Classes
class	cudf::approx_distinct_count
	Object-oriented HyperLogLog sketch for approximate distinct counting. More...

Functions
cudf::size_type	cudf::distinct_count (column_view const &input, null_policy null_handling, nan_policy nan_handling, rmm::cuda_stream_view stream=cudf::get_default_stream())
	Count the distinct elements in the column_view. More...

cudf::size_type	cudf::distinct_count (table_view const &input, null_equality nulls_equal=null_equality::EQUAL, rmm::cuda_stream_view stream=cudf::get_default_stream())
	Count the distinct rows in a table. More...

cudf::size_type	cudf::unique_count (column_view const &input, null_policy null_handling, nan_policy nan_handling, rmm::cuda_stream_view stream=cudf::get_default_stream())
	Count the number of consecutive groups of equivalent rows in a column. More...

cudf::size_type	cudf::unique_count (table_view const &input, null_equality nulls_equal=null_equality::EQUAL, rmm::cuda_stream_view stream=cudf::get_default_stream())
	Count the number of consecutive groups of equivalent rows in a table. More...

Detailed Description

Function Documentation

cudf::size_type cudf::distinct_count	(	column_view const &	input,
		null_policy	null_handling,
		nan_policy	nan_handling,
		rmm::cuda_stream_view	stream = `cudf::get_default_stream()`
	)

Count the distinct elements in the column_view.

If nulls_equal == nulls_equal::UNEQUAL, all nulls are distinct.

Given an input column_view, number of distinct 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 distinct count.

nulls are handled as equal.

Parameters

[in]	input	The column_view whose distinct 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
[in]	stream	CUDA stream used for device memory operations and kernel launches

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

Count the distinct rows in a table.

Parameters

[in]	input	Table whose distinct 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.
[in]	stream	CUDA stream used for device memory operations and kernel launches

cudf::size_type cudf::unique_count	(	column_view const &	input,
		null_policy	null_handling,
		nan_policy	nan_handling,
		rmm::cuda_stream_view	stream = `cudf::get_default_stream()`
	)

Count the number of consecutive groups of equivalent rows in a column.

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 count.

nulls are handled as equal.

Parameters

[in]	input	The column_view whose consecutive groups of equivalent rows will be counted
[in]	null_handling	flag to include or ignore `null` while counting
[in]	nan_handling	flag to consider `NaN==null` or not
[in]	stream	CUDA stream used for device memory operations and kernel launches

cudf::size_type cudf::unique_count	(	table_view const &	input,
		null_equality	nulls_equal = `null_equality::EQUAL`,
		rmm::cuda_stream_view	stream = `cudf::get_default_stream()`
	)

Count the number of consecutive groups of equivalent rows in a table.

Parameters

[in]	input	Table whose consecutive groups of equivalent 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.
[in]	stream	CUDA stream used for device memory operations and kernel launches