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292 lines
11 KiB
C++
292 lines
11 KiB
C++
#include <Columns/ColumnConst.h>
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#include <Columns/ColumnVector.h>
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#include <Core/ColumnWithTypeAndName.h>
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#include <Core/ColumnsWithTypeAndName.h>
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#include <Core/Types.h>
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#include <DataTypes/DataTypesNumber.h>
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#include <DataTypes/IDataType.h>
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#include <DataTypes/NumberTraits.h>
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#include <Functions/FunctionFactory.h>
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#include <Functions/FunctionHelpers.h>
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#include <Functions/IFunction.h>
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#include <Interpreters/Context.h>
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#include <Interpreters/castColumn.h>
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#include <Common/Concepts.h>
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#include <Common/Exception.h>
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#include <Common/NaNUtils.h>
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#include <Common/register_objects.h>
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#include <algorithm>
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#include <iterator>
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#include <memory>
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#include <optional>
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#include <string>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int ILLEGAL_TYPE_OF_ARGUMENT;
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extern const int BAD_ARGUMENTS;
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extern const int LOGICAL_ERROR;
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}
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class FunctionWidthBucket : public IFunction
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{
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template <typename TDataType>
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void throwIfInvalid(
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const size_t argument_index,
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const ColumnConst * col_const,
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const typename ColumnVector<TDataType>::Container * col_vec,
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const size_t expected_size) const
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{
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if ((nullptr == col_const) ^ (nullptr != col_vec && col_vec->size() == expected_size))
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{
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throw Exception(
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ErrorCodes::LOGICAL_ERROR,
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"Logical error in function {}: argument {} has unexpected type or size!",
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getName(),
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argument_index);
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}
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}
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template <typename TDataType>
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const typename ColumnVector<TDataType>::Container * getDataIfNotNull(const ColumnVector<TDataType> * col_vec) const
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{
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if (nullptr == col_vec)
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{
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return nullptr;
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}
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return &col_vec->getData();
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}
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template <typename TDataType>
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static TDataType
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getValue(const ColumnConst * col_const, const typename ColumnVector<TDataType>::Container * col_vec, const size_t index)
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{
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if (nullptr != col_const)
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{
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return col_const->getValue<TDataType>();
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}
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return col_vec->data()[index];
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}
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static Float64 calculateRelativeBucket(const Float64 operand, const Float64 low, const Float64 high)
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{
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return (operand - low) / (high - low);
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}
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template <typename TResultType, typename TCountType>
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std::optional<TResultType> checkArguments(const Float64 operand, const Float64 low, const Float64 high, const TCountType count) const
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{
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if (count == 0)
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{
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "Last argument (count) for function {} cannot be 0.", getName());
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}
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if (isNaN(operand) || isNaN(low) || isNaN(high))
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{
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throw Exception(
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ErrorCodes::BAD_ARGUMENTS, "The first three arguments (operand, low, high) cannot be NaN in function {}", getName());
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}
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// operand can be infinity, the following conditions will take care of it
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if (!isFinite(low) || !isFinite(high))
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{
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throw Exception(ErrorCodes::BAD_ARGUMENTS, "The second and third arguments (low, high) cannot be Inf function {}", getName());
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}
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if (operand < low || low >= high)
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{
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return 0;
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}
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else if (operand >= high)
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{
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return count + 1;
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}
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return std::nullopt;
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}
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template <typename TResultType, typename TCountType>
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TResultType NO_SANITIZE_UNDEFINED calculate(const Float64 operand, const Float64 low, const Float64 high, const TCountType count) const
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{
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if (const auto maybe_early_return = checkArguments<TResultType>(operand, low, high, count); maybe_early_return.has_value())
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{
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return *maybe_early_return;
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}
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const auto relative_bucket = calculateRelativeBucket(operand, low, high);
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if (isNaN(relative_bucket) || !isFinite(relative_bucket))
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{
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throw Exception(
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ErrorCodes::LOGICAL_ERROR, "The calculation resulted in NaN or Inf which is unexpected in function {}.", getName());
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}
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return static_cast<TResultType>(count * relative_bucket + 1);
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}
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template <is_any_of<UInt8, UInt16, UInt32, UInt64> TCountType>
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ColumnPtr executeForResultType(const ColumnsWithTypeAndName & arguments, size_t input_rows_count) const
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{
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using ResultType = typename NumberTraits::Construct<false, false, NumberTraits::nextSize(sizeof(TCountType))>::Type;
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auto common_type = std::make_shared<DataTypeNumber<Float64>>();
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std::vector<ColumnPtr> casted_columns;
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casted_columns.reserve(3);
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for (const auto argument_index : collections::range(0, 3))
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{
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casted_columns.push_back(castColumn(arguments[argument_index], common_type));
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}
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const auto * operands_vec = getDataIfNotNull(checkAndGetColumn<ColumnVector<Float64>>(casted_columns[0].get()));
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const auto * lows_vec = getDataIfNotNull(checkAndGetColumn<ColumnVector<Float64>>(casted_columns[1].get()));
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const auto * highs_vec = getDataIfNotNull(checkAndGetColumn<ColumnVector<Float64>>(casted_columns[2].get()));
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const auto * counts_vec = getDataIfNotNull(checkAndGetColumn<ColumnVector<TCountType>>(arguments[3].column.get()));
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const auto * operands_col_const = checkAndGetColumnConst<ColumnVector<Float64>>(casted_columns[0].get());
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const auto * lows_col_const = checkAndGetColumnConst<ColumnVector<Float64>>(casted_columns[1].get());
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const auto * highs_col_const = checkAndGetColumnConst<ColumnVector<Float64>>(casted_columns[2].get());
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const auto * counts_col_const = checkAndGetColumnConst<ColumnVector<TCountType>>(arguments[3].column.get());
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throwIfInvalid<Float64>(0, operands_col_const, operands_vec, input_rows_count);
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throwIfInvalid<Float64>(1, lows_col_const, lows_vec, input_rows_count);
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throwIfInvalid<Float64>(2, highs_col_const, highs_vec, input_rows_count);
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throwIfInvalid<TCountType>(4, counts_col_const, counts_vec, input_rows_count);
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const auto are_all_const_cols
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= nullptr != operands_col_const && nullptr != lows_col_const && nullptr != highs_col_const && nullptr != counts_col_const;
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if (are_all_const_cols)
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{
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throw Exception(
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ErrorCodes::LOGICAL_ERROR, "Logical error in function {}: unexpected combination of argument types!", getName());
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}
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auto result_column = ColumnVector<ResultType>::create();
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result_column->reserve(1);
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auto & result_data = result_column->getData();
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for (const auto row_index : collections::range(0, input_rows_count))
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{
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const auto operand = getValue<Float64>(operands_col_const, operands_vec, row_index);
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const auto low = getValue<Float64>(lows_col_const, lows_vec, row_index);
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const auto high = getValue<Float64>(highs_col_const, highs_vec, row_index);
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const auto count = getValue<TCountType>(counts_col_const, counts_vec, row_index);
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result_data.push_back(calculate<ResultType>(operand, low, high, count));
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}
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return result_column;
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}
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public:
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static inline const char * name = "widthBucket";
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explicit FunctionWidthBucket() = default;
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static FunctionPtr create(ContextPtr) { return std::make_shared<FunctionWidthBucket>(); }
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String getName() const override { return name; }
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size_t getNumberOfArguments() const override { return 4; }
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DataTypePtr getReturnTypeImpl(const DataTypes & arguments) const override
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{
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for (const auto argument_index : collections::range(0, 3))
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{
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if (!isNativeNumber(arguments[argument_index]))
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{
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throw Exception(
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ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT,
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"The first three arguments of function {} must be a Int8, Int16, Int32, Int64, UInt8, UInt16, UInt32, UInt64, Float32 "
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"or Float64.",
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getName());
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}
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}
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if (!WhichDataType(arguments[3]).isNativeUInt())
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{
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throw Exception(
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ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT,
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"The last argument of function {} must be UInt8, UInt16, UInt32 or UInt64, found {}.",
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getName(),
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arguments[3]->getName());
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}
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switch (arguments[3]->getTypeId())
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{
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case TypeIndex::UInt8:
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return std::make_shared<DataTypeUInt16>();
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case TypeIndex::UInt16:
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return std::make_shared<DataTypeUInt32>();
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case TypeIndex::UInt32:
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[[fallthrough]];
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case TypeIndex::UInt64:
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return std::make_shared<DataTypeUInt64>();
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default:
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break;
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}
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UNREACHABLE();
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}
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bool isSuitableForShortCircuitArgumentsExecution(const DataTypesWithConstInfo & /*arguments*/) const override { return true; }
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ColumnPtr
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executeImpl(const ColumnsWithTypeAndName & arguments, const DataTypePtr & /*result_type*/, size_t input_rows_count) const override
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{
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switch (arguments[3].type->getTypeId())
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{
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case TypeIndex::UInt8:
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return executeForResultType<UInt8>(arguments, input_rows_count);
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case TypeIndex::UInt16:
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return executeForResultType<UInt16>(arguments, input_rows_count);
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case TypeIndex::UInt32:
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return executeForResultType<UInt32>(arguments, input_rows_count);
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case TypeIndex::UInt64:
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return executeForResultType<UInt64>(arguments, input_rows_count);
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default:
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break;
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}
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UNREACHABLE();
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}
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bool useDefaultImplementationForConstants() const override { return true; }
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};
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REGISTER_FUNCTION(WidthBucket)
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{
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factory.registerFunction<FunctionWidthBucket>({
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R"(
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Returns the number of the bucket in which `operand` falls in a histogram having `count` equal-width buckets spanning the range `low` to `high`. Returns `0` if `operand < low`, and returns `count+1` if `operand >= high`.
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`operand`, `low`, `high` can be any native number type. `count` can only be unsigned native integer and its value cannot be zero.
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**Syntax**
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```sql
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widthBucket(operand, low, high, count)
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```
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There is also a case insensitive alias called `WIDTH_BUCKET` to provide compatibility with other databases.
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**Example**
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Query:
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[example:simple]
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Result:
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``` text
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┌─widthBucket(10.15, -8.6, 23, 18)─┐
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│ 11 │
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└──────────────────────────────────┘
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```
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)",
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Documentation::Examples{
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{"simple", "SELECT widthBucket(10.15, -8.6, 23, 18)"},
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},
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Documentation::Categories{"Mathematical"},
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});
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factory.registerAlias("width_bucket", "widthBucket", FunctionFactory::CaseInsensitive);
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}
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}
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