ClickHouse/dbms/src/Functions/IFunction.h

#pragma once

#include <memory>

#include <Core/Names.h>
#include <Core/Field.h>
#include <Core/Block.h>
#include <Core/ColumnNumbers.h>
#include <DataTypes/IDataType.h>


namespace DB
{

namespace ErrorCodes
{
    extern const int ILLEGAL_TYPE_OF_ARGUMENT;
    extern const int NOT_IMPLEMENTED;
    extern const int LOGICAL_ERROR;
}

class IPreparedFunction
{
public:
    virtual ~IPreparedFunction() = default;

    /// Get the main function name.
    virtual String getName() const = 0;

    virtual void execute(Block & block, const ColumnNumbers & arguments, size_t result) = 0;
};

using PreparedFunctionPtr = std::shared_ptr<IPreparedFunction>;

class PreparedFunctionImpl : public IPreparedFunction
{
public:
    void execute(Block & block, const ColumnNumbers & arguments, size_t result) final;

protected:
    virtual void executeImpl(Block & block, const ColumnNumbers & arguments, size_t result) = 0;

    /** Default implementation in presence of Nullable arguments or NULL constants as arguments is the following:
      *  if some of arguments are NULL constants then return NULL constant,
      *  if some of arguments are Nullable, then execute function as usual for block,
      *   where Nullable columns are substituted with nested columns (they have arbitrary values in rows corresponding to NULL value)
      *   and wrap result in Nullable column where NULLs are in all rows where any of arguments are NULL.
      */
    virtual bool useDefaultImplementationForNulls() const { return true; }

    /** If the function have non-zero number of arguments,
      *  and if all arguments are constant, that we could automatically provide default implementation:
      *  arguments are converted to ordinary columns with single value, then function is executed as usual,
      *  and then the result is converted to constant column.
      */
    virtual bool useDefaultImplementationForConstants() const { return false; }

    /** Some arguments could remain constant during this implementation.
      */
    virtual ColumnNumbers getArgumentsThatAreAlwaysConstant() const { return {}; }

private:
    bool defaultImplementationForNulls(Block & block, const ColumnNumbers & args, size_t result);
    bool defaultImplementationForConstantArguments(Block & block, const ColumnNumbers & args, size_t result);
};


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 PreparedFunctionPtr prepare(const Block & sample_block) const = 0;

    /// TODO: make const
    virtual void execute(Block & block, const ColumnNumbers & arguments, size_t result)
    {
        return prepare(block)->execute(block, arguments, result);
    }

    /** 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; }

    /** 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 divisable 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 isDeterministicInScopeOfQuery() { return true; }

    /** 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

        explicit 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>;

class IFunctionBuilder
{
public:
    virtual ~IFunctionBuilder() = default;

    /// Get the main function name.
    virtual String getName() const = 0;

    /// Override and return true if function could take different number of arguments.
    virtual bool isVariadic() const { return false; }

    /// 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. Default implementation will check only in non-variadic case.
    virtual void checkNumberOfArguments(size_t number_of_arguments) const = 0;

    /// Check arguments and return IFunction.
    virtual FunctionBasePtr build(const ColumnsWithTypeAndName & arguments) const = 0;
};

using FunctionBuilderPtr = std::shared_ptr<IFunctionBuilder>;

class FunctionBuilderImpl : public IFunctionBuilder
{
public:
    FunctionBasePtr build(const ColumnsWithTypeAndName & arguments) const final
    {
        return buildImpl(arguments, getReturnType(arguments));
    }

    /// Default implementation. Will check only in non-variadic case.
    void checkNumberOfArguments(size_t number_of_arguments) const override;

    DataTypePtr getReturnType(const ColumnsWithTypeAndName & arguments) const;

protected:
    /// Get the result type by argument type. If the function does not apply to these arguments, throw an exception.
    virtual DataTypePtr getReturnTypeImpl(const ColumnsWithTypeAndName & arguments) const
    {
        DataTypes data_types(arguments.size());
        for (size_t i = 0; i < arguments.size(); ++i)
            data_types[i] = arguments[i].type;

        return getReturnTypeImpl(data_types);
    }

    virtual DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const
    {
        throw Exception("getReturnType is not implemented for " + getName(), ErrorCodes::NOT_IMPLEMENTED);
    }

    /** If useDefaultImplementationForNulls() is true, than change arguments for getReturnType() and buildImpl():
      *  if some of arguments are Nullable(Nothing) then don't call getReturnType(), call buildImpl() with return_type = Nullable(Nothing),
      *  if some of arguments are Nullable, then:
      *   - Nullable types are substituted with nested types for getReturnType() function
      *   - wrap getReturnType() result in Nullable type and pass to buildImpl
      *
      * Otherwise build returns buildImpl(arguments, getReturnType(arguments));
      */
    virtual bool useDefaultImplementationForNulls() const { return true; }

    virtual FunctionBasePtr buildImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & return_type) const = 0;
};


class IFunction : public std::enable_shared_from_this<IFunction>,
                  public FunctionBuilderImpl, public IFunctionBase, public PreparedFunctionImpl
{
public:
    String getName() const override = 0;
    /// TODO: make const
    void executeImpl(Block & block, const ColumnNumbers & arguments, size_t result) override = 0;

    /// Override this functions to change default implementation behavior. See details in IMyFunction.
    bool useDefaultImplementationForNulls() const override { return true; }
    bool useDefaultImplementationForConstants() const override { return false; }
    ColumnNumbers getArgumentsThatAreAlwaysConstant() const override { return {}; }

    void execute(Block & block, const ColumnNumbers & arguments, size_t result) final
    {
        return PreparedFunctionImpl::execute(block, arguments, result);
    }

    PreparedFunctionPtr prepare(const Block & sample_block) const final
    {
        throw Exception("prepare is not implemented for IFunction", ErrorCodes::NOT_IMPLEMENTED);
    }

    const DataTypes & getArgumentTypes() const final
    {
        throw Exception("getArgumentTypes is not implemented for IFunction", ErrorCodes::NOT_IMPLEMENTED);
    }

protected:
    FunctionBasePtr buildImpl(const ColumnsWithTypeAndName & arguments_, const DataTypePtr & return_type_) const final
    {
        throw Exception("buildImpl is not implemented for IFunction", ErrorCodes::NOT_IMPLEMENTED);
    }
};

class DefaultExecutable final : public PreparedFunctionImpl
{
public:
    explicit DefaultExecutable(std::shared_ptr<IFunction> function) : function(std::move(function)) {}

protected:
    void executeImpl(Block & block, const ColumnNumbers & arguments, size_t result) final
    {
        return function->executeImpl(block, arguments, result);
    }
    bool useDefaultImplementationForNulls() const final { return function->useDefaultImplementationForNulls(); }
    bool useDefaultImplementationForConstants() const final { return function->useDefaultImplementationForConstants(); }
    ColumnNumbers getArgumentsThatAreAlwaysConstant() const final { return function->getArgumentsThatAreAlwaysConstant(); }

private:
    std::shared_ptr<IFunction> function;
};

class DefaultFunction final : public IFunctionBase
{
public:
    DefaultFunction(std::shared_ptr<IFunction> function, DataTypes && arguments, DataTypePtr && return_type)
            : function(std::move(function)), arguments(std::move(arguments)), return_type(std::move(return_type)) {}

    String getName() const override { return function->getName(); }

    const DataTypes & getArgumentTypes() const override { return arguments; }
    const DataTypePtr & getReturnType() const override { return return_type; }

    PreparedFunctionPtr prepare(const Block & sample_block) const override { return std::make_shared<DefaultExecutable>(function); }

    bool isSuitableForConstantFolding() const override { return function->isSuitableForConstantFolding(); }

    bool isInjective(const Block & sample_block) override { return function->isInjective(sample_block); }

    bool isDeterministicInScopeOfQuery() override { return function->isDeterministicInScopeOfQuery(); }

    bool hasInformationAboutMonotonicity() const override { return function->hasInformationAboutMonotonicity(); }

    IFunctionBase::Monotonicity getMonotonicityForRange(const IDataType & type, const Field & left, const Field & right) const override
    {
        return function->getMonotonicityForRange(type, left, right);
    }
private:
    std::shared_ptr<IFunction> function;
    DataTypes arguments;
    DataTypePtr return_type;
};

class DefaultFunctionBuilder : public FunctionBuilderImpl
{
public:
    explicit DefaultFunctionBuilder(std::shared_ptr<IFunction> function) : function(std::move(function)) {}

    void checkNumberOfArguments(size_t number_of_arguments) const override
    {
        return function->checkNumberOfArguments(number_of_arguments);
    }

    String getName() const override { return function->getName(); };
    bool isVariadic() const override { return function->isVariadic(); }
    size_t getNumberOfArguments() const override { return function->getNumberOfArguments(); }

protected:
    /// Get the result type by argument type. If the function does not apply to these arguments, throw an exception.
    DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override { return function->getReturnTypeImpl(arguments); }
    DataTypePtr getReturnTypeImpl(const ColumnsWithTypeAndName & arguments) const override { return function->getReturnTypeImpl(arguments); }

    bool useDefaultImplementationForNulls() const override { return function->useDefaultImplementationForNulls(); }

    FunctionBasePtr buildImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & return_type) const override
    {
        DataTypes data_types(arguments.size());
        for (size_t i = 0; i < arguments.size(); ++i)
            data_types[i] = arguments[i].type;
        return std::make_shared<DefaultFunction>(function, data_types, return_type);
    }

private:
    std::shared_ptr<IFunction> function;
};

using FunctionPtr = std::shared_ptr<IFunction>;

//
///** Interface for normal functions.
//  * Normal functions are functions that do not change the number of rows in the table,
//  *  and the result of which for each row does not depend on other rows.
//  *
//  * A function can take an arbitrary number of arguments; returns exactly one value.
//  * The type of the result depends on the type and number of arguments.
//  *
//  * The function is dispatched for the whole block. This allows you to perform all kinds of checks rarely,
//  *  and do the main job as an efficient loop.
//  *
//  * The function is applied to one or more columns of the block, and writes its result,
//  *  adding a new column to the block. The function does not modify its arguments.
//  */
//class IFunction
//{
//public:
//    /** The successor of IFunction must implement:
//      * - getName
//      * - either getReturnType, or getReturnTypeAndPrerequisites
//      * - one of the overloads of `execute`.
//      */
//
//    /// Get the main function name.
//    virtual String getName() const = 0;
//
//    /// Override and return true if function could take different number of arguments.
//    virtual bool isVariadic() const { return false; }
//
//    /// 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. Default implementation will check only in non-variadic case.
//    /// It is called inside getReturnType.
//    virtual void checkNumberOfArguments(size_t number_of_arguments) const;
//
//    /** 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; }
//
//    /** 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 divisable 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 isDeterministicInScopeOfQuery() { return true; }
//
//    /// Get the result type by argument type. If the function does not apply to these arguments, throw an exception.
//    /// Overloading for those who do not need prerequisites and values of constant arguments. Not called from outside.
//    DataTypePtr getReturnType(const DataTypes & arguments) const;
//
//    virtual DataTypePtr getReturnTypeImpl(const DataTypes & /*arguments*/) const
//    {
//        throw Exception("getReturnType is not implemented for " + getName(), ErrorCodes::NOT_IMPLEMENTED);
//    }
//
//    /** Get the result type by argument types and constant argument values.
//      * If the function does not apply to these arguments, throw an exception.
//      * You can also return a description of the additional columns that are required to perform the function.
//      * For non-constant columns `arguments[i].column = nullptr`.
//      * Meaningful element types in out_prerequisites: APPLY_FUNCTION, ADD_COLUMN.
//      */
//    void getReturnTypeAndPrerequisites(
//        const ColumnsWithTypeAndName & arguments,
//        DataTypePtr & out_return_type,
//        std::vector<ExpressionAction> & out_prerequisites);
//
//    virtual void getReturnTypeAndPrerequisitesImpl(
//        const ColumnsWithTypeAndName & arguments,
//        DataTypePtr & out_return_type,
//        std::vector<ExpressionAction> & /*out_prerequisites*/)
//    {
//        DataTypes types(arguments.size());
//        for (size_t i = 0; i < arguments.size(); ++i)
//            types[i] = arguments[i].type;
//        out_return_type = getReturnTypeImpl(types);
//    }
//
//    /// For higher-order functions (functions, that have lambda expression as at least one argument).
//    /// You pass data types with empty DataTypeExpression for lambda arguments.
//    /// This function will replace it with DataTypeExpression containing actual types.
//    void getLambdaArgumentTypes(DataTypes & arguments) const;
//
//    virtual void getLambdaArgumentTypesImpl(DataTypes & /*arguments*/) const
//    {
//        throw Exception("Function " + getName() + " can't have lambda-expressions as arguments", ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
//    }
//
//    /// Execute the function on the block. Note: can be called simultaneously from several threads, for one object.
//    /// Overloading for those who do not need `prerequisites`. Not called from outside.
//    void execute(Block & block, const ColumnNumbers & arguments, size_t result);
//
//    /// Execute the function above the block. Note: can be called simultaneously from several threads, for one object.
//    /// `prerequisites` go in the same order as `out_prerequisites` obtained from getReturnTypeAndPrerequisites.
//    void execute(Block & block, const ColumnNumbers & arguments, const ColumnNumbers & prerequisites, size_t result);
//
//    virtual void executeImpl(Block & /*block*/, const ColumnNumbers & /*arguments*/, size_t /*result*/)
//    {
//        throw Exception("executeImpl is not implemented for " + getName(), ErrorCodes::NOT_IMPLEMENTED);
//    }
//
//    virtual void executeImpl(Block & block, const ColumnNumbers & arguments, const ColumnNumbers & /*prerequisites*/, size_t result)
//    {
//        executeImpl(block, arguments, result);
//    }
//
//    /** Default implementation in presense of Nullable arguments or NULL constants as arguments is the following:
//      *  if some of arguments are NULL constants then return NULL constant,
//      *  if some of arguments are Nullable, then execute function as usual for block,
//      *   where Nullable columns are substituted with nested columns (they have arbitary values in rows corresponding to NULL value)
//      *   and wrap result in Nullable column where NULLs are in all rows where any of arguments are NULL.
//      */
//    virtual bool useDefaultImplementationForNulls() const { return true; }
//
//    /** If the function have non-zero number of arguments,
//      *  and if all arguments are constant, that we could automatically provide default implementation:
//      *  arguments are converted to ordinary columns with single value, then function is executed as usual,
//      *  and then the result is converted to constant column.
//      */
//    virtual bool useDefaultImplementationForConstants() const { return false; }
//
//    /** Some arguments could remain constant during this implementation.
//      */
//    virtual ColumnNumbers getArgumentsThatAreAlwaysConstant() const { return {}; }
//
//
//    /** 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);
//    }
//
//    virtual ~IFunction() {}
//};

}