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doris/be/src/vec/functions/function_cast.h

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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
// This file is copied from
// https://github.com/ClickHouse/ClickHouse/blob/master/src/Functions/FunctionsConversion.h
// and modified by Doris
#pragma once
#include <fmt/format.h>
#include "udf/udf_internal.h"
#include "vec/columns/column_array.h"
#include "vec/columns/column_const.h"
#include "vec/columns/column_nullable.h"
#include "vec/columns/column_string.h"
#include "vec/columns/columns_common.h"
#include "vec/common/assert_cast.h"
#include "vec/common/field_visitors.h"
#include "vec/common/string_buffer.hpp"
#include "vec/data_types/data_type_decimal.h"
#include "vec/data_types/data_type_factory.hpp"
#include "vec/data_types/data_type_jsonb.h"
#include "vec/data_types/data_type_nullable.h"
#include "vec/data_types/data_type_number.h"
#include "vec/data_types/data_type_string.h"
#include "vec/functions/function.h"
#include "vec/functions/function_helpers.h"
#include "vec/io/io_helper.h"
#include "vec/io/reader_buffer.h"
#include "vec/runtime/vdatetime_value.h"
namespace doris::vectorized {
/** Type conversion functions.
* toType - conversion in "natural way";
*/
inline UInt32 extract_to_decimal_scale(const ColumnWithTypeAndName& named_column) {
const auto* arg_type = named_column.type.get();
bool ok = check_and_get_data_type<DataTypeUInt64>(arg_type) ||
check_and_get_data_type<DataTypeUInt32>(arg_type) ||
check_and_get_data_type<DataTypeUInt16>(arg_type) ||
check_and_get_data_type<DataTypeUInt8>(arg_type);
if (!ok) {
LOG(FATAL) << fmt::format("Illegal type of toDecimal() scale {}",
named_column.type->get_name());
}
Field field;
named_column.column->get(0, field);
return field.get<UInt32>();
}
/** Conversion of number types to each other, enums to numbers, dates and datetimes to numbers and back: done by straight assignment.
* (Date is represented internally as number of days from some day; DateTime - as unix timestamp)
*/
template <typename FromDataType, typename ToDataType, typename Name>
struct ConvertImpl {
using FromFieldType = typename FromDataType::FieldType;
using ToFieldType = typename ToDataType::FieldType;
template <typename Additions = void*>
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result,
size_t /*input_rows_count*/, bool check_overflow [[maybe_unused]] = false,
Additions additions [[maybe_unused]] = Additions()) {
const ColumnWithTypeAndName& named_from = block.get_by_position(arguments[0]);
using ColVecFrom =
std::conditional_t<IsDecimalNumber<FromFieldType>, ColumnDecimal<FromFieldType>,
ColumnVector<FromFieldType>>;
using ColVecTo = std::conditional_t<IsDecimalNumber<ToFieldType>,
ColumnDecimal<ToFieldType>, ColumnVector<ToFieldType>>;
if constexpr (IsDataTypeDecimal<FromDataType> || IsDataTypeDecimal<ToDataType>) {
if constexpr (!(IsDataTypeDecimalOrNumber<FromDataType> || IsTimeType<FromDataType> ||
IsTimeV2Type<FromDataType>) ||
!IsDataTypeDecimalOrNumber<ToDataType>)
return Status::RuntimeError("Illegal column {} of first argument of function {}",
named_from.column->get_name(), Name::name);
}
if (const ColVecFrom* col_from =
check_and_get_column<ColVecFrom>(named_from.column.get())) {
typename ColVecTo::MutablePtr col_to = nullptr;
if constexpr (IsDataTypeDecimal<ToDataType>) {
UInt32 scale = additions;
col_to = ColVecTo::create(0, scale);
} else {
col_to = ColVecTo::create();
}
const auto& vec_from = col_from->get_data();
auto& vec_to = col_to->get_data();
size_t size = vec_from.size();
vec_to.resize(size);
if constexpr (IsDataTypeDecimal<FromDataType> || IsDataTypeDecimal<ToDataType>) {
ColumnUInt8::MutablePtr col_null_map_to = nullptr;
UInt8* vec_null_map_to = nullptr;
if (check_overflow) {
col_null_map_to = ColumnUInt8::create(size, 0);
vec_null_map_to = col_null_map_to->get_data().data();
}
for (size_t i = 0; i < size; ++i) {
if constexpr (IsDataTypeDecimal<FromDataType> &&
IsDataTypeDecimal<ToDataType>) {
vec_to[i] = convert_decimals<FromDataType, ToDataType>(
vec_from[i], vec_from.get_scale(), vec_to.get_scale(),
vec_null_map_to ? &vec_null_map_to[i] : vec_null_map_to);
} else if constexpr (IsDataTypeDecimal<FromDataType> &&
IsDataTypeNumber<ToDataType>) {
vec_to[i] = convert_from_decimal<FromDataType, ToDataType>(
vec_from[i], vec_from.get_scale());
} else if constexpr (IsDataTypeNumber<FromDataType> &&
IsDataTypeDecimal<ToDataType>) {
vec_to[i] = convert_to_decimal<FromDataType, ToDataType>(
vec_from[i], vec_to.get_scale(),
vec_null_map_to ? &vec_null_map_to[i] : vec_null_map_to);
} else if constexpr (IsTimeType<FromDataType> &&
IsDataTypeDecimal<ToDataType>) {
vec_to[i] = convert_to_decimal<DataTypeInt64, ToDataType>(
reinterpret_cast<const VecDateTimeValue&>(vec_from[i]).to_int64(),
vec_to.get_scale(),
vec_null_map_to ? &vec_null_map_to[i] : vec_null_map_to);
} else if constexpr (IsDateV2Type<FromDataType> &&
IsDataTypeDecimal<ToDataType>) {
vec_to[i] = convert_to_decimal<DataTypeUInt32, ToDataType>(
reinterpret_cast<const DateV2Value<DateV2ValueType>&>(vec_from[i])
.to_date_int_val(),
vec_to.get_scale(),
vec_null_map_to ? &vec_null_map_to[i] : vec_null_map_to);
} else if constexpr (IsDateTimeV2Type<FromDataType> &&
IsDataTypeDecimal<ToDataType>) {
// TODO: should we consider the scale of datetimev2?
vec_to[i] = convert_to_decimal<DataTypeUInt64, ToDataType>(
reinterpret_cast<const DateV2Value<DateTimeV2ValueType>&>(
vec_from[i])
.to_date_int_val(),
vec_to.get_scale(),
vec_null_map_to ? &vec_null_map_to[i] : vec_null_map_to);
}
}
if (check_overflow) {
block.replace_by_position(
result,
ColumnNullable::create(std::move(col_to), std::move(col_null_map_to)));
} else {
block.replace_by_position(result, std::move(col_to));
}
return Status::OK();
} else if constexpr (IsTimeType<FromDataType>) {
for (size_t i = 0; i < size; ++i) {
if constexpr (IsTimeType<ToDataType>) {
vec_to[i] = static_cast<ToFieldType>(vec_from[i]);
if constexpr (IsDateTimeType<ToDataType>) {
DataTypeDateTime::cast_to_date_time(vec_to[i]);
} else {
DataTypeDate::cast_to_date(vec_to[i]);
}
} else if constexpr (IsDateV2Type<ToDataType>) {
DataTypeDateV2::cast_from_date(vec_from[i], vec_to[i]);
} else if constexpr (IsDateTimeV2Type<ToDataType>) {
DataTypeDateTimeV2::cast_from_date(vec_from[i], vec_to[i]);
} else {
vec_to[i] =
reinterpret_cast<const VecDateTimeValue&>(vec_from[i]).to_int64();
}
}
} else if constexpr (IsTimeV2Type<FromDataType>) {
for (size_t i = 0; i < size; ++i) {
if constexpr (IsTimeV2Type<ToDataType>) {
if constexpr (IsDateTimeV2Type<ToDataType> && IsDateV2Type<FromDataType>) {
DataTypeDateV2::cast_to_date_time_v2(vec_from[i], vec_to[i]);
} else if constexpr (IsDateTimeV2Type<FromDataType> &&
IsDateV2Type<ToDataType>) {
DataTypeDateTimeV2::cast_to_date_v2(vec_from[i], vec_to[i]);
} else {
UInt32 scale = additions;
vec_to[i] = vec_from[i] / std::pow(10, 6 - scale);
}
} else if constexpr (IsTimeType<ToDataType>) {
if constexpr (IsDateTimeType<ToDataType> && IsDateV2Type<FromDataType>) {
DataTypeDateV2::cast_to_date_time(vec_from[i], vec_to[i]);
} else if constexpr (IsDateTimeV2Type<ToDataType> &&
IsDateV2Type<FromDataType>) {
DataTypeDateV2::cast_to_date(vec_from[i], vec_to[i]);
} else if constexpr (IsDateTimeType<ToDataType> &&
IsDateTimeV2Type<FromDataType>) {
DataTypeDateTimeV2::cast_to_date_time(vec_from[i], vec_to[i]);
} else if constexpr (IsDateTimeV2Type<ToDataType> &&
IsDateTimeV2Type<FromDataType>) {
DataTypeDateTimeV2::cast_to_date(vec_from[i], vec_to[i]);
} else if constexpr (IsDateType<ToDataType> && IsDateV2Type<FromDataType>) {
DataTypeDateV2::cast_to_date(vec_from[i], vec_to[i]);
}
} else {
if constexpr (IsDateTimeV2Type<FromDataType>) {
vec_to[i] = reinterpret_cast<const DateV2Value<DateTimeV2ValueType>&>(
vec_from[i])
.to_int64();
} else {
vec_to[i] = reinterpret_cast<const DateV2Value<DateV2ValueType>&>(
vec_from[i])
.to_int64();
}
}
}
} else {
for (size_t i = 0; i < size; ++i) {
vec_to[i] = static_cast<ToFieldType>(vec_from[i]);
}
}
// TODO: support boolean cast more reasonable
if constexpr (std::is_same_v<uint8_t, ToFieldType>) {
for (int i = 0; i < size; ++i) {
vec_to[i] = static_cast<bool>(vec_to[i]);
}
}
block.replace_by_position(result, std::move(col_to));
} else {
return Status::RuntimeError("Illegal column {} of first argument of function {}",
named_from.column->get_name(), Name::name);
}
return Status::OK();
}
};
/** If types are identical, just take reference to column.
*/
template <typename T, typename Name>
struct ConvertImpl<std::enable_if_t<!T::is_parametric, T>, T, Name> {
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result,
size_t /*input_rows_count*/) {
block.get_by_position(result).column = block.get_by_position(arguments[0]).column;
return Status::OK();
}
};
// using other type cast to Date/DateTime, unless String
// Date/DateTime
template <typename FromDataType, typename ToDataType, typename Name>
struct ConvertImplToTimeType {
using FromFieldType = typename FromDataType::FieldType;
using ToFieldType = typename ToDataType::FieldType;
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result,
size_t /*input_rows_count*/) {
const ColumnWithTypeAndName& named_from = block.get_by_position(arguments[0]);
using ColVecFrom =
std::conditional_t<IsDecimalNumber<FromFieldType>, ColumnDecimal<FromFieldType>,
ColumnVector<FromFieldType>>;
using DateValueType = std::conditional_t<
IsTimeV2Type<ToDataType>,
std::conditional_t<IsDateV2Type<ToDataType>, DateV2Value<DateV2ValueType>,
DateV2Value<DateTimeV2ValueType>>,
VecDateTimeValue>;
using ColVecTo = ColumnVector<ToFieldType>;
if (const ColVecFrom* col_from =
check_and_get_column<ColVecFrom>(named_from.column.get())) {
const auto& vec_from = col_from->get_data();
size_t size = vec_from.size();
// create nested column
auto col_to = ColVecTo::create(size);
auto& vec_to = col_to->get_data();
// create null column
ColumnUInt8::MutablePtr col_null_map_to;
col_null_map_to = ColumnUInt8::create(size);
auto& vec_null_map_to = col_null_map_to->get_data();
for (size_t i = 0; i < size; ++i) {
auto& date_value = reinterpret_cast<DateValueType&>(vec_to[i]);
if constexpr (IsDecimalNumber<FromFieldType>) {
// TODO: should we consider the scale of datetimev2?
vec_null_map_to[i] = !date_value.from_date_int64(
convert_from_decimal<FromDataType, DataTypeInt64>(
vec_from[i], vec_from.get_scale()));
} else {
vec_null_map_to[i] = !date_value.from_date_int64(vec_from[i]);
}
// DateType of VecDateTimeValue should cast to date
if constexpr (IsDateType<ToDataType>) {
date_value.cast_to_date();
} else if constexpr (IsDateTimeType<ToDataType>) {
date_value.to_datetime();
}
}
block.get_by_position(result).column =
ColumnNullable::create(std::move(col_to), std::move(col_null_map_to));
} else {
return Status::RuntimeError("Illegal column {} of first argument of function {}",
named_from.column->get_name(), Name::name);
}
return Status::OK();
}
};
// Generic conversion of any type to String.
struct ConvertImplGenericToString {
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result) {
const auto& col_with_type_and_name = block.get_by_position(arguments[0]);
const IDataType& type = *col_with_type_and_name.type;
const IColumn& col_from = *col_with_type_and_name.column;
size_t size = col_from.size();
auto col_to = ColumnString::create();
VectorBufferWriter write_buffer(*col_to.get());
for (size_t i = 0; i < size; ++i) {
type.to_string(col_from, i, write_buffer);
write_buffer.commit();
}
block.replace_by_position(result, std::move(col_to));
return Status::OK();
}
static Status execute2(FunctionContext* /*ctx*/, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t /*input_rows_count*/) {
return execute(block, arguments, result);
}
};
template <typename StringColumnType>
struct ConvertImplGenericFromString {
static Status execute(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
static_assert(std::is_same_v<StringColumnType, ColumnString>,
"Can be used only to parse from ColumnString");
const auto& col_with_type_and_name = block.get_by_position(arguments[0]);
const IColumn& col_from = *col_with_type_and_name.column;
// result column must set type
DCHECK(block.get_by_position(result).type != nullptr);
auto data_type_to = block.get_by_position(result).type;
if (const StringColumnType* col_from_string =
check_and_get_column<StringColumnType>(&col_from)) {
auto col_to = data_type_to->create_column();
size_t size = col_from.size();
col_to->reserve(size);
ColumnUInt8::MutablePtr col_null_map_to = ColumnUInt8::create(size);
ColumnUInt8::Container* vec_null_map_to = &col_null_map_to->get_data();
for (size_t i = 0; i < size; ++i) {
const auto& val = col_from_string->get_data_at(i);
// Note: here we should handle the null element
if (val.size == 0) {
col_to->insert_default();
continue;
}
ReadBuffer read_buffer((char*)(val.data), val.size);
Status st = data_type_to->from_string(read_buffer, col_to);
// if parsing failed, will return null
(*vec_null_map_to)[i] = !st.ok();
if (!st.ok()) {
col_to->insert_default();
}
}
block.get_by_position(result).column =
ColumnNullable::create(std::move(col_to), std::move(col_null_map_to));
} else {
return Status::RuntimeError(
"Illegal column {} of first argument of conversion function from string",
col_from.get_name());
}
return Status::OK();
}
};
// Generic conversion of number to jsonb.
template <typename ColumnType>
struct ConvertImplNumberToJsonb {
static Status execute(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
const auto& col_with_type_and_name = block.get_by_position(arguments[0]);
auto column_string = ColumnString::create();
JsonbWriter writer;
const auto* col =
check_and_get_column<const ColumnType>(col_with_type_and_name.column.get());
const auto& data = col->get_data();
for (size_t i = 0; i < input_rows_count; i++) {
writer.reset();
if constexpr (std::is_same_v<ColumnUInt8, ColumnType>) {
writer.writeBool(data[i]);
} else if constexpr (std::is_same_v<ColumnInt8, ColumnType>) {
writer.writeInt8(data[i]);
} else if constexpr (std::is_same_v<ColumnInt16, ColumnType>) {
writer.writeInt16(data[i]);
} else if constexpr (std::is_same_v<ColumnInt32, ColumnType>) {
writer.writeInt32(data[i]);
} else if constexpr (std::is_same_v<ColumnInt64, ColumnType>) {
writer.writeInt64(data[i]);
} else if constexpr (std::is_same_v<ColumnFloat64, ColumnType>) {
writer.writeDouble(data[i]);
} else {
LOG(FATAL) << "unsupported type ";
}
column_string->insert_data(writer.getOutput()->getBuffer(),
writer.getOutput()->getSize());
}
block.replace_by_position(result, std::move(column_string));
return Status::OK();
}
};
// Generic conversion of any type to jsonb.
struct ConvertImplGenericToJsonb {
static Status execute(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
const auto& col_with_type_and_name = block.get_by_position(arguments[0]);
const IDataType& type = *col_with_type_and_name.type;
const IColumn& col_from = *col_with_type_and_name.column;
auto column_string = ColumnString::create();
JsonbWriter writer;
auto tmp_col = ColumnString::create();
for (size_t i = 0; i < input_rows_count; i++) {
// convert to string
tmp_col->clear();
VectorBufferWriter write_buffer(*tmp_col.get());
type.to_string(col_from, i, write_buffer);
write_buffer.commit();
// write string to jsonb
writer.reset();
writer.writeStartString();
auto str_ref = tmp_col->get_data_at(0);
writer.writeString(str_ref.data, str_ref.size);
writer.writeEndString();
column_string->insert_data(writer.getOutput()->getBuffer(),
writer.getOutput()->getSize());
}
block.replace_by_position(result, std::move(column_string));
return Status::OK();
}
};
template <TypeIndex type_index, typename ColumnType>
struct ConvertImplFromJsonb {
static Status execute(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
const auto& col_with_type_and_name = block.get_by_position(arguments[0]);
const IColumn& col_from = *col_with_type_and_name.column;
// result column must set type
DCHECK(block.get_by_position(result).type != nullptr);
auto data_type_to = block.get_by_position(result).type;
if (const ColumnString* column_string = check_and_get_column<ColumnString>(&col_from)) {
auto null_map_col = ColumnUInt8::create(input_rows_count, 0);
auto& null_map = null_map_col->get_data();
auto col_to = ColumnType::create();
//IColumn & col_to = *res;
// size_t size = col_from.size();
col_to->reserve(input_rows_count);
auto& res = col_to->get_data();
res.resize(input_rows_count);
for (size_t i = 0; i < input_rows_count; ++i) {
const auto& val = column_string->get_data_at(i);
// ReadBuffer read_buffer((char*)(val.data), val.size);
// RETURN_IF_ERROR(data_type_to->from_string(read_buffer, col_to));
if (val.size == 0) {
null_map[i] = 1;
res[i] = 0;
continue;
}
// doc is NOT necessary to be deleted since JsonbDocument will not allocate memory
JsonbDocument* doc = JsonbDocument::createDocument(val.data, val.size);
if (UNLIKELY(!doc || !doc->getValue())) {
null_map[i] = 1;
res[i] = 0;
continue;
}
// value is NOT necessary to be deleted since JsonbValue will not allocate memory
JsonbValue* value = doc->getValue();
if (UNLIKELY(!value)) {
null_map[i] = 1;
res[i] = 0;
continue;
}
if constexpr (type_index == TypeIndex::UInt8) {
if (value->isTrue()) {
res[i] = 1;
} else if (value->isFalse()) {
res[i] = 0;
} else {
null_map[i] = 1;
res[i] = 0;
}
} else if constexpr (type_index == TypeIndex::Int8) {
if (value->isInt8()) {
res[i] = ((const JsonbIntVal*)value)->val();
} else {
null_map[i] = 1;
res[i] = 0;
}
} else if constexpr (type_index == TypeIndex::Int16) {
if (value->isInt8() || value->isInt16()) {
res[i] = (int16_t)((const JsonbIntVal*)value)->val();
} else {
null_map[i] = 1;
res[i] = 0;
}
} else if constexpr (type_index == TypeIndex::Int32) {
if (value->isInt8() || value->isInt16() || value->isInt32()) {
res[i] = (int32_t)((const JsonbIntVal*)value)->val();
} else {
null_map[i] = 1;
res[i] = 0;
}
} else if constexpr (type_index == TypeIndex::Int64) {
if (value->isInt8() || value->isInt16() || value->isInt32() ||
value->isInt64()) {
res[i] = ((const JsonbIntVal*)value)->val();
} else {
null_map[i] = 1;
res[i] = 0;
}
} else if constexpr (type_index == TypeIndex::Float64) {
if (value->isDouble()) {
res[i] = ((const JsonbDoubleVal*)value)->val();
} else if (value->isInt8() || value->isInt16() || value->isInt32() ||
value->isInt64()) {
res[i] = ((const JsonbIntVal*)value)->val();
} else {
null_map[i] = 1;
res[i] = 0;
}
} else {
LOG(FATAL) << "unsupported type ";
}
}
block.replace_by_position(
result, ColumnNullable::create(std::move(col_to), std::move(null_map_col)));
} else {
return Status::RuntimeError(
"Illegal column {} of first argument of conversion function from string",
col_from.get_name());
}
return Status::OK();
}
};
template <typename ToDataType, typename Name>
struct ConvertImpl<DataTypeString, ToDataType, Name> {
template <typename Additions = void*>
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result,
size_t /*input_rows_count*/, bool check_overflow [[maybe_unused]] = false,
Additions additions [[maybe_unused]] = Additions()) {
return Status::RuntimeError("not support convert from string");
}
};
struct NameToString {
static constexpr auto name = "to_string";
};
struct NameToDecimal32 {
static constexpr auto name = "toDecimal32";
};
struct NameToDecimal64 {
static constexpr auto name = "toDecimal64";
};
struct NameToDecimal128 {
static constexpr auto name = "toDecimal128";
};
struct NameToDecimal128I {
static constexpr auto name = "toDecimal128I";
};
struct NameToUInt8 {
static constexpr auto name = "toUInt8";
};
struct NameToUInt16 {
static constexpr auto name = "toUInt16";
};
struct NameToUInt32 {
static constexpr auto name = "toUInt32";
};
struct NameToUInt64 {
static constexpr auto name = "toUInt64";
};
struct NameToInt8 {
static constexpr auto name = "toInt8";
};
struct NameToInt16 {
static constexpr auto name = "toInt16";
};
struct NameToInt32 {
static constexpr auto name = "toInt32";
};
struct NameToInt64 {
static constexpr auto name = "toInt64";
};
struct NameToInt128 {
static constexpr auto name = "toInt128";
};
struct NameToFloat32 {
static constexpr auto name = "toFloat32";
};
struct NameToFloat64 {
static constexpr auto name = "toFloat64";
};
struct NameToDate {
static constexpr auto name = "toDate";
};
struct NameToDateTime {
static constexpr auto name = "toDateTime";
};
template <typename DataType, typename Additions = void*>
bool try_parse_impl(typename DataType::FieldType& x, ReadBuffer& rb, const DateLUTImpl*,
Additions additions [[maybe_unused]] = Additions()) {
if constexpr (IsDateTimeType<DataType>) {
return try_read_datetime_text(x, rb);
}
if constexpr (IsDateType<DataType>) {
return try_read_date_text(x, rb);
}
if constexpr (IsDateV2Type<DataType>) {
return try_read_date_v2_text(x, rb);
}
if constexpr (IsDateTimeV2Type<DataType>) {
UInt32 scale = additions;
return try_read_datetime_v2_text(x, rb, scale);
}
if constexpr (std::is_floating_point_v<typename DataType::FieldType>) {
return try_read_float_text(x, rb);
}
// uint8_t now use as boolean in doris
if constexpr (std::is_same_v<typename DataType::FieldType, uint8_t>) {
return try_read_bool_text(x, rb);
}
if constexpr (std::is_integral_v<typename DataType::FieldType>) {
return try_read_int_text(x, rb);
}
if constexpr (IsDataTypeDecimal<DataType>) {
UInt32 scale = additions;
return try_read_decimal_text(x, rb, DataType::max_precision(), scale);
}
}
/// Monotonicity.
struct PositiveMonotonicity {
static bool has() { return true; }
static IFunction::Monotonicity get(const IDataType&, const Field&, const Field&) {
return {true};
}
};
struct UnknownMonotonicity {
static bool has() { return false; }
static IFunction::Monotonicity get(const IDataType&, const Field&, const Field&) {
return {false};
}
};
template <typename T>
struct ToNumberMonotonicity {
static bool has() { return true; }
static UInt64 divide_by_range_of_type(UInt64 x) {
if constexpr (sizeof(T) < sizeof(UInt64))
return x >> (sizeof(T) * 8);
else
return 0;
}
static IFunction::Monotonicity get(const IDataType& type, const Field& left,
const Field& right) {
if (!type.is_value_represented_by_number()) return {};
/// If type is same, the conversion is always monotonic.
/// (Enum has separate case, because it is different data type)
if (check_and_get_data_type<DataTypeNumber<T>>(
&type) /*|| check_and_get_data_type<DataTypeEnum<T>>(&type)*/)
return {true, true, true};
/// Float cases.
/// When converting to Float, the conversion is always monotonic.
if (std::is_floating_point_v<T>) return {true, true, true};
/// If converting from Float, for monotonicity, arguments must fit in range of result type.
if (WhichDataType(type).is_float()) {
if (left.is_null() || right.is_null()) return {};
Float64 left_float = left.get<Float64>();
Float64 right_float = right.get<Float64>();
if (left_float >= std::numeric_limits<T>::min() &&
left_float <= static_cast<Float64>(std::numeric_limits<T>::max()) &&
right_float >= std::numeric_limits<T>::min() &&
right_float <= static_cast<Float64>(std::numeric_limits<T>::max()))
return {true};
return {};
}
/// Integer cases.
const bool from_is_unsigned = type.is_value_represented_by_unsigned_integer();
const bool to_is_unsigned = std::is_unsigned_v<T>;
const size_t size_of_from = type.get_size_of_value_in_memory();
const size_t size_of_to = sizeof(T);
const bool left_in_first_half =
left.is_null() ? from_is_unsigned : (left.get<Int64>() >= 0);
const bool right_in_first_half =
right.is_null() ? !from_is_unsigned : (right.get<Int64>() >= 0);
/// Size of type is the same.
if (size_of_from == size_of_to) {
if (from_is_unsigned == to_is_unsigned) return {true, true, true};
if (left_in_first_half == right_in_first_half) return {true};
return {};
}
/// Size of type is expanded.
if (size_of_from < size_of_to) {
if (from_is_unsigned == to_is_unsigned) return {true, true, true};
if (!to_is_unsigned) return {true, true, true};
/// signed -> unsigned. If arguments from the same half, then function is monotonic.
if (left_in_first_half == right_in_first_half) return {true};
return {};
}
/// Size of type is shrinked.
if (size_of_from > size_of_to) {
/// Function cannot be monotonic on unbounded ranges.
if (left.is_null() || right.is_null()) return {};
if (from_is_unsigned == to_is_unsigned) {
/// all bits other than that fits, must be same.
if (divide_by_range_of_type(left.get<UInt64>()) ==
divide_by_range_of_type(right.get<UInt64>()))
return {true};
return {};
} else {
/// When signedness is changed, it's also required for arguments to be from the same half.
/// And they must be in the same half after converting to the result type.
if (left_in_first_half == right_in_first_half &&
(T(left.get<Int64>()) >= 0) == (T(right.get<Int64>()) >= 0) &&
divide_by_range_of_type(left.get<UInt64>()) ==
divide_by_range_of_type(right.get<UInt64>()))
return {true};
return {};
}
}
__builtin_unreachable();
}
};
/** The monotonicity for the `to_string` function is mainly determined for test purposes.
* It is doubtful that anyone is looking to optimize queries with conditions `std::to_string(CounterID) = 34`.
*/
struct ToStringMonotonicity {
static bool has() { return true; }
static IFunction::Monotonicity get(const IDataType& type, const Field& left,
const Field& right) {
IFunction::Monotonicity positive(true, true);
IFunction::Monotonicity not_monotonic;
if (left.is_null() || right.is_null()) return {};
if (left.get_type() == Field::Types::UInt64 && right.get_type() == Field::Types::UInt64) {
return (left.get<Int64>() == 0 && right.get<Int64>() == 0) ||
(floor(log10(left.get<UInt64>())) ==
floor(log10(right.get<UInt64>())))
? positive
: not_monotonic;
}
if (left.get_type() == Field::Types::Int64 && right.get_type() == Field::Types::Int64) {
return (left.get<Int64>() == 0 && right.get<Int64>() == 0) ||
(left.get<Int64>() > 0 && right.get<Int64>() > 0 &&
floor(log10(left.get<Int64>())) ==
floor(log10(right.get<Int64>())))
? positive
: not_monotonic;
}
return not_monotonic;
}
};
template <typename ToDataType, typename Name, typename MonotonicityImpl>
class FunctionConvert : public IFunction {
public:
using Monotonic = MonotonicityImpl;
static constexpr auto name = Name::name;
static constexpr bool to_decimal =
std::is_same_v<Name, NameToDecimal32> || std::is_same_v<Name, NameToDecimal64> ||
std::is_same_v<Name, NameToDecimal128> || std::is_same_v<Name, NameToDecimal128I>;
static FunctionPtr create() { return std::make_shared<FunctionConvert>(); }
String get_name() const override { return name; }
bool is_variadic() const override { return true; }
size_t get_number_of_arguments() const override { return 0; }
bool get_is_injective(const Block&) override { return std::is_same_v<Name, NameToString>; }
// This function should not be called for get DateType Ptr
// using the FunctionCast::get_return_type_impl
DataTypePtr get_return_type_impl(const ColumnsWithTypeAndName& arguments) const override {
return std::make_shared<ToDataType>();
}
bool use_default_implementation_for_constants() const override { return true; }
ColumnNumbers get_arguments_that_are_always_constant() const override { return {1}; }
Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
size_t result, size_t input_rows_count) override {
if (!arguments.size()) {
return Status::RuntimeError("Function {} expects at least 1 arguments", get_name());
}
const IDataType* from_type = block.get_by_position(arguments[0]).type.get();
Status ret_status;
/// Generic conversion of any type to String.
if constexpr (std::is_same_v<ToDataType, DataTypeString>) {
return ConvertImplGenericToString::execute(block, arguments, result);
} else {
auto call = [&](const auto& types) -> bool {
using Types = std::decay_t<decltype(types)>;
using LeftDataType = typename Types::LeftType;
using RightDataType = typename Types::RightType;
// now, cast to decimal do not execute the code
if constexpr (IsDataTypeDecimal<RightDataType>) {
if (arguments.size() != 2) {
ret_status = Status::RuntimeError(
"Function {} expects 2 arguments for Decimal.", get_name());
return true;
}
const ColumnWithTypeAndName& scale_column = block.get_by_position(arguments[1]);
UInt32 scale = extract_to_decimal_scale(scale_column);
ret_status = ConvertImpl<LeftDataType, RightDataType, Name>::execute(
block, arguments, result, input_rows_count,
context->impl()->check_overflow_for_decimal(), scale);
} else if constexpr (IsDataTypeDateTimeV2<RightDataType>) {
const ColumnWithTypeAndName& scale_column = block.get_by_position(result);
auto type =
check_and_get_data_type<DataTypeDateTimeV2>(scale_column.type.get());
ret_status = ConvertImpl<LeftDataType, RightDataType, Name>::execute(
block, arguments, result, input_rows_count,
context->impl()->check_overflow_for_decimal(), type->get_scale());
} else {
ret_status = ConvertImpl<LeftDataType, RightDataType, Name>::execute(
block, arguments, result, input_rows_count);
}
return true;
};
bool done = call_on_index_and_data_type<ToDataType>(from_type->get_type_id(), call);
if (!done) {
ret_status = Status::RuntimeError(
"Illegal type {} of argument of function {}",
block.get_by_position(arguments[0]).type->get_name(), get_name());
}
return ret_status;
}
}
bool has_information_about_monotonicity() const override { return Monotonic::has(); }
Monotonicity get_monotonicity_for_range(const IDataType& type, const Field& left,
const Field& right) const override {
return Monotonic::get(type, left, right);
}
};
using FunctionToUInt8 = FunctionConvert<DataTypeUInt8, NameToUInt8, ToNumberMonotonicity<UInt8>>;
using FunctionToUInt16 =
FunctionConvert<DataTypeUInt16, NameToUInt16, ToNumberMonotonicity<UInt16>>;
using FunctionToUInt32 =
FunctionConvert<DataTypeUInt32, NameToUInt32, ToNumberMonotonicity<UInt32>>;
using FunctionToUInt64 =
FunctionConvert<DataTypeUInt64, NameToUInt64, ToNumberMonotonicity<UInt64>>;
using FunctionToInt8 = FunctionConvert<DataTypeInt8, NameToInt8, ToNumberMonotonicity<Int8>>;
using FunctionToInt16 = FunctionConvert<DataTypeInt16, NameToInt16, ToNumberMonotonicity<Int16>>;
using FunctionToInt32 = FunctionConvert<DataTypeInt32, NameToInt32, ToNumberMonotonicity<Int32>>;
using FunctionToInt64 = FunctionConvert<DataTypeInt64, NameToInt64, ToNumberMonotonicity<Int64>>;
using FunctionToInt128 =
FunctionConvert<DataTypeInt128, NameToInt128, ToNumberMonotonicity<Int128>>;
using FunctionToFloat32 =
FunctionConvert<DataTypeFloat32, NameToFloat32, ToNumberMonotonicity<Float32>>;
using FunctionToFloat64 =
FunctionConvert<DataTypeFloat64, NameToFloat64, ToNumberMonotonicity<Float64>>;
using FunctionToString = FunctionConvert<DataTypeString, NameToString, ToStringMonotonicity>;
using FunctionToDecimal32 =
FunctionConvert<DataTypeDecimal<Decimal32>, NameToDecimal32, UnknownMonotonicity>;
using FunctionToDecimal64 =
FunctionConvert<DataTypeDecimal<Decimal64>, NameToDecimal64, UnknownMonotonicity>;
using FunctionToDecimal128 =
FunctionConvert<DataTypeDecimal<Decimal128>, NameToDecimal128, UnknownMonotonicity>;
using FunctionToDecimal128I =
FunctionConvert<DataTypeDecimal<Decimal128I>, NameToDecimal128I, UnknownMonotonicity>;
using FunctionToDate = FunctionConvert<DataTypeDate, NameToDate, UnknownMonotonicity>;
using FunctionToDateTime = FunctionConvert<DataTypeDateTime, NameToDateTime, UnknownMonotonicity>;
using FunctionToDateV2 = FunctionConvert<DataTypeDateV2, NameToDate, UnknownMonotonicity>;
using FunctionToDateTimeV2 =
FunctionConvert<DataTypeDateTimeV2, NameToDateTime, UnknownMonotonicity>;
template <typename DataType>
struct FunctionTo;
template <>
struct FunctionTo<DataTypeUInt8> {
using Type = FunctionToUInt8;
};
template <>
struct FunctionTo<DataTypeUInt16> {
using Type = FunctionToUInt16;
};
template <>
struct FunctionTo<DataTypeUInt32> {
using Type = FunctionToUInt32;
};
template <>
struct FunctionTo<DataTypeUInt64> {
using Type = FunctionToUInt64;
};
template <>
struct FunctionTo<DataTypeInt8> {
using Type = FunctionToInt8;
};
template <>
struct FunctionTo<DataTypeInt16> {
using Type = FunctionToInt16;
};
template <>
struct FunctionTo<DataTypeInt32> {
using Type = FunctionToInt32;
};
template <>
struct FunctionTo<DataTypeInt64> {
using Type = FunctionToInt64;
};
template <>
struct FunctionTo<DataTypeInt128> {
using Type = FunctionToInt128;
};
template <>
struct FunctionTo<DataTypeFloat32> {
using Type = FunctionToFloat32;
};
template <>
struct FunctionTo<DataTypeFloat64> {
using Type = FunctionToFloat64;
};
template <>
struct FunctionTo<DataTypeDecimal<Decimal32>> {
using Type = FunctionToDecimal32;
};
template <>
struct FunctionTo<DataTypeDecimal<Decimal64>> {
using Type = FunctionToDecimal64;
};
template <>
struct FunctionTo<DataTypeDecimal<Decimal128>> {
using Type = FunctionToDecimal128;
};
template <>
struct FunctionTo<DataTypeDecimal<Decimal128I>> {
using Type = FunctionToDecimal128I;
};
template <>
struct FunctionTo<DataTypeDate> {
using Type = FunctionToDate;
};
template <>
struct FunctionTo<DataTypeDateTime> {
using Type = FunctionToDateTime;
};
template <>
struct FunctionTo<DataTypeDateV2> {
using Type = FunctionToDateV2;
};
template <>
struct FunctionTo<DataTypeDateTimeV2> {
using Type = FunctionToDateTimeV2;
};
class PreparedFunctionCast : public PreparedFunctionImpl {
public:
using WrapperType = std::function<Status(FunctionContext* context, Block&, const ColumnNumbers&,
size_t, size_t)>;
explicit PreparedFunctionCast(WrapperType&& wrapper_function_, const char* name_)
: wrapper_function(std::move(wrapper_function_)), name(name_) {}
String get_name() const override { return name; }
protected:
Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
size_t result, size_t input_rows_count) override {
/// drop second argument, pass others
ColumnNumbers new_arguments {arguments.front()};
if (arguments.size() > 2)
new_arguments.insert(std::end(new_arguments), std::next(std::begin(arguments), 2),
std::end(arguments));
return wrapper_function(context, block, new_arguments, result, input_rows_count);
}
bool use_default_implementation_for_nulls() const override { return false; }
bool use_default_implementation_for_constants() const override { return true; }
bool use_default_implementation_for_low_cardinality_columns() const override { return false; }
ColumnNumbers get_arguments_that_are_always_constant() const override { return {1}; }
private:
WrapperType wrapper_function;
const char* name;
};
struct NameCast {
static constexpr auto name = "CAST";
};
template <typename FromDataType, typename ToDataType, typename Name>
struct ConvertThroughParsing {
static_assert(std::is_same_v<FromDataType, DataTypeString>,
"ConvertThroughParsing is only applicable for String or FixedString data types");
using ToFieldType = typename ToDataType::FieldType;
static bool is_all_read(ReadBuffer& in) { return in.eof(); }
template <typename Additions = void*>
static Status execute(Block& block, const ColumnNumbers& arguments, size_t result,
size_t input_rows_count, bool check_overflow [[maybe_unused]] = false,
Additions additions [[maybe_unused]] = Additions()) {
using ColVecTo = std::conditional_t<IsDecimalNumber<ToFieldType>,
ColumnDecimal<ToFieldType>, ColumnVector<ToFieldType>>;
const DateLUTImpl* local_time_zone [[maybe_unused]] = nullptr;
const DateLUTImpl* utc_time_zone [[maybe_unused]] = nullptr;
const IColumn* col_from = block.get_by_position(arguments[0]).column.get();
const ColumnString* col_from_string = check_and_get_column<ColumnString>(col_from);
if (std::is_same_v<FromDataType, DataTypeString> && !col_from_string) {
return Status::RuntimeError("Illegal column {} of first argument of function {}",
col_from->get_name(), Name::name);
}
size_t size = input_rows_count;
typename ColVecTo::MutablePtr col_to = nullptr;
if constexpr (IsDataTypeDecimal<ToDataType>) {
UInt32 scale = additions;
col_to = ColVecTo::create(size, scale);
} else {
col_to = ColVecTo::create(size);
}
typename ColVecTo::Container& vec_to = col_to->get_data();
ColumnUInt8::MutablePtr col_null_map_to;
ColumnUInt8::Container* vec_null_map_to [[maybe_unused]] = nullptr;
col_null_map_to = ColumnUInt8::create(size);
vec_null_map_to = &col_null_map_to->get_data();
const ColumnString::Chars* chars = nullptr;
const IColumn::Offsets* offsets = nullptr;
size_t fixed_string_size = 0;
if constexpr (std::is_same_v<FromDataType, DataTypeString>) {
chars = &col_from_string->get_chars();
offsets = &col_from_string->get_offsets();
}
size_t current_offset = 0;
for (size_t i = 0; i < size; ++i) {
size_t next_offset = std::is_same_v<FromDataType, DataTypeString>
? (*offsets)[i]
: (current_offset + fixed_string_size);
size_t string_size = std::is_same_v<FromDataType, DataTypeString>
? next_offset - current_offset
: fixed_string_size;
ReadBuffer read_buffer(&(*chars)[current_offset], string_size);
bool parsed;
if constexpr (IsDataTypeDecimal<ToDataType>) {
parsed = try_parse_impl<ToDataType>(vec_to[i], read_buffer, local_time_zone,
vec_to.get_scale());
} else if constexpr (IsDataTypeDateTimeV2<ToDataType>) {
auto type = check_and_get_data_type<DataTypeDateTimeV2>(
block.get_by_position(result).type.get());
parsed = try_parse_impl<ToDataType>(vec_to[i], read_buffer, local_time_zone,
type->get_scale());
} else {
parsed = try_parse_impl<ToDataType>(vec_to[i], read_buffer, local_time_zone);
}
(*vec_null_map_to)[i] = !parsed || !is_all_read(read_buffer);
current_offset = next_offset;
}
block.get_by_position(result).column =
ColumnNullable::create(std::move(col_to), std::move(col_null_map_to));
return Status::OK();
}
};
template <typename Name>
struct ConvertImpl<DataTypeString, DataTypeDecimal<Decimal32>, Name>
: ConvertThroughParsing<DataTypeString, DataTypeDecimal<Decimal32>, Name> {};
template <typename Name>
struct ConvertImpl<DataTypeString, DataTypeDecimal<Decimal64>, Name>
: ConvertThroughParsing<DataTypeString, DataTypeDecimal<Decimal64>, Name> {};
template <typename Name>
struct ConvertImpl<DataTypeString, DataTypeDecimal<Decimal128>, Name>
: ConvertThroughParsing<DataTypeString, DataTypeDecimal<Decimal128>, Name> {};
template <typename Name>
struct ConvertImpl<DataTypeString, DataTypeDecimal<Decimal128I>, Name>
: ConvertThroughParsing<DataTypeString, DataTypeDecimal<Decimal128I>, Name> {};
template <typename ToDataType, typename Name>
class FunctionConvertFromString : public IFunction {
public:
static constexpr auto name = Name::name;
static FunctionPtr create() { return std::make_shared<FunctionConvertFromString>(); }
String get_name() const override { return name; }
bool is_variadic() const override { return true; }
size_t get_number_of_arguments() const override { return 0; }
bool use_default_implementation_for_constants() const override { return true; }
ColumnNumbers get_arguments_that_are_always_constant() const override { return {1}; }
// This function should not be called for get DateType Ptr
// using the FunctionCast::get_return_type_impl
DataTypePtr get_return_type_impl(const ColumnsWithTypeAndName& arguments) const override {
DataTypePtr res;
if constexpr (IsDataTypeDecimal<ToDataType>) {
LOG(FATAL) << "Someting wrong with toDecimalNNOrZero() or toDecimalNNOrNull()";
} else
res = std::make_shared<ToDataType>();
return res;
}
Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
size_t result, size_t input_rows_count) override {
const IDataType* from_type = block.get_by_position(arguments[0]).type.get();
if (check_and_get_data_type<DataTypeString>(from_type)) {
return ConvertThroughParsing<DataTypeString, ToDataType, Name>::execute(
block, arguments, result, input_rows_count);
}
return Status::RuntimeError(
"Illegal type {} of argument of function {} . Only String or FixedString "
"argument is accepted for try-conversion function. For other arguments, use "
"function without 'orZero' or 'orNull'.",
block.get_by_position(arguments[0]).type->get_name(), get_name());
}
};
template <typename ToDataType, typename Name>
class FunctionConvertToTimeType : public IFunction {
public:
static constexpr auto name = Name::name;
static FunctionPtr create() { return std::make_shared<FunctionConvertToTimeType>(); }
String get_name() const override { return name; }
bool is_variadic() const override { return true; }
size_t get_number_of_arguments() const override { return 0; }
bool use_default_implementation_for_constants() const override { return true; }
ColumnNumbers get_arguments_that_are_always_constant() const override { return {1}; }
// This function should not be called for get DateType Ptr
// using the FunctionCast::get_return_type_impl
DataTypePtr get_return_type_impl(const ColumnsWithTypeAndName& arguments) const override {
return std::make_shared<ToDataType>();
}
Status execute_impl(FunctionContext* context, Block& block, const ColumnNumbers& arguments,
size_t result, size_t input_rows_count) override {
Status ret_status = Status::OK();
const IDataType* from_type = block.get_by_position(arguments[0]).type.get();
auto call = [&](const auto& types) -> bool {
using Types = std::decay_t<decltype(types)>;
using LeftDataType = typename Types::LeftType;
using RightDataType = typename Types::RightType;
ret_status = ConvertImplToTimeType<LeftDataType, RightDataType, Name>::execute(
block, arguments, result, input_rows_count);
return true;
};
bool done = call_on_index_and_number_data_type<ToDataType>(from_type->get_type_id(), call);
if (!done) {
return Status::RuntimeError("Illegal type {} of argument of function {}",
block.get_by_position(arguments[0]).type->get_name(),
get_name());
}
return ret_status;
}
};
class FunctionCast final : public IFunctionBase {
public:
using WrapperType =
std::function<Status(FunctionContext*, Block&, const ColumnNumbers&, size_t, size_t)>;
using MonotonicityForRange =
std::function<Monotonicity(const IDataType&, const Field&, const Field&)>;
FunctionCast(const char* name_, MonotonicityForRange&& monotonicity_for_range_,
const DataTypes& argument_types_, const DataTypePtr& return_type_)
: name(name_),
monotonicity_for_range(monotonicity_for_range_),
argument_types(argument_types_),
return_type(return_type_) {}
const DataTypes& get_argument_types() const override { return argument_types; }
const DataTypePtr& get_return_type() const override { return return_type; }
PreparedFunctionPtr prepare(FunctionContext* context, const Block& /*sample_block*/,
const ColumnNumbers& /*arguments*/,
size_t /*result*/) const override {
return std::make_shared<PreparedFunctionCast>(
prepare_unpack_dictionaries(context, get_argument_types()[0], get_return_type()),
name);
}
String get_name() const override { return name; }
bool is_deterministic() const override { return true; }
bool is_deterministic_in_scope_of_query() const override { return true; }
bool has_information_about_monotonicity() const override {
return static_cast<bool>(monotonicity_for_range);
}
Monotonicity get_monotonicity_for_range(const IDataType& type, const Field& left,
const Field& right) const override {
return monotonicity_for_range(type, left, right);
}
private:
const char* name;
MonotonicityForRange monotonicity_for_range;
DataTypes argument_types;
DataTypePtr return_type;
template <typename DataType>
WrapperType create_wrapper(const DataTypePtr& from_type, const DataType* const,
bool requested_result_is_nullable) const {
FunctionPtr function;
if (requested_result_is_nullable &&
check_and_get_data_type<DataTypeString>(from_type.get())) {
/// In case when converting to Nullable type, we apply different parsing rule,
/// that will not throw an exception but return NULL in case of malformed input.
function = FunctionConvertFromString<DataType, NameCast>::create();
} else if (requested_result_is_nullable &&
(IsTimeType<DataType> || IsTimeV2Type<DataType>)&&!(
check_and_get_data_type<DataTypeDateTime>(from_type.get()) ||
check_and_get_data_type<DataTypeDate>(from_type.get()) ||
check_and_get_data_type<DataTypeDateV2>(from_type.get()) ||
check_and_get_data_type<DataTypeDateTimeV2>(from_type.get()))) {
function = FunctionConvertToTimeType<DataType, NameCast>::create();
} else {
function = FunctionTo<DataType>::Type::create();
}
/// Check conversion using underlying function
{ function->get_return_type(ColumnsWithTypeAndName(1, {nullptr, from_type, ""})); }
return [function](FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
return function->execute(context, block, arguments, result, input_rows_count);
};
}
WrapperType create_string_wrapper(const DataTypePtr& from_type) const {
FunctionPtr function = FunctionToString::create();
/// Check conversion using underlying function
{ function->get_return_type(ColumnsWithTypeAndName(1, {nullptr, from_type, ""})); }
return [function](FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
return function->execute(context, block, arguments, result, input_rows_count);
};
}
template <typename FieldType>
WrapperType create_decimal_wrapper(const DataTypePtr& from_type,
const DataTypeDecimal<FieldType>* to_type) const {
using ToDataType = DataTypeDecimal<FieldType>;
TypeIndex type_index = from_type->get_type_id();
UInt32 precision = to_type->get_precision();
UInt32 scale = to_type->get_scale();
WhichDataType which(type_index);
bool ok = which.is_int() || which.is_native_uint() || which.is_decimal() ||
which.is_float() || which.is_date_or_datetime() ||
which.is_date_v2_or_datetime_v2() || which.is_string_or_fixed_string();
if (!ok) {
return create_unsupport_wrapper(from_type->get_name(), to_type->get_name());
}
return [type_index, precision, scale](FunctionContext* context, Block& block,
const ColumnNumbers& arguments, const size_t result,
size_t input_rows_count) {
auto res = call_on_index_and_data_type<ToDataType>(
type_index, [&](const auto& types) -> bool {
using Types = std::decay_t<decltype(types)>;
using LeftDataType = typename Types::LeftType;
using RightDataType = typename Types::RightType;
ConvertImpl<LeftDataType, RightDataType, NameCast>::execute(
block, arguments, result, input_rows_count,
context->impl()->check_overflow_for_decimal(), scale);
return true;
});
/// Additionally check if call_on_index_and_data_type wasn't called at all.
if (!res) {
auto to = DataTypeDecimal<FieldType>(precision, scale);
return Status::RuntimeError("Conversion from {} to {} is not supported",
getTypeName(type_index), to.get_name());
}
return Status::OK();
};
}
WrapperType create_identity_wrapper(const DataTypePtr&) const {
return [](FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t /*input_rows_count*/) {
block.get_by_position(result).column = block.get_by_position(arguments.front()).column;
return Status::OK();
};
}
WrapperType create_nothing_wrapper(const IDataType* to_type) const {
ColumnPtr res = to_type->create_column_const_with_default_value(1);
return [res](FunctionContext* context, Block& block, const ColumnNumbers&,
const size_t result, size_t input_rows_count) {
/// Column of Nothing type is trivially convertible to any other column
block.get_by_position(result).column =
res->clone_resized(input_rows_count)->convert_to_full_column_if_const();
return Status::OK();
};
}
WrapperType create_unsupport_wrapper(const String error_msg) const {
LOG(WARNING) << error_msg;
return [error_msg](FunctionContext* /*context*/, Block& /*block*/,
const ColumnNumbers& /*arguments*/, const size_t /*result*/,
size_t /*input_rows_count*/) {
return Status::InvalidArgument(error_msg);
};
}
WrapperType create_unsupport_wrapper(const String from_type_name,
const String to_type_name) const {
const String error_msg = fmt::format("Conversion from {} to {} is not supported",
from_type_name, to_type_name);
return create_unsupport_wrapper(error_msg);
}
WrapperType create_array_wrapper(FunctionContext* context, const DataTypePtr& from_type_untyped,
const DataTypeArray& to_type) const {
/// Conversion from String through parsing.
if (check_and_get_data_type<DataTypeString>(from_type_untyped.get())) {
return &ConvertImplGenericFromString<ColumnString>::execute;
}
const auto* from_type = check_and_get_data_type<DataTypeArray>(from_type_untyped.get());
if (!from_type) {
return create_unsupport_wrapper(
"CAST AS Array can only be performed between same-dimensional Array, String "
"types");
}
DataTypePtr from_nested_type = from_type->get_nested_type();
/// In query SELECT CAST([] AS Array(Array(String))) from type is Array(Nothing)
bool from_empty_array = is_nothing(from_nested_type);
if (from_type->get_number_of_dimensions() != to_type.get_number_of_dimensions() &&
!from_empty_array) {
return create_unsupport_wrapper(
"CAST AS Array can only be performed between same-dimensional array types");
}
const DataTypePtr& to_nested_type = to_type.get_nested_type();
/// Prepare nested type conversion
const auto nested_function =
prepare_unpack_dictionaries(context, from_nested_type, to_nested_type);
return [nested_function, from_nested_type, to_nested_type](
FunctionContext* context, Block& block, const ColumnNumbers& arguments,
const size_t result, size_t /*input_rows_count*/) -> Status {
auto& from_column = block.get_by_position(arguments.front()).column;
const ColumnArray* from_col_array =
check_and_get_column<ColumnArray>(from_column.get());
if (from_col_array) {
/// create columns for converting nested column containing original and result columns
ColumnWithTypeAndName from_nested_column {from_col_array->get_data_ptr(),
from_nested_type, ""};
/// convert nested column
ColumnNumbers new_arguments {block.columns()};
block.insert(from_nested_column);
size_t nested_result = block.columns();
block.insert({to_nested_type, ""});
RETURN_IF_ERROR(nested_function(context, block, new_arguments, nested_result,
from_col_array->get_data_ptr()->size()));
auto nested_result_column = block.get_by_position(nested_result).column;
/// set converted nested column to result
block.get_by_position(result).column = ColumnArray::create(
nested_result_column, from_col_array->get_offsets_ptr());
} else {
return Status::RuntimeError("Illegal column {} for function CAST AS Array",
from_column->get_name());
}
return Status::OK();
};
}
// check jsonb value type and get to_type value
WrapperType create_jsonb_wrapper(const DataTypeJsonb& from_type,
const DataTypePtr& to_type) const {
// Conversion from String through parsing.
if (check_and_get_data_type<DataTypeString>(to_type.get())) {
return &ConvertImplGenericToString::execute2;
}
switch (to_type->get_type_id()) {
case TypeIndex::UInt8:
return &ConvertImplFromJsonb<TypeIndex::UInt8, ColumnUInt8>::execute;
case TypeIndex::Int8:
return &ConvertImplFromJsonb<TypeIndex::Int8, ColumnInt8>::execute;
case TypeIndex::Int16:
return &ConvertImplFromJsonb<TypeIndex::Int16, ColumnInt16>::execute;
case TypeIndex::Int32:
return &ConvertImplFromJsonb<TypeIndex::Int32, ColumnInt32>::execute;
case TypeIndex::Int64:
return &ConvertImplFromJsonb<TypeIndex::Int64, ColumnInt64>::execute;
case TypeIndex::Float64:
return &ConvertImplFromJsonb<TypeIndex::Float64, ColumnFloat64>::execute;
default:
return create_unsupport_wrapper(from_type.get_name(), to_type->get_name());
}
return nullptr;
}
// create cresponding jsonb value with type to_type
// use jsonb writer to create jsonb value
WrapperType create_jsonb_wrapper(const DataTypePtr& from_type,
const DataTypeJsonb& to_type) const {
switch (from_type->get_type_id()) {
case TypeIndex::UInt8:
return &ConvertImplNumberToJsonb<ColumnUInt8>::execute;
case TypeIndex::Int8:
return &ConvertImplNumberToJsonb<ColumnInt8>::execute;
case TypeIndex::Int16:
return &ConvertImplNumberToJsonb<ColumnInt16>::execute;
case TypeIndex::Int32:
return &ConvertImplNumberToJsonb<ColumnInt32>::execute;
case TypeIndex::Int64:
return &ConvertImplNumberToJsonb<ColumnInt64>::execute;
case TypeIndex::Float64:
return &ConvertImplNumberToJsonb<ColumnFloat64>::execute;
case TypeIndex::String:
return &ConvertImplGenericFromString<ColumnString>::execute;
default:
return &ConvertImplGenericToJsonb::execute;
}
}
WrapperType prepare_unpack_dictionaries(FunctionContext* context, const DataTypePtr& from_type,
const DataTypePtr& to_type) const {
const auto& from_nested = from_type;
const auto& to_nested = to_type;
if (from_type->only_null()) {
if (!to_nested->is_nullable()) {
return create_unsupport_wrapper("Cannot convert NULL to a non-nullable type");
}
return [](FunctionContext* context, Block& block, const ColumnNumbers&,
const size_t result, size_t input_rows_count) {
auto& res = block.get_by_position(result);
res.column = res.type->create_column_const_with_default_value(input_rows_count)
->convert_to_full_column_if_const();
return Status::OK();
};
}
constexpr bool skip_not_null_check = false;
auto wrapper =
prepare_remove_nullable(context, from_nested, to_nested, skip_not_null_check);
return wrapper;
}
WrapperType prepare_remove_nullable(FunctionContext* context, const DataTypePtr& from_type,
const DataTypePtr& to_type,
bool skip_not_null_check) const {
/// Determine whether pre-processing and/or post-processing must take place during conversion.
bool source_is_nullable = from_type->is_nullable();
bool result_is_nullable = to_type->is_nullable();
auto wrapper = prepare_impl(context, remove_nullable(from_type), remove_nullable(to_type),
result_is_nullable);
if (result_is_nullable) {
return [wrapper, source_is_nullable](FunctionContext* context, Block& block,
const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
/// Create a temporary block on which to perform the operation.
auto& res = block.get_by_position(result);
const auto& ret_type = res.type;
const auto& nullable_type = static_cast<const DataTypeNullable&>(*ret_type);
const auto& nested_type = nullable_type.get_nested_type();
Block tmp_block;
size_t tmp_res_index = 0;
if (source_is_nullable) {
auto [t_block, tmp_args] =
create_block_with_nested_columns(block, arguments, true);
tmp_block = std::move(t_block);
tmp_res_index = tmp_block.columns();
tmp_block.insert({nullptr, nested_type, ""});
/// Perform the requested conversion.
RETURN_IF_ERROR(
wrapper(context, tmp_block, {0}, tmp_res_index, input_rows_count));
} else {
tmp_block = block;
tmp_res_index = block.columns();
tmp_block.insert({nullptr, nested_type, ""});
/// Perform the requested conversion.
RETURN_IF_ERROR(wrapper(context, tmp_block, arguments, tmp_res_index,
input_rows_count));
}
// Note: here we should return the nullable result column
const auto& tmp_res = tmp_block.get_by_position(tmp_res_index);
res.column = wrap_in_nullable(tmp_res.column,
Block({block.get_by_position(arguments[0]), tmp_res}),
{0}, 1, input_rows_count);
return Status::OK();
};
} else if (source_is_nullable) {
/// Conversion from Nullable to non-Nullable.
return [wrapper, skip_not_null_check](FunctionContext* context, Block& block,
const ColumnNumbers& arguments,
const size_t result, size_t input_rows_count) {
auto [tmp_block, tmp_args, tmp_res] =
create_block_with_nested_columns(block, arguments, result);
/// Check that all values are not-NULL.
/// Check can be skipped in case if LowCardinality dictionary is transformed.
/// In that case, correctness will be checked beforehand.
if (!skip_not_null_check) {
const auto& col = block.get_by_position(arguments[0]).column;
const auto& nullable_col = assert_cast<const ColumnNullable&>(*col);
const auto& null_map = nullable_col.get_null_map_data();
if (!memory_is_zero(null_map.data(), null_map.size())) {
return Status::RuntimeError(
"Cannot convert NULL value to non-Nullable type");
}
}
RETURN_IF_ERROR(wrapper(context, tmp_block, tmp_args, tmp_res, input_rows_count));
block.get_by_position(result).column = tmp_block.get_by_position(tmp_res).column;
return Status::OK();
};
} else {
return wrapper;
}
}
/// 'from_type' and 'to_type' are nested types in case of Nullable.
/// 'requested_result_is_nullable' is true if CAST to Nullable type is requested.
WrapperType prepare_impl(FunctionContext* context, const DataTypePtr& from_type,
const DataTypePtr& to_type, bool requested_result_is_nullable) const {
if (from_type->equals(*to_type))
return create_identity_wrapper(from_type);
else if (WhichDataType(from_type).is_nothing())
return create_nothing_wrapper(to_type.get());
if (from_type->get_type_id() == TypeIndex::JSONB) {
return create_jsonb_wrapper(static_cast<const DataTypeJsonb&>(*from_type), to_type);
}
if (to_type->get_type_id() == TypeIndex::JSONB) {
return create_jsonb_wrapper(from_type, static_cast<const DataTypeJsonb&>(*to_type));
}
WrapperType ret;
auto make_default_wrapper = [&](const auto& types) -> bool {
using Types = std::decay_t<decltype(types)>;
using ToDataType = typename Types::LeftType;
if constexpr (std::is_same_v<ToDataType, DataTypeUInt8> ||
std::is_same_v<ToDataType, DataTypeUInt16> ||
std::is_same_v<ToDataType, DataTypeUInt32> ||
std::is_same_v<ToDataType, DataTypeUInt64> ||
std::is_same_v<ToDataType, DataTypeInt8> ||
std::is_same_v<ToDataType, DataTypeInt16> ||
std::is_same_v<ToDataType, DataTypeInt32> ||
std::is_same_v<ToDataType, DataTypeInt64> ||
std::is_same_v<ToDataType, DataTypeInt128> ||
std::is_same_v<ToDataType, DataTypeFloat32> ||
std::is_same_v<ToDataType, DataTypeFloat64> ||
std::is_same_v<ToDataType, DataTypeDate> ||
std::is_same_v<ToDataType, DataTypeDateTime> ||
std::is_same_v<ToDataType, DataTypeDateV2> ||
std::is_same_v<ToDataType, DataTypeDateTimeV2>) {
ret = create_wrapper(from_type, check_and_get_data_type<ToDataType>(to_type.get()),
requested_result_is_nullable);
return true;
}
if constexpr (std::is_same_v<ToDataType, DataTypeDecimal<Decimal32>> ||
std::is_same_v<ToDataType, DataTypeDecimal<Decimal64>> ||
std::is_same_v<ToDataType, DataTypeDecimal<Decimal128>> ||
std::is_same_v<ToDataType, DataTypeDecimal<Decimal128I>>) {
ret = create_decimal_wrapper(from_type,
check_and_get_data_type<ToDataType>(to_type.get()));
return true;
}
return false;
};
if (call_on_index_and_data_type<void>(to_type->get_type_id(), make_default_wrapper))
return ret;
switch (to_type->get_type_id()) {
case TypeIndex::String:
return create_string_wrapper(from_type);
case TypeIndex::Array:
return create_array_wrapper(context, from_type,
static_cast<const DataTypeArray&>(*to_type));
default:
break;
}
return create_unsupport_wrapper(from_type->get_name(), to_type->get_name());
}
};
class FunctionBuilderCast : public FunctionBuilderImpl {
public:
using MonotonicityForRange = FunctionCast::MonotonicityForRange;
static constexpr auto name = "CAST";
static FunctionBuilderPtr create() { return std::make_shared<FunctionBuilderCast>(); }
FunctionBuilderCast() {}
String get_name() const override { return name; }
size_t get_number_of_arguments() const override { return 2; }
ColumnNumbers get_arguments_that_are_always_constant() const override { return {1}; }
protected:
FunctionBasePtr build_impl(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;
auto monotonicity = get_monotonicity_information(arguments.front().type, return_type.get());
return std::make_shared<FunctionCast>(name, std::move(monotonicity), data_types,
return_type);
}
DataTypePtr get_return_type_impl(const ColumnsWithTypeAndName& arguments) const override {
const auto type_col =
check_and_get_column_const<ColumnString>(arguments.back().column.get());
if (!type_col) {
LOG(FATAL) << fmt::format(
"Second argument to {} must be a constant string describing type", get_name());
}
auto type = DataTypeFactory::instance().get(type_col->get_value<String>());
DCHECK(type != nullptr);
bool need_to_be_nullable = false;
// 1. from_type is nullable
need_to_be_nullable |= arguments[0].type->is_nullable();
// 2. from_type is string, to_type is not string
need_to_be_nullable |= (arguments[0].type->get_type_id() == TypeIndex::String) &&
(type->get_type_id() != TypeIndex::String);
// 3. from_type is not DateTime/Date, to_type is DateTime/Date
need_to_be_nullable |= (arguments[0].type->get_type_id() != TypeIndex::Date &&
arguments[0].type->get_type_id() != TypeIndex::DateTime) &&
(type->get_type_id() == TypeIndex::Date ||
type->get_type_id() == TypeIndex::DateTime);
// 4. from_type is not DateTimeV2/DateV2, to_type is DateTimeV2/DateV2
need_to_be_nullable |= (arguments[0].type->get_type_id() != TypeIndex::DateV2 &&
arguments[0].type->get_type_id() != TypeIndex::DateTimeV2) &&
(type->get_type_id() == TypeIndex::DateV2 ||
type->get_type_id() == TypeIndex::DateTimeV2);
if (need_to_be_nullable) {
return make_nullable(type);
}
return type;
}
bool use_default_implementation_for_nulls() const override { return false; }
bool use_default_implementation_for_low_cardinality_columns() const override { return false; }
private:
template <typename DataType>
static auto monotonicity_for_type(const DataType* const) {
return FunctionTo<DataType>::Type::Monotonic::get;
}
MonotonicityForRange get_monotonicity_information(const DataTypePtr& from_type,
const IDataType* to_type) const {
if (const auto type = check_and_get_data_type<DataTypeUInt8>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeUInt16>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeUInt32>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeUInt64>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeInt8>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeInt16>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeInt32>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeInt64>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeFloat32>(to_type))
return monotonicity_for_type(type);
if (const auto type = check_and_get_data_type<DataTypeFloat64>(to_type))
return monotonicity_for_type(type);
/// other types like Null, FixedString, Array and Tuple have no monotonicity defined
return {};
}
};
} // namespace doris::vectorized
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