ClickHouse/dbms/src/Functions/IFunction.h

228 lines
9.8 KiB
C++

#pragma once
#include <memory>
#include "config_core.h"
#include <Core/Names.h>
#include <Core/Block.h>
#include <Core/ColumnNumbers.h>
#include <DataTypes/IDataType.h>
/// This file contains user interface for functions.
/// For developer interface (in case you need to implement a new function) see IFunctionImpl.h
namespace llvm
{
class LLVMContext;
class Value;
class IRBuilderBase;
}
namespace DB
{
namespace ErrorCodes
{
extern const int ILLEGAL_TYPE_OF_ARGUMENT;
extern const int NOT_IMPLEMENTED;
extern const int LOGICAL_ERROR;
}
class Field;
/// The simplest executable object.
/// Motivation:
/// * Prepare something heavy once before main execution loop instead of doing it for each block.
/// * Provide const interface for IFunctionBase (later).
/// * Create one executable function per thread to use caches without synchronization (later).
class IExecutableFunction
{
public:
virtual ~IExecutableFunction() = default;
/// Get the main function name.
virtual String getName() const = 0;
virtual void execute(Block & block, const ColumnNumbers & arguments, size_t result, size_t input_rows_count, bool dry_run) = 0;
virtual void createLowCardinalityResultCache(size_t cache_size) = 0;
};
using ExecutableFunctionPtr = std::shared_ptr<IExecutableFunction>;
using ValuePlaceholders = std::vector<std::function<llvm::Value * ()>>;
/// Function with known arguments and return type (when the specific overload was chosen).
/// It is also the point where all function-specific properties are known.
class IFunctionBase
{
public:
virtual ~IFunctionBase() = default;
/// Get the main function name.
virtual String getName() const = 0;
virtual const DataTypes & getArgumentTypes() const = 0;
virtual const DataTypePtr & getReturnType() const = 0;
/// Do preparations and return executable.
/// sample_block should contain data types of arguments and values of constants, if relevant.
virtual ExecutableFunctionPtr prepare(const Block & sample_block, const ColumnNumbers & arguments, size_t result) const = 0;
/// TODO: make const
virtual void execute(Block & block, const ColumnNumbers & arguments, size_t result, size_t input_rows_count, bool dry_run = false)
{
return prepare(block, arguments, result)->execute(block, arguments, result, input_rows_count, dry_run);
}
#if USE_EMBEDDED_COMPILER
virtual bool isCompilable() const { return false; }
/** Produce LLVM IR code that operates on scalar values. See `toNativeType` in DataTypes/Native.h
* for supported value types and how they map to LLVM types.
*
* NOTE: the builder is actually guaranteed to be exactly `llvm::IRBuilder<>`, so you may safely
* downcast it to that type. This method is specified with `IRBuilderBase` because forward-declaring
* templates with default arguments is impossible and including LLVM in such a generic header
* as this one is a major pain.
*/
virtual llvm::Value * compile(llvm::IRBuilderBase & /*builder*/, ValuePlaceholders /*values*/) const
{
throw Exception(getName() + " is not JIT-compilable", ErrorCodes::NOT_IMPLEMENTED);
}
#endif
virtual bool isStateful() const { return false; }
/** Should we evaluate this function while constant folding, if arguments are constants?
* Usually this is true. Notable counterexample is function 'sleep'.
* If we will call it during query analysis, we will sleep extra amount of time.
*/
virtual bool isSuitableForConstantFolding() const { return true; }
/** Some functions like ignore(...) or toTypeName(...) always return constant result which doesn't depend on arguments.
* In this case we can calculate result and assume that it's constant in stream header.
* There is no need to implement function if it has zero arguments.
* Must return ColumnConst with single row or nullptr.
*/
virtual ColumnPtr getResultIfAlwaysReturnsConstantAndHasArguments(const Block & /*block*/, const ColumnNumbers & /*arguments*/) const { return nullptr; }
/** Function is called "injective" if it returns different result for different values of arguments.
* Example: hex, negate, tuple...
*
* Function could be injective with some arguments fixed to some constant values.
* Examples:
* plus(const, x);
* multiply(const, x) where x is an integer and constant is not divisible by two;
* concat(x, 'const');
* concat(x, 'const', y) where const contain at least one non-numeric character;
* concat with FixedString
* dictGet... functions takes name of dictionary as its argument,
* and some dictionaries could be explicitly defined as injective.
*
* It could be used, for example, to remove useless function applications from GROUP BY.
*
* Sometimes, function is not really injective, but considered as injective, for purpose of query optimization.
* For example, toString function is not injective for Float64 data type,
* as it returns 'nan' for many different representation of NaNs.
* But we assume, that it is injective. This could be documented as implementation-specific behaviour.
*
* sample_block should contain data types of arguments and values of constants, if relevant.
*/
virtual bool isInjective(const Block & /*sample_block*/) { return false; }
/** Function is called "deterministic", if it returns same result for same values of arguments.
* Most of functions are deterministic. Notable counterexample is rand().
* Sometimes, functions are "deterministic" in scope of single query
* (even for distributed query), but not deterministic it general.
* Example: now(). Another example: functions that work with periodically updated dictionaries.
*/
virtual bool isDeterministic() const = 0;
virtual bool isDeterministicInScopeOfQuery() const = 0;
/** Lets you know if the function is monotonic in a range of values.
* This is used to work with the index in a sorted chunk of data.
* And allows to use the index not only when it is written, for example `date >= const`, but also, for example, `toMonth(date) >= 11`.
* All this is considered only for functions of one argument.
*/
virtual bool hasInformationAboutMonotonicity() const { return false; }
/// The property of monotonicity for a certain range.
struct Monotonicity
{
bool is_monotonic = false; /// Is the function monotonous (nondecreasing or nonincreasing).
bool is_positive = true; /// true if the function is nondecreasing, false, if notincreasing. If is_monotonic = false, then it does not matter.
bool is_always_monotonic = false; /// Is true if function is monotonic on the whole input range I
Monotonicity(bool is_monotonic_ = false, bool is_positive_ = true, bool is_always_monotonic_ = false)
: is_monotonic(is_monotonic_), is_positive(is_positive_), is_always_monotonic(is_always_monotonic_) {}
};
/** Get information about monotonicity on a range of values. Call only if hasInformationAboutMonotonicity.
* NULL can be passed as one of the arguments. This means that the corresponding range is unlimited on the left or on the right.
*/
virtual Monotonicity getMonotonicityForRange(const IDataType & /*type*/, const Field & /*left*/, const Field & /*right*/) const
{
throw Exception("Function " + getName() + " has no information about its monotonicity.", ErrorCodes::NOT_IMPLEMENTED);
}
};
using FunctionBasePtr = std::shared_ptr<IFunctionBase>;
/// Creates IFunctionBase from argument types list (chooses one function overload).
class IFunctionOverloadResolver
{
public:
virtual ~IFunctionOverloadResolver() = default;
/// Get the main function name.
virtual String getName() const = 0;
/// See the comment for the same method in IFunctionBase
virtual bool isDeterministic() const = 0;
virtual bool isDeterministicInScopeOfQuery() const = 0;
/// Override and return true if function needs to depend on the state of the data.
virtual bool isStateful() const = 0;
/// Override and return true if function could take different number of arguments.
virtual bool isVariadic() const = 0;
/// For non-variadic functions, return number of arguments; otherwise return zero (that should be ignored).
virtual size_t getNumberOfArguments() const = 0;
/// Throw if number of arguments is incorrect.
virtual void checkNumberOfArguments(size_t number_of_arguments) const = 0;
/// Check if arguments are correct and returns IFunctionBase.
virtual FunctionBasePtr build(const ColumnsWithTypeAndName & arguments) const = 0;
/// For higher-order functions (functions, that have lambda expression as at least one argument).
/// You pass data types with empty DataTypeFunction for lambda arguments.
/// This function will replace it with DataTypeFunction containing actual types.
virtual void getLambdaArgumentTypes(DataTypes & arguments) const = 0;
/// Returns indexes of arguments, that must be ColumnConst
virtual ColumnNumbers getArgumentsThatAreAlwaysConstant() const = 0;
/// Returns indexes if arguments, that can be Nullable without making result of function Nullable
/// (for functions like isNull(x))
virtual ColumnNumbers getArgumentsThatDontImplyNullableReturnType(size_t number_of_arguments) const = 0;
};
using FunctionOverloadResolverPtr = std::shared_ptr<IFunctionOverloadResolver>;
/** Return ColumnNullable of src, with null map as OR-ed null maps of args columns in blocks.
* Or ColumnConst(ColumnNullable) if the result is always NULL or if the result is constant and always not NULL.
*/
ColumnPtr wrapInNullable(const ColumnPtr & src, const Block & block, const ColumnNumbers & args, size_t result, size_t input_rows_count);
}