Files
file	stream_compaction.hpp
	Column APIs for filtering rows.

Enumerations
enum	cudf::duplicate_keep_option { cudf::duplicate_keep_option::KEEP_FIRST = 0, cudf::duplicate_keep_option::KEEP_LAST, cudf::duplicate_keep_option::KEEP_NONE }
	Choices for drop_duplicates API for retainment of duplicate rows. More...

Functions
std::unique_ptr< table >	cudf::drop_nulls (table_view const &input, std::vector< size_type > const &keys, cudf::size_type keep_threshold, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Filters a table to remove null elements with threshold count. More...

std::unique_ptr< table >	cudf::drop_nulls (table_view const &input, std::vector< size_type > const &keys, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Filters a table to remove null elements. More...

std::unique_ptr< table >	cudf::drop_nans (table_view const &input, std::vector< size_type > const &keys, cudf::size_type keep_threshold, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Filters a table to remove NANs with threshold count. More...

std::unique_ptr< table >	cudf::drop_nans (table_view const &input, std::vector< size_type > const &keys, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Filters a table to remove NANs. More...

std::unique_ptr< table >	cudf::apply_boolean_mask (table_view const &input, column_view const &boolean_mask, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Filters `input` using `boolean_mask` of boolean values as a mask. More...

std::unique_ptr< table >	cudf::drop_duplicates (table_view const &input, std::vector< size_type > const &keys, duplicate_keep_option keep, null_equality nulls_equal=null_equality::EQUAL, rmm::mr::device_memory_resource *mr=rmm::mr::get_current_device_resource())
	Create a new table without duplicate rows. More...

cudf::size_type	cudf::distinct_count (column_view const &input, null_policy null_handling, nan_policy nan_handling)
	Count the unique elements in the column_view. More...

cudf::size_type	cudf::distinct_count (table_view const &input, null_equality nulls_equal=null_equality::EQUAL)
	Count the unique rows in a table. More...

Detailed Description

Enumeration Type Documentation

◆ duplicate_keep_option

enum cudf::duplicate_keep_option

strong

Choices for drop_duplicates API for retainment of duplicate rows.

Enumerator
KEEP_FIRST	Keeps first duplicate row and unique rows.
KEEP_LAST	Keeps last duplicate row and unique rows.
KEEP_NONE	Keeps only unique rows are kept.

Definition at line 210 of file stream_compaction.hpp.

Function Documentation

◆ apply_boolean_mask()

std::unique_ptr<table> cudf::apply_boolean_mask	(	table_view const &	input,
		column_view const &	boolean_mask,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Filters input using boolean_mask of boolean values as a mask.

Given an input table_view and a mask column_view, an element i from each column_view of the input is copied to the corresponding output column if the corresponding element i in the mask is non-null and true. This operation is stable: the input order is preserved.

Note: if input.num_rows() is zero, there is no error, and an empty table is returned.

Exceptions

cudf::logic_error	if The `input` size and `boolean_mask` size mismatches.
cudf::logic_error	if `boolean_mask` is not `type_id::BOOL8` type.

Parameters

[in]	input	The input table_view to filter
[in]	boolean_mask	A nullable column_view of type type_id::BOOL8 used as a mask to filter the `input`.
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table containing copy of all rows of input passing the filter defined by boolean_mask.

◆ distinct_count() [1/2]

cudf::size_type cudf::distinct_count	(	column_view const &	input,
		null_policy	null_handling,
		nan_policy	nan_handling
	)

Count the unique elements in the column_view.

Given an input column_view, number of unique elements in this column_view is returned

If null_handling is null_policy::EXCLUDE and nan_handling is nan_policy::NAN_IS_NULL, both NaN and null values are ignored. If null_handling is null_policy::EXCLUDE and nan_handling is nan_policy::NAN_IS_VALID, only null is ignored, NaN is considered in unique count.

Parameters

[in]	input	The column_view whose unique elements will be counted.
[in]	null_handling	flag to include or ignore `null` while counting
[in]	nan_handling	flag to consider `NaN==null` or not.

Returns: number of unique elements

◆ distinct_count() [2/2]

cudf::size_type cudf::distinct_count	(	table_view const &	input,
		null_equality	nulls_equal = `null_equality::EQUAL`
	)

Count the unique rows in a table.

Parameters

[in]	input	Table whose unique rows will be counted.
[in]	nulls_equal	flag to denote if null elements should be considered equal nulls are not equal if null_equality::UNEQUAL

Returns: number of unique rows in the table

◆ drop_duplicates()

std::unique_ptr<table> cudf::drop_duplicates	(	table_view const &	input,
		std::vector< size_type > const &	keys,
		duplicate_keep_option	keep,
		null_equality	nulls_equal = `null_equality::EQUAL`,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Create a new table without duplicate rows.

Given an input table_view, each row is copied to output table if the corresponding row of keys columns is unique, where the definition of unique depends on the value of keep:

KEEP_FIRST: only the first of a sequence of duplicate rows is copied
KEEP_LAST: only the last of a sequence of duplicate rows is copied
KEEP_NONE: no duplicate rows are copied

Exceptions

cudf::logic_error if The input row size mismatches with keys.

Parameters

[in]	input	input table_view to copy only unique rows
[in]	keys	vector of indices representing key columns from `input`
[in]	keep	keep first entry, last entry, or no entries if duplicates found
[in]	nulls_equal	flag to denote nulls are equal if null_equality::EQUAL, nulls are not equal if null_equality::UNEQUAL
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table with unique rows as per specified keep.

◆ drop_nans() [1/2]

std::unique_ptr<table> cudf::drop_nans	(	table_view const &	input,
		std::vector< size_type > const &	keys,
		cudf::size_type	keep_threshold,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Filters a table to remove NANs with threshold count.

Filters the rows of the input considering specified columns indicated in keys for NANs. These key columns must be of floating-point type.

Given an input table_view, row i from the input columns is copied to the output if the same row i of keys has at least keep_threshold non-NAN elements.

This operation is stable: the input order is preserved in the output.

input   {col1: {1.0, 2.0, 3.0, NAN},
         col2: {4.0, null, NAN, NAN},
         col3: {7.0, NAN, NAN, NAN}}
keys = {0, 1, 2} // All columns
keep_threshold = 2
 
output {col1: {1.0, 2.0}
        col2: {4.0, null}
        col3: {7.0, NAN}}

Note: if input.num_rows() is zero, or keys is empty, there is no error, and an empty table is returned

Exceptions

cudf::logic_error if The keys columns are not floating-point type.

Parameters

[in]	input	The input `table_view` to filter.
[in]	keys	vector of indices representing key columns from `input`
[in]	keep_threshold	The minimum number of non-NAN elements in a row required to keep the row.
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table containing all rows of the input with at least keep_threshold non-NAN elements in keys.

◆ drop_nans() [2/2]

std::unique_ptr<table> cudf::drop_nans	(	table_view const &	input,
		std::vector< size_type > const &	keys,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Filters a table to remove NANs.

Filters the rows of the input considering specified columns indicated in keys for NANs. These key columns must be of floating-point type.

input   {col1: {1.0, 2.0, 3.0, NAN},
         col2: {4.0, null, NAN, NAN},
         col3: {null, NAN, NAN, NAN}}
keys = {0, 1, 2} // All columns
keep_threshold = 2
 
output {col1: {1.0}
        col2: {4.0}
        col3: {null}}

Same as drop_nans but defaults keep_threshold to the number of columns in keys.

Parameters

[in]	input	The input `table_view` to filter.
[in]	keys	vector of indices representing key columns from `input`
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table containing all rows of the input without NANs in the columns of keys.

◆ drop_nulls() [1/2]

std::unique_ptr<table> cudf::drop_nulls	(	table_view const &	input,
		std::vector< size_type > const &	keys,
		cudf::size_type	keep_threshold,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Filters a table to remove null elements with threshold count.

Filters the rows of the input considering specified columns indicated in keys for validity / null values.

Given an input table_view, row i from the input columns is copied to the output if the same row i of keys has at least keep_threshold non-null fields.

This operation is stable: the input order is preserved in the output.

Any non-nullable column in the input is treated as all non-null.

input   {col1: {1, 2,    3,    null},
         col2: {4, 5,    null, null},
         col3: {7, null, null, null}}
keys = {0, 1, 2} // All columns
keep_threshold = 2
 
output {col1: {1, 2}
        col2: {4, 5}
        col3: {7, null}}

Note: if input.num_rows() is zero, or keys is empty or has no nulls, there is no error, and an empty table is returned

Parameters

[in]	input	The input `table_view` to filter.
[in]	keys	vector of indices representing key columns from `input`
[in]	keep_threshold	The minimum number of non-null fields in a row required to keep the row.
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table containing all rows of the input with at least keep_threshold non-null fields in keys.

◆ drop_nulls() [2/2]

std::unique_ptr<table> cudf::drop_nulls	(	table_view const &	input,
		std::vector< size_type > const &	keys,
		rmm::mr::device_memory_resource *	mr = `rmm::mr::get_current_device_resource()`
	)

Filters a table to remove null elements.

Filters the rows of the input considering specified columns indicated in keys for validity / null values.

input   {col1: {1, 2,    3,    null},
         col2: {4, 5,    null, null},
         col3: {7, null, null, null}}
keys = {0, 1, 2} //All columns
 
output {col1: {1}
        col2: {4}
        col3: {7}}

Same as drop_nulls but defaults keep_threshold to the number of columns in keys.

Parameters

[in]	input	The input `table_view` to filter.
[in]	keys	vector of indices representing key columns from `input`
[in]	mr	Device memory resource used to allocate the returned table's device memory

Returns: Table containing all rows of the input without nulls in the columns of keys.

Files

Enumerations

Functions

Detailed Description

Enumeration Type Documentation

◆ duplicate_keep_option

Function Documentation

◆ apply_boolean_mask()

◆ distinct_count() [1/2]

◆ distinct_count() [2/2]

◆ drop_duplicates()

◆ drop_nans() [1/2]

◆ drop_nans() [2/2]

◆ drop_nulls() [1/2]

◆ drop_nulls() [2/2]