#pragma once #include #include "config_core.h" #include #include #include #include /// 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; using ValuePlaceholders = std::vector>; /// 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; /// 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; /** 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); }