 1, 1]
// keys = [1, 1, 2, 2, 2]
//
// output
// result = [6, 7, 11, 12, 13]
//
thrust::inclusive_scan_by_key(rmm::exec_policy(cudf::default_stream_value),
keys->view().begin<size_type>(),
keys->view().end<size_type>(),
result->view().begin<size_type>(),
result->mutable_view().begin<size_type>());
return result;
}
#define PROP_EXPECT_EQ(a, b) \
do { \
if (verbosity == debug_output_level::QUIET) { \
if (a != b) { return false; } \
} else { \
EXPECT_EQ(a, b); \
if (a != b) { \
if (verbosity == debug_output_level::FIRST_ERROR) { \
return false; \
} else { \
result = false; \
} \
} \
} \
} while (0)
template <bool check_exact_equality>
struct column_property_comparator {
bool types_equivalent(cudf::data_type const& lhs, cudf::data_type const& rhs)
{
return is_fixed_point(lhs) ? lhs.id() == rhs.id() : lhs == rhs;
}
size_type count_nulls(cudf::column_view const& c, cudf::column_view const& row_indices)
{
auto validity_iter = cudf::detail::make_counting_transform_iterator(
0,
[row_indices = row_indices.begin<size_type>(),
validity = c.null_mask(),
offset = c.offset()] __device__(int index) {
// both null mask and offsets data are not pre-sliced. so we need to add the column offset
// to every incoming index.
auto const true_index = row_indices[index] + offset;
return !validity || cudf::bit_is_set(validity, true_index) ? 0 : 1;
});
return thrust::reduce(rmm::exec_policy(cudf::default_stream_value),
validity_iter,
validity_iter + row_indices.size());
}
bool compare_common(cudf::column_view const& lhs,
cudf::column_view const& rhs,
cudf::column_view const& lhs_row_indices,
cudf::column_view const& rhs_row_indices,
debug_output_level verbosity)
{
bool result = true;
if (check_exact_equality) {
PROP_EXPECT_EQ(lhs.type(), rhs.type());
} else {
PROP_EXPECT_EQ(types_equivalent(lhs.type(), rhs.type()), true);
}
auto const lhs_size = check_exact_equality ? lhs.size() : lhs_row_indices.size();
auto const rhs_size = check_exact_equality ? rhs.size() : rhs_row_indices.size();
PROP_EXPECT_EQ(lhs_size, rhs_size);
if (lhs_size > 0 && check_exact_equality) { PROP_EXPECT_EQ(lhs.nullable(), rhs.nullable()); }
// DISCUSSION: does this make sense, semantically?
auto const lhs_null_count =
check_exact_equality ? lhs.null_count() : count_nulls(lhs, lhs_row_indices);
auto const rhs_null_count =
check_exact_equality ? rhs.null_count() : count_nulls(rhs, rhs_row_indices);
PROP_EXPECT_EQ(lhs_null_count, rhs_null_count);
// equivalent, but not exactly equal columns can have a different number of children if their
// sizes are both 0. Specifically, empty string columns may or may not have children.
if (check_exact_equality || (lhs.size() > 0 && lhs.null_count() < lhs.size())) {
PROP_EXPECT_EQ(lhs.num_children(), rhs.num_children());
}
return result;
}
template <typename T,
std::enable_if_t<!std::is_same_v<T, cudf::list_view> &&
!std::is_same_v<T, cudf::struct_view>>* = nullptr>
bool operator()(cudf::column_view const& lhs,
cudf::column_view const& rhs,
cudf::column_view const& lhs_row_indices,
cudf::column_view const& rhs_row_indices,
debug_output_level verbosity)
{
return compare_common(lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity);
}
template <typename T, std::enable_if_t<std::is_same_v<T, cudf::list_view>>* = nullptr>
bool operator()(cudf::column_view const& lhs,
cudf::column_view const& rhs,
cudf::column_view const& lhs_row_indices,
cudf::column_view const& rhs_row_indices,
debug_output_level verbosity)
{
if (!compare_common(lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity)) { return false; }
cudf::lists_column_view lhs_l(lhs);
cudf::lists_column_view rhs_l(rhs);
// recurse
// note: if a column is all nulls (and we are checking for exact equality) or otherwise empty,
// no indices are generated and no recursion happens
auto lhs_child_indices =
generate_child_row_indices(lhs_l, lhs_row_indices, check_exact_equality);
if (lhs_child_indices->size() > 0) {
auto lhs_child = lhs_l.get_sliced_child(cudf::default_stream_value);
auto rhs_child = rhs_l.get_sliced_child(cudf::default_stream_value);
auto rhs_child_indices =
generate_child_row_indices(rhs_l, rhs_row_indices, check_exact_equality);
return cudf::type_dispatcher(lhs_child.type(),
column_property_comparator<check_exact_equality>{},
lhs_child,
rhs_child,
*lhs_child_indices,
*rhs_child_indices,
verbosity);
}
return true;
}
template <typename T, std::enable_if_t<std::is_same_v<T, cudf::struct_view>>* = nullptr>
bool operator()(cudf::column_view const& lhs,
cudf::column_view const& rhs,
cudf::column_view const& lhs_row_indices,
cudf::column_view const& rhs_row_indices,
debug_output_level verbosity)
{
if (!compare_common(lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity)) { return false; }
structs_column_view l_scv(lhs);
structs_column_view r_scv(rhs);
for (size_type i = 0; i < lhs.num_children(); i++) {
column_view lhs_child = l_scv.get_sliced_child(i);
column_view rhs_child = r_scv.get_sliced_child(i);
if (!cudf::type_dispatcher(lhs_child.type(),
column_property_comparator<check_exact_equality>{},
lhs_child,
rhs_child,
lhs_row_indices,
rhs_row_indices,
verbosity)) {
return false;
}
}
return true;
}
};
class corresponding_rows_unequal {
public:
corresponding_rows_unequal(table_device_view d_lhs,
table_device_view d_rhs,
column_device_view lhs_row_indices_,
column_device_view rhs_row_indices_,
size_type /*fp_ulps*/)
: comp(cudf::nullate::YES{}, d_lhs, d_rhs, cudf::null_equality::EQUAL),
lhs_row_indices(lhs_row_indices_),
rhs_row_indices(rhs_row_indices_)
{
}
cudf::row_equality_comparator<cudf::nullate::YES> comp;
__device__ bool operator()(size_type index)
{
return !comp(lhs_row_indices.element<size_type>(index),
rhs_row_indices.element<size_type>(index));
}
column_device_view lhs_row_indices;
column_device_view rhs_row_indices;
};
class corresponding_rows_not_equivalent {
table_device_view d_lhs;
table_device_view d_rhs;
column_device_view lhs_row_indices;
column_device_view rhs_row_indices;
size_type const fp_ulps;
public:
corresponding_rows_not_equivalent(table_device_view d_lhs,
table_device_view d_rhs,
column_device_view lhs_row_indices_,
column_device_view rhs_row_indices_,
size_type fp_ulps_)
: d_lhs(d_lhs),
d_rhs(d_rhs),
comp(cudf::nullate::YES{}, d_lhs, d_rhs, null_equality::EQUAL),
lhs_row_indices(lhs_row_indices_),
rhs_row_indices(rhs_row_indices_),
fp_ulps(fp_ulps_)
{
CUDF_EXPECTS(d_lhs.num_columns() == 1 and d_rhs.num_columns() == 1,
"Unsupported number of columns");
}
struct typed_element_not_equivalent {
template <typename T>
__device__ std::enable_if_t<std::is_floating_point_v<T>, bool> operator()(
column_device_view const& lhs,
column_device_view const& rhs,
size_type lhs_index,
size_type rhs_index,
size_type fp_ulps)
{
if (lhs.is_valid(lhs_index) and rhs.is_valid(rhs_index)) {
T const x = lhs.element<T>(lhs_index);
T const y = rhs.element<T>(rhs_index);
// Must handle inf and nan separately
if (std::isinf(x) || std::isinf(y)) {
return x != y; // comparison of (inf==inf) returns true
} else if (std::isnan(x) || std::isnan(y)) {
return std::isnan(x) != std::isnan(y); // comparison of (nan==nan) returns false
} else {
T const abs_x_minus_y = std::abs(x - y);
return abs_x_minus_y >= std::numeric_limits<T>::min() &&
abs_x_minus_y > std::numeric_limits<T>::epsilon() * std::abs(x + y) * fp_ulps;
}
} else {
// if either is null, then the inequality was checked already
return true;
}
}
template <typename T, typename... Args>
__device__ std::enable_if_t<not std::is_floating_point_v<T>, bool> operator()(Args...)
{
// Non-floating point inequality is checked already
return true;
}
};
cudf::row_equality_comparator<cudf::nullate::YES> comp;
__device__ bool operator()(size_type index)
{
auto const lhs_index = lhs_row_indices.element<size_type>(index);
auto const rhs_index = rhs_row_indices.element<size_type>(index);
if (not comp(lhs_index, rhs_index)) {
auto lhs_col = this->d_lhs.column(0);
auto rhs_col = this->d_rhs.column(0);
return type_dispatcher(lhs_col.type(),
typed_element_not_equivalent{},
lhs_col,
rhs_col,
lhs_index,
rhs_index,
fp_ulps);
}
return false;
}
};
// Stringify the inconsistent values resulted from the comparison of two columns element-wise
std::string stringify_column_differences(cudf::device_span<int const> differences,
column_view const& lhs,
column_view const& rhs,
column_view const& lhs_row_indices,
column_view const& rhs_row_indices,
debug_output_level verbosity,
int depth)
{
CUDF_EXPECTS(not differences.empty(), "Shouldn't enter this function if `differences` is empty");
std::string const depth_str = depth > 0 ? "depth " + std::to_string(depth) + '\n' : "";
// move the differences to the host.
auto h_differences = cudf::detail::make_host_vector_sync(differences);
if (verbosity == debug_output_level::ALL_ERRORS) {
std::ostringstream buffer;
buffer << depth_str << "differences:" << std::endl;
auto source_table = cudf::table_view({lhs, rhs});
auto diff_column =
fixed_width_column_wrapper<int32_t>(h_differences.begin(), h_differences.end());
auto diff_table = cudf::gather(source_table, diff_column);
// Need to pull back the differences
auto const h_left_strings = to_strings(diff_table->get_column(0));
auto const h_right_strings = to_strings(diff_table->get_column(1));
for (size_t i = 0; i < h_differences.size(); ++i)
buffer << depth_str << "lhs[" << h_differences[i] << "] = " << h_left_strings[i] << ", rhs["
<< h_differences[i] << "] = " << h_right_strings[i] << std::endl;
return buffer.str();
} else {
auto const index = h_differences[0]; // only stringify first difference
auto const lhs_index =
cudf::detail::get_value<size_type>(lhs_row_indices, index, cudf::default_stream_value);
auto const rhs_index =
cudf::detail::get_value<size_type>(rhs_row_indices, index, cudf::default_stream_value);
auto diff_lhs = cudf::detail::slice(lhs, lhs_index, lhs_index + 1);
auto diff_rhs = cudf::detail::slice(rhs, rhs_index, rhs_index + 1);
return depth_str + "first difference: " + "lhs[" + std::to_string(index) +
"] = " + to_string(diff_lhs, "") + ", rhs[" + std::to_string(index) +
"] = " + to_string(diff_rhs, "");
}
}
// non-nested column types
template <typename T, bool check_exact_equality>
struct column_comparator_impl {
bool operator()(column_view const& lhs,
column_view const& rhs,
column_view const& lhs_row_indices,
column_view const& rhs_row_indices,
debug_output_level verbosity,
size_type fp_ulps,
int depth)
{
auto d_lhs = cudf::table_device_view::create(table_view{{lhs}});
auto d_rhs = cudf::table_device_view::create(table_view{{rhs}});
auto d_lhs_row_indices = cudf::column_device_view::create(lhs_row_indices);
auto d_rhs_row_indices = cudf::column_device_view::create(rhs_row_indices);
using ComparatorType = std::conditional_t<check_exact_equality,
corresponding_rows_unequal,
corresponding_rows_not_equivalent>;
auto differences = rmm::device_uvector<int>(
lhs.size(), cudf::default_stream_value); // worst case: everything different
auto input_iter = thrust::make_counting_iterator(0);
auto diff_iter = thrust::copy_if(
rmm::exec_policy(cudf::default_stream_value),
input_iter,
input_iter + lhs_row_indices.size(),
differences.begin(),
ComparatorType(*d_lhs, *d_rhs, *d_lhs_row_indices, *d_rhs_row_indices, fp_ulps));
differences.resize(thrust::distance(differences.begin(), diff_iter),
cudf::default_stream_value); // shrink back down
if (not differences.is_empty()) {
if (verbosity != debug_output_level::QUIET) {
// GTEST_FAIL() does a return that conflicts with our return type. so hide it in a lambda.
[&]() {
GTEST_FAIL() << stringify_column_differences(
differences, lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity, depth);
}();
}
return false;
}
return true;
}
};
// forward declaration for nested-type recursion.
template <bool check_exact_equality>
struct column_comparator;
// specialization for list columns
template <bool check_exact_equality>
struct column_comparator_impl<list_view, check_exact_equality> {
bool operator()(column_view const& lhs,
column_view const& rhs,
column_view const& lhs_row_indices,
column_view const& rhs_row_indices,
debug_output_level verbosity,
size_type fp_ulps,
int depth)
{
lists_column_view lhs_l(lhs);
lists_column_view rhs_l(rhs);
CUDF_EXPECTS(lhs_row_indices.size() == rhs_row_indices.size(), "List column size mismatch");
if (lhs_row_indices.is_empty()) { return true; }
// worst case - everything is different
rmm::device_uvector<int> differences(lhs_row_indices.size(), cudf::default_stream_value);
// compare offsets, taking slicing into account
// left side
size_type lhs_shift = cudf::detail::get_value<size_type>(
lhs_l.offsets(), lhs_l.offset(), cudf::default_stream_value);
auto lhs_offsets = thrust::make_transform_iterator(
lhs_l.offsets().begin<size_type>() + lhs_l.offset(),
[lhs_shift] __device__(size_type offset) { return offset - lhs_shift; });
auto lhs_valids = thrust::make_transform_iterator(
thrust::make_counting_iterator(0),
[mask = lhs_l.null_mask(), offset = lhs_l.offset()] __device__(size_type index) {
return mask == nullptr ? true : cudf::bit_is_set(mask, index + offset);
});
// right side
size_type rhs_shift = cudf::detail::get_value<size_type>(
rhs_l.offsets(), rhs_l.offset(), cudf::default_stream_value);
auto rhs_offsets = thrust::make_transform_iterator(
rhs_l.offsets().begin<size_type>() + rhs_l.offset(),
[rhs_shift] __device__(size_type offset) { return offset - rhs_shift; });
auto rhs_valids = thrust::make_transform_iterator(
thrust::make_counting_iterator(0),
[mask = rhs_l.null_mask(), offset = rhs_l.offset()] __device__(size_type index) {
return mask == nullptr ? true : cudf::bit_is_set(mask, index + offset);
});
// when checking for equivalency, we can't compare offset values directly, we can only
// compare lengths of the rows, and only if valid. as a concrete example, you could have two
// equivalent columns with the following data:
//
// column A
// offsets = [0, 3, 5, 7]
// validity = [0, 1, 1, 1]
//
// column B
// offsets = [0, 0, 2, 4]
// validity = [0, 1, 1, 1]
//
// Row 0 in column A happens to have a positive length, even though the row is null, but column
// B does not. So the offsets for the remaining valid rows are fundamentally different even
// though the row lengths are the same.
//
auto input_iter = thrust::make_counting_iterator(0);
auto diff_iter = thrust::copy_if(
rmm::exec_policy(cudf::default_stream_value),
input_iter,
input_iter + lhs_row_indices.size(),
differences.begin(),
[lhs_offsets,
rhs_offsets,
lhs_valids,
rhs_valids,
lhs_indices = lhs_row_indices.begin<size_type>(),
rhs_indices = rhs_row_indices.begin<size_type>()] __device__(size_type index) {
auto const lhs_index = lhs_indices[index];
auto const rhs_index = rhs_indices[index];
// check for validity match
if (lhs_valids[lhs_index] != rhs_valids[rhs_index]) { return true; }
// if the row is valid, check that the length of the list is the same. do this
// for both the equivalency and exact equality checks.
if (lhs_valids[lhs_index] && ((lhs_offsets[lhs_index + 1] - lhs_offsets[lhs_index]) !=
(rhs_offsets[rhs_index + 1] - rhs_offsets[rhs_index]))) {
return true;
}
// if validity matches -and- is false, we can ignore the actual offset values. this
// is technically not checking "equal()", but it's how the non-list code path handles it
if (!lhs_valids[lhs_index]) { return false; }
// if checking exact equality, compare the actual offset values
if (check_exact_equality && lhs_offsets[lhs_index] != rhs_offsets[rhs_index]) {
return true;
}
return false;
});
differences.resize(thrust::distance(differences.begin(), diff_iter),
cudf::default_stream_value); // shrink back down
if (not differences.is_empty()) {
if (verbosity != debug_output_level::QUIET) {
// GTEST_FAIL() does a return that conflicts with our return type. so hide it in a lambda.
[&]() {
GTEST_FAIL() << stringify_column_differences(
differences, lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity, depth);
}();
}
return false;
}
// recurse
// note: if a column is all nulls (and we are only checking for equivalence) or otherwise empty,
// no indices are generated and no recursion happens
auto lhs_child_indices =
generate_child_row_indices(lhs_l, lhs_row_indices, check_exact_equality);
if (lhs_child_indices->size() > 0) {
auto lhs_child = lhs_l.get_sliced_child(cudf::default_stream_value);
auto rhs_child = rhs_l.get_sliced_child(cudf::default_stream_value);
auto rhs_child_indices =
generate_child_row_indices(rhs_l, rhs_row_indices, check_exact_equality);
return cudf::type_dispatcher(lhs_child.type(),
column_comparator<check_exact_equality>{},
lhs_child,
rhs_child,
*lhs_child_indices,
*rhs_child_indices,
verbosity,
fp_ulps,
depth + 1);
}
return true;
}
};
template <bool check_exact_equality>
struct column_comparator_impl<struct_view, check_exact_equality> {
bool operator()(column_view const& lhs,
column_view const& rhs,
column_view const& lhs_row_indices,
column_view const& rhs_row_indices,
debug_output_level verbosity,
size_type fp_ulps,
int depth)
{
structs_column_view l_scv(lhs);
structs_column_view r_scv(rhs);
for (size_type i = 0; i < lhs.num_children(); i++) {
column_view lhs_child = l_scv.get_sliced_child(i);
column_view rhs_child = r_scv.get_sliced_child(i);
if (!cudf::type_dispatcher(lhs_child.type(),
column_comparator<check_exact_equality>{},
lhs_child,
rhs_child,
lhs_row_indices,
rhs_row_indices,
verbosity,
fp_ulps,
depth + 1)) {
return false;
}
}
return true;
}
};
template <bool check_exact_equality>
struct column_comparator {
template <typename T>
bool operator()(column_view const& lhs,
column_view const& rhs,
column_view const& lhs_row_indices,
column_view const& rhs_row_indices,
debug_output_level verbosity,
size_type fp_ulps,
int depth = 0)
{
// compare properties
if (!cudf::type_dispatcher(lhs.type(),
column_property_comparator<check_exact_equality>{},
lhs,
rhs,
lhs_row_indices,
rhs_row_indices,
verbosity)) {
return false;
}
// compare values
column_comparator_impl<T, check_exact_equality> comparator{};
return comparator(lhs, rhs, lhs_row_indices, rhs_row_indices, verbosity, fp_ulps, depth);
}
};
} // namespace
/**
* @copydoc cudf::test::expect_column_properties_equal
*/
bool expect_column_properties_equal(column_view const& lhs,
column_view const& rhs,
debug_output_level verbosity)
{
auto lhs_indices = generate_all_row_indices(lhs.size());
auto rhs_indices = generate_all_row_indices(rhs.size());
return cudf::type_dispatcher(lhs.type(),
column_property_comparator<true>{},
lhs,
rhs,
*lhs_indices,
*rhs_indices,
verbosity);
}
/**
* @copydoc cudf::test::expect_column_properties_equivalent
*/
bool expect_column_properties_equivalent(column_view const& lhs,
column_view const& rhs,
debug_output_level verbosity)
{
auto lhs_indices = generate_all_row_indices(lhs.size());
auto rhs_indices = generate_all_row_indices(rhs.size());
return cudf::type_dispatcher(lhs.type(),
column_property_comparator<false>{},
lhs,
rhs,
*lhs_indices,
*rhs_indices,
verbosity);
}
/**
* @copydoc cudf::test::expect_columns_equal
*/
bool expect_columns_equal(cudf::column_view const& lhs,
cudf::column_view const& rhs,
debug_output_level verbosity)
{
auto lhs_indices = generate_all_row_indices(lhs.size());
auto rhs_indices = generate_all_row_indices(rhs.size());
return cudf::type_dispatcher(lhs.type(),
column_comparator<true>{},
lhs,
rhs,
*lhs_indices,
*rhs_indices,
verbosity,
cudf::test::default_ulp);
}
/**
* @copydoc cudf::test::expect_columns_equivalent
*/
bool expect_columns_equivalent(cudf::column_view const& lhs,
cudf::column_view const& rhs,
debug_output_level verbosity,
size_type fp_ulps)
{
auto lhs_indices = generate_all_row_indices(lhs.size());
auto rhs_indices = generate_all_row_indices(rhs.size());
return cudf::type_dispatcher(lhs.type(),
column_comparator<false>{},
lhs,
rhs,
*lhs_indices,
*rhs_indices,
verbosity,
fp_ulps);
}
/**
* @copydoc cudf::test::expect_equal_buffers
*/
void expect_equal_buffers(void const* lhs, void const* rhs, std::size_t size_bytes)
{
if (size_bytes > 0) {
EXPECT_NE(nullptr, lhs);
EXPECT_NE(nullptr, rhs);
}
auto typed_lhs = static_cast<char const*>(lhs);
auto typed_rhs = static_cast<char const*>(rhs);
EXPECT_TRUE(thrust::equal(
rmm::exec_policy(cudf::default_stream_value), typed_lhs, typed_lhs + size_bytes, typed_rhs));
}
/**
* @copydoc cudf::test::bitmask_to_host
*/
std::vector<bitmask_type> bitmask_to_host(cudf::column_view const& c)
{
if (c.nullable()) {
auto num_bitmasks = num_bitmask_words(c.size());
std::vector<bitmask_type> host_bitmask(num_bitmasks);
if (c.offset() == 0) {
CUDF_CUDA_TRY(cudaMemcpy(host_bitmask.data(),
c.null_mask(),
num_bitmasks * sizeof(bitmask_type),
cudaMemcpyDeviceToHost));
} else {
auto mask = copy_bitmask(c.null_mask(), c.offset(), c.offset() + c.size());
CUDF_CUDA_TRY(cudaMemcpy(host_bitmask.data(),
mask.data(),
num_bitmasks * sizeof(bitmask_type),
cudaMemcpyDeviceToHost));
}
return host_bitmask;
} else {
return std::vector<bitmask_type>{};
}
}
namespace {
template <typename T, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
static auto numeric_to_string_precise(T value)
{
return std::to_string(value);
}
template <typename T, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
static auto numeric_to_string_precise(T value)
{
std::ostringstream o;
o << std::setprecision(std::numeric_limits<T>::max_digits10) << value;
return o.str();
}
static auto duration_suffix(cudf::duration_D) { return " days"; }
static auto duration_suffix(cudf::duration_s) { return " seconds"; }
static auto duration_suffix(cudf::duration_ms) { return " milliseconds"; }
static auto duration_suffix(cudf::duration_us) { return " microseconds"; }
static auto duration_suffix(cudf::duration_ns) { return " nanoseconds"; }
std::string get_nested_type_str(cudf::column_view const& view)
{
if (view.type().id() == cudf::type_id::LIST) {
lists_column_view lcv(view);
return cudf::jit::get_type_name(view.type()) + "<" + (get_nested_type_str(lcv.child())) + ">";
}
if (view.type().id() == cudf::type_id::STRUCT) {
std::ostringstream out;
out << cudf::jit::get_type_name(view.type()) + "<";
std::transform(view.child_begin(),
view.child_end(),
std::ostream_iterator<std::string>(out, ","),
[&out](auto const col) { return get_nested_type_str(col); });
out << ">";
return out.str();
}
return cudf::jit::get_type_name(view.type());
}
template <typename NestedColumnView>
std::string nested_offsets_to_string(NestedColumnView const& c, std::string const& delimiter = ", ")
{
column_view offsets = (c.parent()).child(NestedColumnView::offsets_column_index);
CUDF_EXPECTS(offsets.type().id() == type_id::INT32,
"Column does not appear to be an offsets column");
CUDF_EXPECTS(offsets.offset() == 0, "Offsets column has an internal offset!");
size_type output_size = c.size() + 1;
// the first offset value to normalize everything against
size_type first =
cudf::detail::get_value<size_type>(offsets, c.offset(), cudf::default_stream_value);
rmm::device_uvector<size_type> shifted_offsets(output_size, cudf::default_stream_value);
// normalize the offset values for the column offset
size_type const* d_offsets = offsets.head<size_type>() + c.offset();
thrust::transform(
rmm::exec_policy(cudf::default_stream_value),
d_offsets,
d_offsets + output_size,
shifted_offsets.begin(),
[first] __device__(int32_t offset) { return static_cast<size_type>(offset - first); });
auto const h_shifted_offsets = cudf::detail::make_host_vector_sync(shifted_offsets);
std::ostringstream buffer;
for (size_t idx = 0; idx < h_shifted_offsets.size(); idx++) {
buffer << h_shifted_offsets[idx];
if (idx < h_shifted_offsets.size() - 1) { buffer << delimiter; }
}
return buffer.str();
}
struct column_view_printer {
template <typename Element, std::enable_if_t<is_numeric<Element>()>* = nullptr>
void operator()(cudf::column_view const& col, std::vector<std::string>& out, std::string const&)
{
auto h_data = cudf::test::to_host<Element>(col);
out.resize(col.size());
if (col.nullable()) {
std::transform(thrust::make_counting_iterator(size_type{0}),
thrust::make_counting_iterator(col.size()),
out.begin(),
[&h_data](auto idx) {
return bit_is_set(h_data.second.data(), idx)
? numeric_to_string_precise(h_data.first[idx])
: std::string("NULL");
});
} else {
std::transform(h_data.first.begin(), h_data.first.end(), out.begin(), [](Element el) {
return numeric_to_string_precise(el);
});