Compute Functions

Datum class

class Datum

Variant type for various Arrow C++ data structures.

Public Functions

Datum() = default

Empty datum, to be populated elsewhere.

int64_t TotalBufferSize() const

The sum of bytes in each buffer referenced by the datum Note: Scalars report a size of 0.

See also

arrow::util::TotalBufferSize for caveats

inline bool is_value() const

True if Datum contains a scalar or array-like data.

const std::shared_ptr<DataType> &type() const

The value type of the variant, if any.

Returns:

nullptr if no type

const std::shared_ptr<Schema> &schema() const

The schema of the variant, if any.

Returns:

nullptr if no schema

int64_t length() const

The value length of the variant, if any.

Returns:

kUnknownLength if no type

ArrayVector chunks() const

The array chunks of the variant, if any.

Returns:

empty if not arraylike

struct Empty

Abstract Function classes

void PrintTo(const FunctionOptions&, std::ostream*)
class FunctionOptionsType
#include <arrow/compute/function.h>

Extension point for defining options outside libarrow (but still within this project).

class FunctionOptions : public arrow::util::EqualityComparable<FunctionOptions>
#include <arrow/compute/function.h>

Base class for specifying options configuring a function’s behavior, such as error handling.

Subclassed by arrow::compute::ArithmeticOptions, arrow::compute::ArraySortOptions, arrow::compute::AssumeTimezoneOptions, arrow::compute::CastOptions, arrow::compute::CountOptions, arrow::compute::CumulativeSumOptions, arrow::compute::DayOfWeekOptions, arrow::compute::DictionaryEncodeOptions, arrow::compute::ElementWiseAggregateOptions, arrow::compute::ExtractRegexOptions, arrow::compute::FilterOptions, arrow::compute::IndexOptions, arrow::compute::JoinOptions, arrow::compute::ListSliceOptions, arrow::compute::MakeStructOptions, arrow::compute::MapLookupOptions, arrow::compute::MatchSubstringOptions, arrow::compute::ModeOptions, arrow::compute::NullOptions, arrow::compute::PadOptions, arrow::compute::PartitionNthOptions, arrow::compute::QuantileOptions, arrow::compute::RandomOptions, arrow::compute::RankOptions, arrow::compute::ReplaceSliceOptions, arrow::compute::ReplaceSubstringOptions, arrow::compute::RoundOptions, arrow::compute::RoundTemporalOptions, arrow::compute::RoundToMultipleOptions, arrow::compute::ScalarAggregateOptions, arrow::compute::SelectKOptions, arrow::compute::SetLookupOptions, arrow::compute::SliceOptions, arrow::compute::SortOptions, arrow::compute::SplitOptions, arrow::compute::SplitPatternOptions, arrow::compute::StrftimeOptions, arrow::compute::StrptimeOptions, arrow::compute::StructFieldOptions, arrow::compute::TakeOptions, arrow::compute::TDigestOptions, arrow::compute::TrimOptions, arrow::compute::Utf8NormalizeOptions, arrow::compute::VarianceOptions, arrow::compute::WeekOptions

Public Functions

Result<std::shared_ptr<Buffer>> Serialize() const

Serialize an options struct to a buffer.

Public Static Functions

static Result<std::unique_ptr<FunctionOptions>> Deserialize(const std::string &type_name, const Buffer &buffer)

Deserialize an options struct from a buffer.

Note: this will only look for type_name in the default FunctionRegistry; to use a custom FunctionRegistry, look up the FunctionOptionsType, then call FunctionOptionsType::Deserialize().

struct Arity
#include <arrow/compute/function.h>

Contains the number of required arguments for the function.

Naming conventions taken from https://en.wikipedia.org/wiki/Arity.

Public Members

int num_args

The number of required arguments (or the minimum number for varargs functions).

bool is_varargs = false

If true, then the num_args is the minimum number of required arguments.

Public Static Functions

static inline Arity Nullary()

A function taking no arguments.

static inline Arity Unary()

A function taking 1 argument.

static inline Arity Binary()

A function taking 2 arguments.

static inline Arity Ternary()

A function taking 3 arguments.

static inline Arity VarArgs(int min_args = 0)

A function taking a variable number of arguments.

Parameters:

min_args[in] the minimum number of arguments required when invoking the function

struct FunctionDoc
#include <arrow/compute/function.h>

Public Members

std::string summary

A one-line summary of the function, using a verb.

For example, “Add two numeric arrays or scalars”.

std::string description

A detailed description of the function, meant to follow the summary.

std::vector<std::string> arg_names

Symbolic names (identifiers) for the function arguments.

Some bindings may use this to generate nicer function signatures.

std::string options_class

Name of the options class, if any.

bool options_required

Whether options are required for function execution.

If false, then either the function does not have an options class or there is a usable default options value.

class FunctionExecutor
#include <arrow/compute/function.h>

An executor of a function with a preconfigured kernel.

Public Functions

virtual Status Init(const FunctionOptions *options = NULLPTR, ExecContext *exec_ctx = NULLPTR) = 0

Initialize or re-initialize the preconfigured kernel.

This method may be called zero or more times. Depending on how the FunctionExecutor was obtained, it may already have been initialized.

virtual Result<Datum> Execute(const std::vector<Datum> &args, int64_t length = -1) = 0

Execute the preconfigured kernel with arguments that must fit it.

The method requires the arguments be castable to the preconfigured types.

Parameters:
  • args[in] Arguments to execute the function on

  • length[in] Length of arguments batch or -1 to default it. If the function has no parameters, this determines the batch length, defaulting to 0. Otherwise, if the function is scalar, this must equal the argument batch’s inferred length or be -1 to default to it. This is ignored for vector functions.

class Function
#include <arrow/compute/function.h>

Base class for compute functions.

Function implementations contain a collection of “kernels” which are implementations of the function for specific argument types. Selecting a viable kernel for executing a function is referred to as “dispatching”.

Subclassed by arrow::compute::detail::FunctionImpl< KernelType >, arrow::compute::MetaFunction, arrow::compute::detail::FunctionImpl< HashAggregateKernel >, arrow::compute::detail::FunctionImpl< ScalarAggregateKernel >, arrow::compute::detail::FunctionImpl< ScalarKernel >, arrow::compute::detail::FunctionImpl< VectorKernel >

Public Types

enum Kind

The kind of function, which indicates in what contexts it is valid for use.

Values:

enumerator SCALAR

A function that performs scalar data operations on whole arrays of data.

Can generally process Array or Scalar values. The size of the output will be the same as the size (or broadcasted size, in the case of mixing Array and Scalar inputs) of the input.

enumerator VECTOR

A function with array input and output whose behavior depends on the values of the entire arrays passed, rather than the value of each scalar value.

enumerator SCALAR_AGGREGATE

A function that computes scalar summary statistics from array input.

enumerator HASH_AGGREGATE

A function that computes grouped summary statistics from array input and an array of group identifiers.

enumerator META

A function that dispatches to other functions and does not contain its own kernels.

Public Functions

inline const std::string &name() const

The name of the kernel. The registry enforces uniqueness of names.

inline Function::Kind kind() const

The kind of kernel, which indicates in what contexts it is valid for use.

inline const Arity &arity() const

Contains the number of arguments the function requires, or if the function accepts variable numbers of arguments.

inline const FunctionDoc &doc() const

Return the function documentation.

virtual int num_kernels() const = 0

Returns the number of registered kernels for this function.

virtual Result<const Kernel*> DispatchExact(const std::vector<TypeHolder> &types) const

Return a kernel that can execute the function given the exact argument types (without implicit type casts).

NB: This function is overridden in CastFunction.

virtual Result<const Kernel*> DispatchBest(std::vector<TypeHolder> *values) const

Return a best-match kernel that can execute the function given the argument types, after implicit casts are applied.

Parameters:

values[inout] Argument types. An element may be modified to indicate that the returned kernel only approximately matches the input value descriptors; callers are responsible for casting inputs to the type required by the kernel.

virtual Result<std::shared_ptr<FunctionExecutor>> GetBestExecutor(std::vector<TypeHolder> inputs) const

Get a function executor with a best-matching kernel.

The returned executor will by default work with the default FunctionOptions and KernelContext. If you want to change that, call FunctionExecutor::Init.

virtual Result<Datum> Execute(const std::vector<Datum> &args, const FunctionOptions *options, ExecContext *ctx) const

Execute the function eagerly with the passed input arguments with kernel dispatch, batch iteration, and memory allocation details taken care of.

If the options pointer is null, then default_options() will be used.

This function can be overridden in subclasses.

inline const FunctionOptions *default_options() const

Returns the default options for this function.

Whatever option semantics a Function has, implementations must guarantee that default_options() is valid to pass to Execute as options.

class ScalarFunction : public arrow::compute::detail::FunctionImpl<ScalarKernel>
#include <arrow/compute/function.h>

A function that executes elementwise operations on arrays or scalars, and therefore whose results generally do not depend on the order of the values in the arguments.

Accepts and returns arrays that are all of the same size. These functions roughly correspond to the functions used in SQL expressions.

Public Functions

Status AddKernel(std::vector<InputType> in_types, OutputType out_type, ArrayKernelExec exec, KernelInit init = NULLPTR)

Add a kernel with given input/output types, no required state initialization, preallocation for fixed-width types, and default null handling (intersect validity bitmaps of inputs).

Status AddKernel(ScalarKernel kernel)

Add a kernel (function implementation).

Returns error if the kernel’s signature does not match the function’s arity.

class VectorFunction : public arrow::compute::detail::FunctionImpl<VectorKernel>
#include <arrow/compute/function.h>

A function that executes general array operations that may yield outputs of different sizes or have results that depend on the whole array contents.

These functions roughly correspond to the functions found in non-SQL array languages like APL and its derivatives.

Public Functions

Status AddKernel(std::vector<InputType> in_types, OutputType out_type, ArrayKernelExec exec, KernelInit init = NULLPTR)

Add a simple kernel with given input/output types, no required state initialization, no data preallocation, and no preallocation of the validity bitmap.

Status AddKernel(VectorKernel kernel)

Add a kernel (function implementation).

Returns error if the kernel’s signature does not match the function’s arity.

class ScalarAggregateFunction : public arrow::compute::detail::FunctionImpl<ScalarAggregateKernel>
#include <arrow/compute/function.h>

Public Functions

Status AddKernel(ScalarAggregateKernel kernel)

Add a kernel (function implementation).

Returns error if the kernel’s signature does not match the function’s arity.

class HashAggregateFunction : public arrow::compute::detail::FunctionImpl<HashAggregateKernel>
#include <arrow/compute/function.h>

Public Functions

Status AddKernel(HashAggregateKernel kernel)

Add a kernel (function implementation).

Returns error if the kernel’s signature does not match the function’s arity.

class MetaFunction : public arrow::compute::Function
#include <arrow/compute/function.h>

A function that dispatches to other functions.

Must implement MetaFunction::ExecuteImpl.

For Array, ChunkedArray, and Scalar Datum kinds, may rely on the execution of concrete Function types, but must handle other Datum kinds on its own.

Public Functions

inline virtual int num_kernels() const override

Returns the number of registered kernels for this function.

virtual Result<Datum> Execute(const std::vector<Datum> &args, const FunctionOptions *options, ExecContext *ctx) const override

Execute the function eagerly with the passed input arguments with kernel dispatch, batch iteration, and memory allocation details taken care of.

If the options pointer is null, then default_options() will be used.

This function can be overridden in subclasses.

Function execution

Warning

doxygengroup: Cannot find group “compute-functions-executor” in doxygen xml output for project “arrow_cpp” from directory: ../../cpp/apidoc/xml

Function registry

class FunctionRegistry

A mutable central function registry for built-in functions as well as user-defined functions.

Functions are implementations of arrow::compute::Function.

Generally, each function contains kernels which are implementations of a function for a specific argument signature. After looking up a function in the registry, one can either execute it eagerly with Function::Execute or use one of the function’s dispatch methods to pick a suitable kernel for lower-level function execution.

Public Functions

Status CanAddFunction(std::shared_ptr<Function> function, bool allow_overwrite = false)

Check whether a new function can be added to the registry.

Returns:

Status::KeyError if a function with the same name is already registered.

Status AddFunction(std::shared_ptr<Function> function, bool allow_overwrite = false)

Add a new function to the registry.

Returns:

Status::KeyError if a function with the same name is already registered.

Status CanAddAlias(const std::string &target_name, const std::string &source_name)

Check whether an alias can be added for the given function name.

Returns:

Status::KeyError if the function with the given name is not registered.

Status AddAlias(const std::string &target_name, const std::string &source_name)

Add alias for the given function name.

Returns:

Status::KeyError if the function with the given name is not registered.

Status CanAddFunctionOptionsType(const FunctionOptionsType *options_type, bool allow_overwrite = false)

Check whether a new function options type can be added to the registry.

Returns:

Status::KeyError if a function options type with the same name is already registered.

Status AddFunctionOptionsType(const FunctionOptionsType *options_type, bool allow_overwrite = false)

Add a new function options type to the registry.

Returns:

Status::KeyError if a function options type with the same name is already registered.

Result<std::shared_ptr<Function>> GetFunction(const std::string &name) const

Retrieve a function by name from the registry.

std::vector<std::string> GetFunctionNames() const

Return vector of all entry names in the registry.

Helpful for displaying a manifest of available functions.

Result<const FunctionOptionsType*> GetFunctionOptionsType(const std::string &name) const

Retrieve a function options type by name from the registry.

int num_functions() const

The number of currently registered functions.

Public Static Functions

static std::unique_ptr<FunctionRegistry> Make()

Construct a new registry.

Most users only need to use the global registry.

static std::unique_ptr<FunctionRegistry> Make(FunctionRegistry *parent)

Construct a new nested registry with the given parent.

Most users only need to use the global registry. The returned registry never changes its parent, even when an operation allows overwritting.

FunctionRegistry *arrow::compute::GetFunctionRegistry()

Return the process-global function registry.

Convenience functions

Result<Datum> CallFunction(const std::string &func_name, const std::vector<Datum> &args, const FunctionOptions *options, ExecContext *ctx = NULLPTR)

One-shot invoker for all types of functions.

Does kernel dispatch, argument checking, iteration of ChunkedArray inputs, and wrapping of outputs.

Result<Datum> CallFunction(const std::string &func_name, const std::vector<Datum> &args, ExecContext *ctx = NULLPTR)

Variant of CallFunction which uses a function’s default options.

NB: Some functions require FunctionOptions be provided.

Result<Datum> CallFunction(const std::string &func_name, const ExecBatch &batch, const FunctionOptions *options, ExecContext *ctx = NULLPTR)

One-shot invoker for all types of functions.

Does kernel dispatch, argument checking, iteration of ChunkedArray inputs, and wrapping of outputs.

Result<Datum> CallFunction(const std::string &func_name, const ExecBatch &batch, ExecContext *ctx = NULLPTR)

Variant of CallFunction which uses a function’s default options.

NB: Some functions require FunctionOptions be provided.

Concrete options classes

enum class RoundMode : int8_t

Rounding and tie-breaking modes for round compute functions.

Additional details and examples are provided in compute.rst.

Values:

enumerator DOWN

Round to nearest integer less than or equal in magnitude (aka “floor”)

enumerator UP

Round to nearest integer greater than or equal in magnitude (aka “ceil”)

enumerator TOWARDS_ZERO

Get the integral part without fractional digits (aka “trunc”)

enumerator TOWARDS_INFINITY

Round negative values with DOWN rule and positive values with UP rule (aka “away from zero”)

enumerator HALF_DOWN

Round ties with DOWN rule (also called “round half towards negative infinity”)

enumerator HALF_UP

Round ties with UP rule (also called “round half towards positive infinity”)

enumerator HALF_TOWARDS_ZERO

Round ties with TOWARDS_ZERO rule (also called “round half away from infinity”)

enumerator HALF_TOWARDS_INFINITY

Round ties with TOWARDS_INFINITY rule (also called “round half away from zero”)

enumerator HALF_TO_EVEN

Round ties to nearest even integer.

enumerator HALF_TO_ODD

Round ties to nearest odd integer.

enum class CalendarUnit : int8_t

Values:

enumerator NANOSECOND
enumerator MICROSECOND
enumerator MILLISECOND
enumerator SECOND
enumerator MINUTE
enumerator HOUR
enumerator DAY
enumerator WEEK
enumerator MONTH
enumerator QUARTER
enumerator YEAR
enum CompareOperator

Values:

enumerator EQUAL
enumerator NOT_EQUAL
enumerator GREATER
enumerator GREATER_EQUAL
enumerator LESS
enumerator LESS_EQUAL
enum class SortOrder

Values:

enumerator Ascending

Arrange values in increasing order.

enumerator Descending

Arrange values in decreasing order.

enum class NullPlacement

Values:

enumerator AtStart

Place nulls and NaNs before any non-null values.

NaNs will come after nulls.

enumerator AtEnd

Place nulls and NaNs after any non-null values.

NaNs will come before nulls.

class ScalarAggregateOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control general scalar aggregate kernel behavior.

By default, null values are ignored (skip_nulls = true).

Public Functions

explicit ScalarAggregateOptions(bool skip_nulls = true, uint32_t min_count = 1)

Public Members

bool skip_nulls

If true (the default), null values are ignored.

Otherwise, if any value is null, emit null.

uint32_t min_count

If less than this many non-null values are observed, emit null.

Public Static Functions

static inline ScalarAggregateOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "ScalarAggregateOptions"
class CountOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control count aggregate kernel behavior.

By default, only non-null values are counted.

Public Types

enum CountMode

Values:

enumerator ONLY_VALID

Count only non-null values.

enumerator ONLY_NULL

Count only null values.

enumerator ALL

Count both non-null and null values.

Public Functions

explicit CountOptions(CountMode mode = CountMode::ONLY_VALID)

Public Members

CountMode mode

Public Static Functions

static inline CountOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "CountOptions"
class ModeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control Mode kernel behavior.

Returns top-n common values and counts. By default, returns the most common value and count.

Public Functions

explicit ModeOptions(int64_t n = 1, bool skip_nulls = true, uint32_t min_count = 0)

Public Members

int64_t n = 1
bool skip_nulls

If true (the default), null values are ignored.

Otherwise, if any value is null, emit null.

uint32_t min_count

If less than this many non-null values are observed, emit null.

Public Static Functions

static inline ModeOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "ModeOptions"
class VarianceOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control Delta Degrees of Freedom (ddof) of Variance and Stddev kernel.

The divisor used in calculations is N - ddof, where N is the number of elements. By default, ddof is zero, and population variance or stddev is returned.

Public Functions

explicit VarianceOptions(int ddof = 0, bool skip_nulls = true, uint32_t min_count = 0)

Public Members

int ddof = 0
bool skip_nulls

If true (the default), null values are ignored.

Otherwise, if any value is null, emit null.

uint32_t min_count

If less than this many non-null values are observed, emit null.

Public Static Functions

static inline VarianceOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "VarianceOptions"
class QuantileOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control Quantile kernel behavior.

By default, returns the median value.

Public Types

enum Interpolation

Interpolation method to use when quantile lies between two data points.

Values:

enumerator LINEAR
enumerator LOWER
enumerator HIGHER
enumerator NEAREST
enumerator MIDPOINT

Public Functions

explicit QuantileOptions(double q = 0.5, enum Interpolation interpolation = LINEAR, bool skip_nulls = true, uint32_t min_count = 0)
explicit QuantileOptions(std::vector<double> q, enum Interpolation interpolation = LINEAR, bool skip_nulls = true, uint32_t min_count = 0)

Public Members

std::vector<double> q

quantile must be between 0 and 1 inclusive

enum Interpolation interpolation
bool skip_nulls

If true (the default), null values are ignored.

Otherwise, if any value is null, emit null.

uint32_t min_count

If less than this many non-null values are observed, emit null.

Public Static Functions

static inline QuantileOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "QuantileOptions"
class TDigestOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control TDigest approximate quantile kernel behavior.

By default, returns the median value.

Public Functions

explicit TDigestOptions(double q = 0.5, uint32_t delta = 100, uint32_t buffer_size = 500, bool skip_nulls = true, uint32_t min_count = 0)
explicit TDigestOptions(std::vector<double> q, uint32_t delta = 100, uint32_t buffer_size = 500, bool skip_nulls = true, uint32_t min_count = 0)

Public Members

std::vector<double> q

quantile must be between 0 and 1 inclusive

uint32_t delta

compression parameter, default 100

uint32_t buffer_size

input buffer size, default 500

bool skip_nulls

If true (the default), null values are ignored.

Otherwise, if any value is null, emit null.

uint32_t min_count

If less than this many non-null values are observed, emit null.

Public Static Functions

static inline TDigestOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "TDigestOptions"
class IndexOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_aggregate.h>

Control Index kernel behavior.

Public Functions

explicit IndexOptions(std::shared_ptr<Scalar> value)
IndexOptions()

Public Members

std::shared_ptr<Scalar> value

Public Static Attributes

static constexpr const char kTypeName[] = "IndexOptions"
struct Aggregate
#include <arrow/compute/api_aggregate.h>

Configure a grouped aggregation.

Public Members

std::string function

the name of the aggregation function

std::shared_ptr<FunctionOptions> options

options for the aggregation function

FieldRef target
std::string name
class ArithmeticOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ArithmeticOptions(bool check_overflow = false)

Public Members

bool check_overflow

Public Static Attributes

static constexpr const char kTypeName[] = "ArithmeticOptions"
class ElementWiseAggregateOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ElementWiseAggregateOptions(bool skip_nulls = true)

Public Members

bool skip_nulls

Public Static Functions

static inline ElementWiseAggregateOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "ElementWiseAggregateOptions"
class RoundOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit RoundOptions(int64_t ndigits = 0, RoundMode round_mode = RoundMode::HALF_TO_EVEN)

Public Members

int64_t ndigits

Rounding precision (number of digits to round to)

RoundMode round_mode

Rounding and tie-breaking mode.

Public Static Functions

static inline RoundOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "RoundOptions"
class RoundTemporalOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit RoundTemporalOptions(int multiple = 1, CalendarUnit unit = CalendarUnit::DAY, bool week_starts_monday = true, bool ceil_is_strictly_greater = false, bool calendar_based_origin = false)

Public Members

int multiple

Number of units to round to.

CalendarUnit unit

The unit used for rounding of time.

bool week_starts_monday

What day does the week start with (Monday=true, Sunday=false)

bool ceil_is_strictly_greater

Enable this flag to return a rounded value that is strictly greater than the input.

For example: ceiling 1970-01-01T00:00:00 to 3 hours would yield 1970-01-01T03:00:00 if set to true and 1970-01-01T00:00:00 if set to false. This applies for ceiling only.

bool calendar_based_origin

By default time is rounded to a multiple of units since 1970-01-01T00:00:00.

By setting calendar_based_origin to true, time will be rounded to a number of units since the last greater calendar unit. For example: rounding to a multiple of days since the beginning of the month or to hours since the beginning of the day. Exceptions: week and quarter are not used as greater units, therefore days will will be rounded to the beginning of the month not week. Greater unit of week is year. Note that ceiling and rounding might change sorting order of an array near greater unit change. For example rounding YYYY-mm-dd 23:00:00 to 5 hours will ceil and round to YYYY-mm-dd+1 01:00:00 and floor to YYYY-mm-dd 20:00:00. On the other hand YYYY-mm-dd+1 00:00:00 will ceil, round and floor to YYYY-mm-dd+1 00:00:00. This can break the order of an already ordered array.

Public Static Functions

static inline RoundTemporalOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "RoundTemporalOptions"
class RoundToMultipleOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit RoundToMultipleOptions(double multiple = 1.0, RoundMode round_mode = RoundMode::HALF_TO_EVEN)
explicit RoundToMultipleOptions(std::shared_ptr<Scalar> multiple, RoundMode round_mode = RoundMode::HALF_TO_EVEN)

Public Members

std::shared_ptr<Scalar> multiple

Rounding scale (multiple to round to).

Should be a positive numeric scalar of a type compatible with the argument to be rounded. The cast kernel is used to convert the rounding multiple to match the result type.

RoundMode round_mode

Rounding and tie-breaking mode.

Public Static Functions

static inline RoundToMultipleOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "RoundToMultipleOptions"
class JoinOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Options for var_args_join.

Public Types

enum NullHandlingBehavior

How to handle null values. (A null separator always results in a null output.)

Values:

enumerator EMIT_NULL

A null in any input results in a null in the output.

enumerator SKIP

Nulls in inputs are skipped.

enumerator REPLACE

Nulls in inputs are replaced with the replacement string.

Public Functions

explicit JoinOptions(NullHandlingBehavior null_handling = EMIT_NULL, std::string null_replacement = "")

Public Members

NullHandlingBehavior null_handling
std::string null_replacement

Public Static Functions

static inline JoinOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "JoinOptions"
class MatchSubstringOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit MatchSubstringOptions(std::string pattern, bool ignore_case = false)
MatchSubstringOptions()

Public Members

std::string pattern

The exact substring (or regex, depending on kernel) to look for inside input values.

bool ignore_case

Whether to perform a case-insensitive match.

Public Static Attributes

static constexpr const char kTypeName[] = "MatchSubstringOptions"
class SplitOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit SplitOptions(int64_t max_splits = -1, bool reverse = false)

Public Members

int64_t max_splits

Maximum number of splits allowed, or unlimited when -1.

bool reverse

Start splitting from the end of the string (only relevant when max_splits != -1)

Public Static Attributes

static constexpr const char kTypeName[] = "SplitOptions"
class SplitPatternOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit SplitPatternOptions(std::string pattern, int64_t max_splits = -1, bool reverse = false)
SplitPatternOptions()

Public Members

std::string pattern

The exact substring to split on.

int64_t max_splits

Maximum number of splits allowed, or unlimited when -1.

bool reverse

Start splitting from the end of the string (only relevant when max_splits != -1)

Public Static Attributes

static constexpr const char kTypeName[] = "SplitPatternOptions"
class ReplaceSliceOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ReplaceSliceOptions(int64_t start, int64_t stop, std::string replacement)
ReplaceSliceOptions()

Public Members

int64_t start

Index to start slicing at.

int64_t stop

Index to stop slicing at.

std::string replacement

String to replace the slice with.

Public Static Attributes

static constexpr const char kTypeName[] = "ReplaceSliceOptions"
class ReplaceSubstringOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ReplaceSubstringOptions(std::string pattern, std::string replacement, int64_t max_replacements = -1)
ReplaceSubstringOptions()

Public Members

std::string pattern

Pattern to match, literal, or regular expression depending on which kernel is used.

std::string replacement

String to replace the pattern with.

int64_t max_replacements

Max number of substrings to replace (-1 means unbounded)

Public Static Attributes

static constexpr const char kTypeName[] = "ReplaceSubstringOptions"
class ExtractRegexOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ExtractRegexOptions(std::string pattern)
ExtractRegexOptions()

Public Members

std::string pattern

Regular expression with named capture fields.

Public Static Attributes

static constexpr const char kTypeName[] = "ExtractRegexOptions"
class SetLookupOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Options for IsIn and IndexIn functions.

Public Functions

explicit SetLookupOptions(Datum value_set, bool skip_nulls = false)
SetLookupOptions()

Public Members

Datum value_set

The set of values to look up input values into.

bool skip_nulls

Whether nulls in value_set count for lookup.

If true, any null in value_set is ignored and nulls in the input produce null (IndexIn) or false (IsIn) values in the output. If false, any null in value_set is successfully matched in the input.

Public Static Attributes

static constexpr const char kTypeName[] = "SetLookupOptions"
class StructFieldOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Options for struct_field function.

Public Functions

explicit StructFieldOptions(std::vector<int> indices)
explicit StructFieldOptions(std::initializer_list<int>)
explicit StructFieldOptions(FieldRef field_ref)
StructFieldOptions()

Public Members

FieldRef field_ref

The FieldRef specifying what to extract from struct or union.

Public Static Attributes

static constexpr const char kTypeName[] = "StructFieldOptions"
class StrptimeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit StrptimeOptions(std::string format, TimeUnit::type unit, bool error_is_null = false)
StrptimeOptions()

Public Members

std::string format

The desired format string.

TimeUnit::type unit

The desired time resolution.

bool error_is_null

Return null on parsing errors if true or raise if false.

Public Static Attributes

static constexpr const char kTypeName[] = "StrptimeOptions"
class StrftimeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit StrftimeOptions(std::string format, std::string locale = "C")
StrftimeOptions()

Public Members

std::string format

The desired format string.

std::string locale

The desired output locale string.

Public Static Attributes

static constexpr const char kTypeName[] = "StrftimeOptions"
static constexpr const char *kDefaultFormat = "%Y-%m-%dT%H:%M:%S"
class PadOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit PadOptions(int64_t width, std::string padding = " ")
PadOptions()

Public Members

int64_t width

The desired string length.

std::string padding

What to pad the string with. Should be one codepoint (Unicode)/byte (ASCII).

Public Static Attributes

static constexpr const char kTypeName[] = "PadOptions"
class TrimOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit TrimOptions(std::string characters)
TrimOptions()

Public Members

std::string characters

The individual characters to be trimmed from the string.

Public Static Attributes

static constexpr const char kTypeName[] = "TrimOptions"
class SliceOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit SliceOptions(int64_t start, int64_t stop = std::numeric_limits<int64_t>::max(), int64_t step = 1)
SliceOptions()

Public Members

int64_t start
int64_t stop
int64_t step

Public Static Attributes

static constexpr const char kTypeName[] = "SliceOptions"
class ListSliceOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit ListSliceOptions(int64_t start, std::optional<int64_t> stop = std::nullopt, int64_t step = 1, std::optional<bool> return_fixed_size_list = std::nullopt)
ListSliceOptions()

Public Members

int64_t start

The start of list slicing.

std::optional<int64_t> stop

Optional stop of list slicing. If not set, then slice to end. (NotImplemented)

int64_t step

Slicing step.

std::optional<bool> return_fixed_size_list

Public Static Attributes

static constexpr const char kTypeName[] = "ListSliceOptions"
class NullOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit NullOptions(bool nan_is_null = false)

Public Members

bool nan_is_null

Public Static Functions

static inline NullOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "NullOptions"
struct CompareOptions
#include <arrow/compute/api_scalar.h>

Public Functions

inline explicit CompareOptions(CompareOperator op)
inline CompareOptions()

Public Members

enum CompareOperator op
class MakeStructOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

MakeStructOptions(std::vector<std::string> n, std::vector<bool> r, std::vector<std::shared_ptr<const KeyValueMetadata>> m)
explicit MakeStructOptions(std::vector<std::string> n)
MakeStructOptions()

Public Members

std::vector<std::string> field_names

Names for wrapped columns.

std::vector<bool> field_nullability

Nullability bits for wrapped columns.

std::vector<std::shared_ptr<const KeyValueMetadata>> field_metadata

Metadata attached to wrapped columns.

Public Static Attributes

static constexpr const char kTypeName[] = "MakeStructOptions"
struct DayOfWeekOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit DayOfWeekOptions(bool count_from_zero = true, uint32_t week_start = 1)

Public Members

bool count_from_zero

Number days from 0 if true and from 1 if false.

uint32_t week_start

What day does the week start with (Monday=1, Sunday=7).

The numbering is unaffected by the count_from_zero parameter.

Public Static Functions

static inline DayOfWeekOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "DayOfWeekOptions"
struct AssumeTimezoneOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Used to control timestamp timezone conversion and handling ambiguous/nonexistent times.

Public Types

enum Ambiguous

How to interpret ambiguous local times that can be interpreted as multiple instants (normally two) due to DST shifts.

AMBIGUOUS_EARLIEST emits the earliest instant amongst possible interpretations. AMBIGUOUS_LATEST emits the latest instant amongst possible interpretations.

Values:

enumerator AMBIGUOUS_RAISE
enumerator AMBIGUOUS_EARLIEST
enumerator AMBIGUOUS_LATEST
enum Nonexistent

How to handle local times that do not exist due to DST shifts.

NONEXISTENT_EARLIEST emits the instant “just before” the DST shift instant in the given timestamp precision (for example, for a nanoseconds precision timestamp, this is one nanosecond before the DST shift instant). NONEXISTENT_LATEST emits the DST shift instant.

Values:

enumerator NONEXISTENT_RAISE
enumerator NONEXISTENT_EARLIEST
enumerator NONEXISTENT_LATEST

Public Functions

explicit AssumeTimezoneOptions(std::string timezone, Ambiguous ambiguous = AMBIGUOUS_RAISE, Nonexistent nonexistent = NONEXISTENT_RAISE)
AssumeTimezoneOptions()

Public Members

std::string timezone

Timezone to convert timestamps from.

Ambiguous ambiguous

How to interpret ambiguous local times (due to DST shifts)

Nonexistent nonexistent

How to interpret non-existent local times (due to DST shifts)

Public Static Attributes

static constexpr const char kTypeName[] = "AssumeTimezoneOptions"
struct WeekOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Functions

explicit WeekOptions(bool week_starts_monday = true, bool count_from_zero = false, bool first_week_is_fully_in_year = false)

Public Members

bool week_starts_monday

What day does the week start with (Monday=true, Sunday=false)

bool count_from_zero

Dates from current year that fall into last ISO week of the previous year return 0 if true and 52 or 53 if false.

bool first_week_is_fully_in_year

Must the first week be fully in January (true), or is a week that begins on December 29, 30, or 31 considered to be the first week of the new year (false)?

Public Static Functions

static inline WeekOptions Defaults()
static inline WeekOptions ISODefaults()
static inline WeekOptions USDefaults()

Public Static Attributes

static constexpr const char kTypeName[] = "WeekOptions"
struct Utf8NormalizeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Types

enum Form

Values:

enumerator NFC
enumerator NFKC
enumerator NFD
enumerator NFKD

Public Functions

explicit Utf8NormalizeOptions(Form form = NFC)

Public Members

Form form

The Unicode normalization form to apply.

Public Static Functions

static inline Utf8NormalizeOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "Utf8NormalizeOptions"
class RandomOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Public Types

enum Initializer

Values:

enumerator SystemRandom
enumerator Seed

Public Functions

RandomOptions(Initializer initializer, uint64_t seed)
RandomOptions()

Public Members

Initializer initializer

The type of initialization for random number generation - system or provided seed.

uint64_t seed

The seed value used to initialize the random number generation.

Public Static Functions

static inline RandomOptions FromSystemRandom()
static inline RandomOptions FromSeed(uint64_t seed)
static inline RandomOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "RandomOptions"
class MapLookupOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_scalar.h>

Options for map_lookup function.

Public Types

enum Occurrence

Values:

enumerator FIRST

Return the first matching value.

enumerator LAST

Return the last matching value.

enumerator ALL

Return all matching values.

Public Functions

explicit MapLookupOptions(std::shared_ptr<Scalar> query_key, Occurrence occurrence)
MapLookupOptions()

Public Members

std::shared_ptr<Scalar> query_key

The key to lookup in the map.

Occurrence occurrence

Whether to return the first, last, or all matching values.

Public Static Attributes

static constexpr const char kTypeName[] = "MapLookupOptions"
class FilterOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Public Types

enum NullSelectionBehavior

Configure the action taken when a slot of the selection mask is null.

Values:

enumerator DROP

The corresponding filtered value will be removed in the output.

enumerator EMIT_NULL

The corresponding filtered value will be null in the output.

Public Functions

explicit FilterOptions(NullSelectionBehavior null_selection = DROP)

Public Members

NullSelectionBehavior null_selection_behavior = DROP

Public Static Functions

static inline FilterOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "FilterOptions"
class TakeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Public Functions

explicit TakeOptions(bool boundscheck = true)

Public Members

bool boundscheck = true

Public Static Functions

static inline TakeOptions BoundsCheck()
static inline TakeOptions NoBoundsCheck()
static inline TakeOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "TakeOptions"
class DictionaryEncodeOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Options for the dictionary encode function.

Public Types

enum NullEncodingBehavior

Configure how null values will be encoded.

Values:

enumerator ENCODE

The null value will be added to the dictionary with a proper index.

enumerator MASK

The null value will be masked in the indices array.

Public Functions

explicit DictionaryEncodeOptions(NullEncodingBehavior null_encoding = MASK)

Public Members

NullEncodingBehavior null_encoding_behavior = MASK

Public Static Functions

static inline DictionaryEncodeOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "DictionaryEncodeOptions"
class SortKey : public arrow::util::EqualityComparable<SortKey>
#include <arrow/compute/api_vector.h>

One sort key for PartitionNthIndices (TODO) and SortIndices.

Public Functions

inline explicit SortKey(FieldRef target, SortOrder order = SortOrder::Ascending)
bool Equals(const SortKey &other) const
std::string ToString() const

Public Members

FieldRef target

A FieldRef targetting the sort column.

SortOrder order

How to order by this sort key.

class ArraySortOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Public Functions

explicit ArraySortOptions(SortOrder order = SortOrder::Ascending, NullPlacement null_placement = NullPlacement::AtEnd)

Public Members

SortOrder order

Sorting order.

NullPlacement null_placement

Whether nulls and NaNs are placed at the start or at the end.

Public Static Functions

static inline ArraySortOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "ArraySortOptions"
class SortOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Public Functions

explicit SortOptions(std::vector<SortKey> sort_keys = {}, NullPlacement null_placement = NullPlacement::AtEnd)

Public Members

std::vector<SortKey> sort_keys

Column key(s) to order by and how to order by these sort keys.

NullPlacement null_placement

Whether nulls and NaNs are placed at the start or at the end.

Public Static Functions

static inline SortOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "SortOptions"
class SelectKOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

SelectK options.

Public Functions

explicit SelectKOptions(int64_t k = -1, std::vector<SortKey> sort_keys = {})

Public Members

int64_t k

The number of k elements to keep.

std::vector<SortKey> sort_keys

Column key(s) to order by and how to order by these sort keys.

Public Static Functions

static inline SelectKOptions Defaults()
static inline SelectKOptions TopKDefault(int64_t k, std::vector<std::string> key_names = {})
static inline SelectKOptions BottomKDefault(int64_t k, std::vector<std::string> key_names = {})

Public Static Attributes

static constexpr const char kTypeName[] = "SelectKOptions"
class RankOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Rank options.

Public Types

enum Tiebreaker

Configure how ties between equal values are handled.

Values:

enumerator Min

Ties get the smallest possible rank in sorted order.

enumerator Max

Ties get the largest possible rank in sorted order.

enumerator First

Ranks are assigned in order of when ties appear in the input.

This ensures the ranks are a stable permutation of the input.

enumerator Dense

The ranks span a dense [1, M] interval where M is the number of distinct values in the input.

Public Functions

explicit RankOptions(std::vector<SortKey> sort_keys = {}, NullPlacement null_placement = NullPlacement::AtEnd, Tiebreaker tiebreaker = RankOptions::First)
inline explicit RankOptions(SortOrder order, NullPlacement null_placement = NullPlacement::AtEnd, Tiebreaker tiebreaker = RankOptions::First)

Convenience constructor for array inputs.

Public Members

std::vector<SortKey> sort_keys

Column key(s) to order by and how to order by these sort keys.

NullPlacement null_placement

Whether nulls and NaNs are placed at the start or at the end.

Tiebreaker tiebreaker

Tiebreaker for dealing with equal values in ranks.

Public Static Functions

static inline RankOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "RankOptions"
class PartitionNthOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Partitioning options for NthToIndices.

Public Functions

explicit PartitionNthOptions(int64_t pivot, NullPlacement null_placement = NullPlacement::AtEnd)
inline PartitionNthOptions()

Public Members

int64_t pivot

The index into the equivalent sorted array of the partition pivot element.

NullPlacement null_placement

Whether nulls and NaNs are partitioned at the start or at the end.

Public Static Attributes

static constexpr const char kTypeName[] = "PartitionNthOptions"
class CumulativeSumOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/api_vector.h>

Options for cumulative sum function.

Public Functions

explicit CumulativeSumOptions(double start = 0, bool skip_nulls = false, bool check_overflow = false)
explicit CumulativeSumOptions(std::shared_ptr<Scalar> start, bool skip_nulls = false, bool check_overflow = false)

Public Members

std::shared_ptr<Scalar> start

Optional starting value for cumulative operation computation.

bool skip_nulls = false

If true, nulls in the input are ignored and produce a corresponding null output.

When false, the first null encountered is propagated through the remaining output.

bool check_overflow = false

When true, returns an Invalid Status when overflow is detected.

Public Static Functions

static inline CumulativeSumOptions Defaults()

Public Static Attributes

static constexpr const char kTypeName[] = "CumulativeSumOptions"
class CastOptions : public arrow::compute::FunctionOptions
#include <arrow/compute/cast.h>

Public Functions

explicit CastOptions(bool safe = true)

Public Members

TypeHolder to_type
bool allow_int_overflow
bool allow_time_truncate
bool allow_time_overflow
bool allow_decimal_truncate
bool allow_float_truncate
bool allow_invalid_utf8

Public Static Functions

static inline CastOptions Safe(TypeHolder to_type = {})
static inline CastOptions Unsafe(TypeHolder to_type = {})

Public Static Attributes

static constexpr const char kTypeName[] = "CastOptions"

Streaming Execution

Streaming Execution Operators

enum class arrow::compute::JoinType

Values:

enumerator LEFT_SEMI
enumerator RIGHT_SEMI
enumerator LEFT_ANTI
enumerator RIGHT_ANTI
enumerator INNER
enumerator LEFT_OUTER
enumerator RIGHT_OUTER
enumerator FULL_OUTER
enum class arrow::compute::JoinKeyCmp

Values:

enumerator EQ
enumerator IS
using ArrayVectorIteratorMaker = std::function<Iterator<std::shared_ptr<ArrayVector>>()>
using ExecBatchIteratorMaker = std::function<Iterator<std::shared_ptr<ExecBatch>>()>
using RecordBatchIteratorMaker = std::function<Iterator<std::shared_ptr<RecordBatch>>()>
constexpr int32_t kDefaultBackpressureHighBytes = 1 << 30
constexpr int32_t kDefaultBackpressureLowBytes = 1 << 28
class ExecNodeOptions
#include <arrow/compute/exec/options.h>

Subclassed by arrow::compute::AggregateNodeOptions, arrow::compute::AsofJoinNodeOptions, arrow::compute::ConsumingSinkNodeOptions, arrow::compute::FilterNodeOptions, arrow::compute::HashJoinNodeOptions, arrow::compute::ProjectNodeOptions, arrow::compute::SchemaSourceNodeOptions< ItMaker >, arrow::compute::SinkNodeOptions, arrow::compute::SourceNodeOptions, arrow::compute::TableSinkNodeOptions, arrow::compute::TableSourceNodeOptions, arrow::dataset::ScanNodeOptions, arrow::dataset::ScanV2Options, arrow::dataset::WriteNodeOptions, arrow::compute::SchemaSourceNodeOptions< ArrayVectorIteratorMaker >, arrow::compute::SchemaSourceNodeOptions< ExecBatchIteratorMaker >, arrow::compute::SchemaSourceNodeOptions< RecordBatchIteratorMaker >

Public Functions

virtual ~ExecNodeOptions() = default
class SourceNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Adapt an AsyncGenerator<ExecBatch> as a source node.

plan->exec_context()->executor() will be used to parallelize pushing to outputs, if provided.

Public Functions

inline SourceNodeOptions(std::shared_ptr<Schema> output_schema, std::function<Future<std::optional<ExecBatch>>()> generator)

Public Members

std::shared_ptr<Schema> output_schema
std::function< Future< std::optional< ExecBatch > >)> generator

Public Static Functions

static Result<std::shared_ptr<SourceNodeOptions>> FromTable(const Table &table, arrow::internal::Executor*)
class TableSourceNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

An extended Source node which accepts a table.

Public Functions

inline TableSourceNodeOptions(std::shared_ptr<Table> table, int64_t max_batch_size = kDefaultMaxBatchSize)

Public Members

std::shared_ptr<Table> table
int64_t max_batch_size

Public Static Attributes

static constexpr int64_t kDefaultMaxBatchSize = 1 << 20
template<typename ItMaker>
class SchemaSourceNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

An extended Source node which accepts a schema.

ItMaker is a maker of an iterator of tabular data.

Public Functions

inline SchemaSourceNodeOptions(std::shared_ptr<Schema> schema, ItMaker it_maker, arrow::internal::Executor *io_executor = NULLPTR)

Public Members

std::shared_ptr<Schema> schema

The schema of the record batches from the iterator.

ItMaker it_maker

A maker of an iterator which acts as the data source.

arrow::internal::Executor *io_executor

The executor to use for scanning the iterator.

Defaults to the default I/O executor.

class ArrayVectorSourceNodeOptions : public arrow::compute::SchemaSourceNodeOptions<ArrayVectorIteratorMaker>
#include <arrow/compute/exec/options.h>

An extended Source node which accepts a schema and array-vectors.

class ExecBatchSourceNodeOptions : public arrow::compute::SchemaSourceNodeOptions<ExecBatchIteratorMaker>
#include <arrow/compute/exec/options.h>

An extended Source node which accepts a schema and exec-batches.

class RecordBatchSourceNodeOptions : public arrow::compute::SchemaSourceNodeOptions<RecordBatchIteratorMaker>
#include <arrow/compute/exec/options.h>

An extended Source node which accepts a schema and record-batches.

class FilterNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which excludes some rows from batches passed through it.

filter_expression will be evaluated against each batch which is pushed to this node. Any rows for which filter_expression does not evaluate to true will be excluded in the batch emitted by this node.

Public Functions

inline explicit FilterNodeOptions(Expression filter_expression)

Public Members

Expression filter_expression
class ProjectNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which executes expressions on input batches, producing new batches.

Each expression will be evaluated against each batch which is pushed to this node to produce a corresponding output column.

If names are not provided, the string representations of exprs will be used.

Public Functions

inline explicit ProjectNodeOptions(std::vector<Expression> expressions, std::vector<std::string> names = {})

Public Members

std::vector<Expression> expressions
std::vector<std::string> names
class AggregateNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which aggregates input batches, optionally grouped by keys.

If the keys attribute is a non-empty vector, then each aggregate in aggregates is expected to be a HashAggregate function. If the keys attribute is an empty vector, then each aggregate is assumed to be a ScalarAggregate function.

Public Functions

inline explicit AggregateNodeOptions(std::vector<Aggregate> aggregates, std::vector<FieldRef> keys = {})

Public Members

std::vector<Aggregate> aggregates
std::vector<FieldRef> keys
class BackpressureMonitor
#include <arrow/compute/exec/options.h>

Public Functions

virtual ~BackpressureMonitor() = default
virtual uint64_t bytes_in_use() const = 0
virtual bool is_paused() const = 0
struct BackpressureOptions
#include <arrow/compute/exec/options.h>

Options to control backpressure behavior.

Public Functions

inline BackpressureOptions()

Create default options that perform no backpressure.

inline BackpressureOptions(uint64_t resume_if_below, uint64_t pause_if_above)

Create options that will perform backpressure.

Parameters:
  • resume_if_below – The producer should resume producing if the backpressure queue has fewer than resume_if_below items.

  • pause_if_above – The producer should pause producing if the backpressure queue has more than pause_if_above items

inline bool should_apply_backpressure() const

Public Members

uint64_t resume_if_below
uint64_t pause_if_above

Public Static Functions

static inline BackpressureOptions DefaultBackpressure()
class SinkNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Add a sink node which forwards to an AsyncGenerator<ExecBatch>

Emitted batches will not be ordered.

Subclassed by arrow::compute::OrderBySinkNodeOptions, arrow::compute::SelectKSinkNodeOptions

Public Functions

inline explicit SinkNodeOptions(std::function<Future<std::optional<ExecBatch>>()> *generator, BackpressureOptions backpressure = {}, BackpressureMonitor **backpressure_monitor = NULLPTR)

Public Members

std::function< Future< std::optional< ExecBatch > >)> * generator

A pointer to a generator of batches.

This will be set when the node is added to the plan and should be used to consume data from the plan. If this function is not called frequently enough then the sink node will start to accumulate data and may apply backpressure.

BackpressureOptions backpressure

Options to control when to apply backpressure.

This is optional, the default is to never apply backpressure. If the plan is not consumed quickly enough the system may eventually run out of memory.

BackpressureMonitor **backpressure_monitor

A pointer to a backpressure monitor.

This will be set when the node is added to the plan. This can be used to inspect the amount of data currently queued in the sink node. This is an optional utility and backpressure can be applied even if this is not used.

class BackpressureControl
#include <arrow/compute/exec/options.h>

Control used by a SinkNodeConsumer to pause & resume.

Callers should ensure that they do not call Pause and Resume simultaneously and they should sequence things so that a call to Pause() is always followed by an eventual call to Resume()

Public Functions

virtual ~BackpressureControl() = default
virtual void Pause() = 0

Ask the input to pause.

This is best effort, batches may continue to arrive Must eventually be followed by a call to Resume() or deadlock will occur

virtual void Resume() = 0

Ask the input to resume.

class SinkNodeConsumer
#include <arrow/compute/exec/options.h>

Subclassed by arrow::compute::TableSinkNodeConsumer

Public Functions

virtual ~SinkNodeConsumer() = default
virtual Status Init(const std::shared_ptr<Schema> &schema, BackpressureControl *backpressure_control, ExecPlan *plan) = 0

Prepare any consumer state.

This will be run once the schema is finalized as the plan is starting and before any calls to Consume. A common use is to save off the schema so that batches can be interpreted. TODO(ARROW-17837) Move ExecPlan* plan to query context

virtual Status Consume(ExecBatch batch) = 0

Consume a batch of data.

virtual Future Finish() = 0

Signal to the consumer that the last batch has been delivered.

The returned future should only finish when all outstanding tasks have completed

class ConsumingSinkNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Add a sink node which consumes data within the exec plan run.

Public Functions

inline explicit ConsumingSinkNodeOptions(std::shared_ptr<SinkNodeConsumer> consumer, std::vector<std::string> names = {})

Public Members

std::shared_ptr<SinkNodeConsumer> consumer
std::vector<std::string> names

Names to rename the sink’s schema fields to.

If specified then names must be provided for all fields. Currently, only a flat schema is supported (see ARROW-15901).

class OrderBySinkNodeOptions : public arrow::compute::SinkNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which sorts rows passed through it.

All batches pushed to this node will be accumulated, then sorted, by the given fields. Then sorted batches will be forwarded to the generator in sorted order.

Public Functions

inline explicit OrderBySinkNodeOptions(SortOptions sort_options, std::function<Future<std::optional<ExecBatch>>()> *generator)

Public Members

SortOptions sort_options
class HashJoinNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which implements join operation using hash join strategy.

Public Functions

inline HashJoinNodeOptions(JoinType in_join_type, std::vector<FieldRef> in_left_keys, std::vector<FieldRef> in_right_keys, Expression filter = literal(true), std::string output_suffix_for_left = default_output_suffix_for_left, std::string output_suffix_for_right = default_output_suffix_for_right, bool disable_bloom_filter = false)
inline HashJoinNodeOptions(std::vector<FieldRef> in_left_keys, std::vector<FieldRef> in_right_keys)
inline HashJoinNodeOptions(JoinType join_type, std::vector<FieldRef> left_keys, std::vector<FieldRef> right_keys, std::vector<FieldRef> left_output, std::vector<FieldRef> right_output, Expression filter = literal(true), std::string output_suffix_for_left = default_output_suffix_for_left, std::string output_suffix_for_right = default_output_suffix_for_right, bool disable_bloom_filter = false)
inline HashJoinNodeOptions(JoinType join_type, std::vector<FieldRef> left_keys, std::vector<FieldRef> right_keys, std::vector<FieldRef> left_output, std::vector<FieldRef> right_output, std::vector<JoinKeyCmp> key_cmp, Expression filter = literal(true), std::string output_suffix_for_left = default_output_suffix_for_left, std::string output_suffix_for_right = default_output_suffix_for_right, bool disable_bloom_filter = false)
HashJoinNodeOptions() = default

Public Members

JoinType join_type = JoinType::INNER
std::vector<FieldRef> left_keys
std::vector<FieldRef> right_keys
bool output_all = false
std::vector<FieldRef> left_output
std::vector<FieldRef> right_output
std::vector<JoinKeyCmp> key_cmp
std::string output_suffix_for_left
std::string output_suffix_for_right
Expression filter = literal(true)
bool disable_bloom_filter = false

Public Static Attributes

static constexpr const char *default_output_suffix_for_left = ""
static constexpr const char *default_output_suffix_for_right = ""
class AsofJoinNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which implements asof join operation.

Note, this API is experimental and will change in the future

This node takes one left table and any number of right tables, and asof joins them together. Batches produced by each input must be ordered by the “on” key. This node will output one row for each row in the left table.

Public Functions

inline AsofJoinNodeOptions(FieldRef on_key, std::vector<FieldRef> by_key, int64_t tolerance)

Public Members

FieldRef on_key

“on” key for the join.

All inputs tables must be sorted by the “on” key. Must be a single field of a common type. Inexact match is used on the “on” key. i.e., a row is considered match iff left_on - tolerance <= right_on <= left_on. Currently, the “on” key must be of an integer, date, or timestamp type.

std::vector<FieldRef> by_key

“by” key for the join.

All input tables must have the “by” key. Exact equality is used for the “by” key. Currently, the “by” key must be of an integer, date, timestamp, or base-binary type

int64_t tolerance

Tolerance for inexact “on” key matching.

Must be non-negative.

The tolerance is interpreted in the same units as the “on” key.

class SelectKSinkNodeOptions : public arrow::compute::SinkNodeOptions
#include <arrow/compute/exec/options.h>

Make a node which select top_k/bottom_k rows passed through it.

All batches pushed to this node will be accumulated, then selected, by the given fields. Then sorted batches will be forwarded to the generator in sorted order.

Public Functions

inline explicit SelectKSinkNodeOptions(SelectKOptions select_k_options, std::function<Future<std::optional<ExecBatch>>()> *generator)

Public Members

SelectKOptions select_k_options

SelectK options.

class TableSinkNodeOptions : public arrow::compute::ExecNodeOptions
#include <arrow/compute/exec/options.h>

Adapt a Table as a sink node.

obtains the output of an execution plan to a table pointer.

Public Functions

inline explicit TableSinkNodeOptions(std::shared_ptr<Table> *output_table)

Public Members

std::shared_ptr<Table> *output_table
constexpr int kDefaultBackgroundMaxQ = 32
constexpr int kDefaultBackgroundQRestart = 16
ExecFactoryRegistry *default_exec_factory_registry()

The default registry, which includes built-in factories.

inline Result<ExecNode*> MakeExecNode(const std::string &factory_name, ExecPlan *plan, std::vector<ExecNode*> inputs, const ExecNodeOptions &options, ExecFactoryRegistry *registry = default_exec_factory_registry())

Construct an ExecNode using the named factory.

Result<std::shared_ptr<Table>> DeclarationToTable(Declaration declaration, ExecContext *exec_context = default_exec_context())

Utility method to run a declaration and collect the results into a table.

This method will add a sink node to the declaration to collect results into a table. It will then create an ExecPlan from the declaration, start the exec plan, block until the plan has finished, and return the created table.

Future<std::shared_ptr<Table>> DeclarationToTableAsync(Declaration declaration, ExecContext *exec_context = default_exec_context())

Asynchronous version of.

Result<std::vector<ExecBatch>> DeclarationToExecBatches(Declaration declaration, ExecContext *exec_context = default_exec_context())

Utility method to run a declaration and collect the results into ExecBatch vector.

See also

DeclarationToTable for details

Future<std::vector<ExecBatch>> DeclarationToExecBatchesAsync(Declaration declaration, ExecContext *exec_context = default_exec_context())

Asynchronous version of.

Result<std::vector<std::shared_ptr<RecordBatch>>> DeclarationToBatches(Declaration declaration, ExecContext *exec_context = default_exec_context())

Utility method to run a declaration and collect the results into a vector.

See also

DeclarationToTable for details

Future<std::vector<std::shared_ptr<RecordBatch>>> DeclarationToBatchesAsync(Declaration declaration, ExecContext *exec_context = default_exec_context())

Asynchronous version of.

std::shared_ptr<RecordBatchReader> MakeGeneratorReader(std::shared_ptr<Schema>, std::function<Future<std::optional<ExecBatch>>()>, MemoryPool*)

Wrap an ExecBatch generator in a RecordBatchReader.

The RecordBatchReader does not impose any ordering on emitted batches.

Result< std::function< Future< std::optional< ExecBatch > >)> > MakeReaderGenerator (std::shared_ptr< RecordBatchReader > reader, arrow::internal::Executor *io_executor, int max_q=kDefaultBackgroundMaxQ, int q_restart=kDefaultBackgroundQRestart)

Make a generator of RecordBatchReaders.

Useful as a source node for an Exec plan

inline bool operator==(const ExecBatch &l, const ExecBatch &r)
inline bool operator!=(const ExecBatch &l, const ExecBatch &r)
void PrintTo(const ExecBatch&, std::ostream*)
class ExecPlan : public std::enable_shared_from_this<ExecPlan>
#include <arrow/compute/exec/exec_plan.h>

Public Types

using NodeVector = std::vector<ExecNode*>

Public Functions

virtual ~ExecPlan() = default
inline ExecContext *exec_context() const
ExecNode *AddNode(std::unique_ptr<ExecNode> node)
template<typename Node, typename ...Args>
inline Node *EmplaceNode(Args&&... args)
size_t GetThreadIndex()

Returns the index of the current thread.

size_t max_concurrency() const

Returns the maximum number of threads that the plan could use.

GetThreadIndex will always return something less than this, so it is safe to e.g. make an array of thread-locals off this.

Result<Future<>> BeginExternalTask()

Start an external task.

This should be avoided if possible. It is kept in for now for legacy purposes. This should be called before the external task is started. If a valid future is returned then it should be marked complete when the external task has finished.

Returns:

an invalid future if the plan has already ended, otherwise this returns a future that must be completed when the external task finishes.

Status ScheduleTask(std::function<Status()> fn)

Add a single function as a task to the plan’s task group.

Parameters:

fn – The task to run. Takes no arguments and returns a Status.

Status ScheduleTask(std::function<Status(size_t)> fn)

Add a single function as a task to the plan’s task group.

Parameters:

fn – The task to run. Takes the thread index and returns a Status.

int RegisterTaskGroup(std::function<Status(size_t, int64_t)> task, std::function<Status(size_t)> on_finished)

Register a “parallel for” task group with the scheduler.

Must be called inside of ExecNode::Init.

Parameters:
  • task – The function implementing the task. Takes the thread_index and the task index.

  • on_finished – The function that gets run once all tasks have been completed. Takes the thread_index.

Status StartTaskGroup(int task_group_id, int64_t num_tasks)

Start the task group with the specified ID.

This can only be called once per task_group_id.

Parameters:
  • task_group_id – The ID of the task group to run

  • num_tasks – The number of times to run the task

util::AsyncTaskScheduler *async_scheduler()
const NodeVector &sources() const

The initial inputs.

const NodeVector &sinks() const

The final outputs.

Status Validate()
Status StartProducing()

Start producing on all nodes.

Nodes are started in reverse topological order, such that any node is started before all of its inputs.

void StopProducing()

Stop producing on all nodes.

Nodes are stopped in topological order, such that any node is stopped before all of its outputs.

Future finished()

A future which will be marked finished when all nodes have stopped producing.

bool HasMetadata() const

Return whether the plan has non-empty metadata.

std::shared_ptr<const KeyValueMetadata> metadata() const

Return the plan’s attached metadata.

inline bool UseLegacyBatching() const

Should the plan use a legacy batching strategy.

This is currently in place only to support the Scanner::ToTable method. This method relies on batch indices from the scanner remaining consistent. This is impractical in the ExecPlan which might slice batches as needed (e.g. for a join)

However, it still works for simple plans and this is the only way we have at the moment for maintaining implicit order.

inline void SetUseLegacyBatching(bool value)
std::string ToString() const

Public Static Functions

static Result<std::shared_ptr<ExecPlan>> Make(ExecContext* = default_exec_context(), std::shared_ptr<const KeyValueMetadata> metadata = NULLPTR)

Make an empty exec plan.

Public Static Attributes

static const uint32_t kMaxBatchSize = 1 << 15
class ExecNode
#include <arrow/compute/exec/exec_plan.h>

Subclassed by arrow::compute::MapNode

Public Types

using NodeVector = std::vector<ExecNode*>

Public Functions

virtual ~ExecNode() = default
virtual const char *kind_name() const = 0
inline int num_inputs() const
inline int num_outputs() const
inline const NodeVector &inputs() const

This node’s predecessors in the exec plan.

inline const std::vector<std::string> &input_labels() const

Labels identifying the function of each input.

inline const NodeVector &outputs() const

This node’s successors in the exec plan.

inline const std::shared_ptr<Schema> &output_schema() const

The datatypes for batches produced by this node.

inline ExecPlan *plan()

This node’s exec plan.

inline const std::string &label() const

An optional label, for display and debugging.

There is no guarantee that this value is non-empty or unique.

inline void SetLabel(std::string label)
Status Validate() const
virtual void InputReceived(ExecNode *input, ExecBatch batch) = 0

Upstream API: These functions are called by input nodes that want to inform this node about an updated condition (a new input batch, an error, an impeding end of stream).

Implementation rules:

virtual void ErrorReceived(ExecNode *input, Status error) = 0

Signal error to ExecNode.

virtual void InputFinished(ExecNode *input, int total_batches) = 0

Mark the inputs finished after the given number of batches.

This may be called before all inputs are received. This simply fixes the total number of incoming batches for an input, so that the ExecNode knows when it has received all input, regardless of order.

virtual Status Init()

Perform any needed initialization.

This hook performs any actions in between creation of ExecPlan and the call to StartProducing. An example could be Bloom filter pushdown. The order of ExecNodes that executes this method is undefined, but the calls are made synchronously.

At this point a node can rely on all inputs & outputs (and the input schemas) being well defined.

virtual Status StartProducing() =