AshinGau commented on code in PR #25138: URL: https://github.com/apache/doris/pull/25138#discussion_r1365056305
########## be/src/vec/exec/format/parquet/parquet_column_convert.h: ########## @@ -0,0 +1,623 @@ +// 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. + +#include <gen_cpp/PlanNodes_types.h> +#include <gen_cpp/Types_types.h> +#include <gen_cpp/parquet_types.h> + +#include <algorithm> +#include <functional> +#include <ostream> +#include <utility> + +#include "common/compiler_util.h" // IWYU pragma: keep +#include "common/status.h" +#include "gen_cpp/descriptors.pb.h" +#include "gutil/endian.h" +#include "io/file_factory.h" +#include "olap/olap_common.h" +#include "util/coding.h" +#include "util/slice.h" +#include "vec/columns/column_string.h" +#include "vec/columns/column_vector.h" +#include "vec/core/types.h" +#include "vec/data_types/data_type.h" +#include "vec/data_types/data_type_factory.hpp" +#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/exec/format/format_common.h" +#include "vec/exec/format/parquet/decoder.h" +#include "vec/exec/format/parquet/parquet_common.h" +namespace doris::vectorized { + +namespace ParquetConvert { + +template <tparquet::Type::type ParquetType> +struct PhysicalTypeTraits {}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::INT32> { + using DataType = int32_t; + using ColumnType = ColumnVector<DataType>; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::INT64> { + using DataType = int64_t; + using ColumnType = ColumnVector<DataType>; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::FLOAT> { + using DataType = float; + using ColumnType = ColumnVector<DataType>; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::DOUBLE> { + using DataType = double; + using ColumnType = ColumnVector<DataType>; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::BYTE_ARRAY> { + using DataType = String; + using ColumnType = ColumnString; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::FIXED_LEN_BYTE_ARRAY> { + using DataType = String; + using ColumnType = ColumnString; +}; + +template <> +struct PhysicalTypeTraits<tparquet::Type::INT96> { + using DataType = Int128; + using ColumnType = ColumnVector<DataType>; +}; + +#define FOR_LOGICAL_NUMERIC_TYPES(M) \ + M(TypeIndex::Int8, Int8, Int32) \ + M(TypeIndex::UInt8, UInt8, Int32) \ + M(TypeIndex::Int16, Int16, Int32) \ + M(TypeIndex::UInt16, UInt16, Int32) \ + M(TypeIndex::Int32, Int32, Int32) \ + M(TypeIndex::UInt32, UInt32, Int32) \ + M(TypeIndex::Int64, Int64, Int64) \ + M(TypeIndex::UInt64, UInt64, Int64) \ + M(TypeIndex::Float32, Float32, Float32) \ + M(TypeIndex::Float64, Float64, Float64) + +#define FOR_LOGICAL_DECIMAL_TYPES(M) \ + M(TypeIndex::Decimal32, Decimal32, Int32) \ + M(TypeIndex::Decimal64, Decimal64, Int64) \ + M(TypeIndex::Decimal128, Decimal128, Int128) \ + M(TypeIndex::Decimal128I, Decimal128, Int128) + +struct ConvertParams { + // schema.logicalType.TIMESTAMP.isAdjustedToUTC == false + static const cctz::time_zone utc0; + // schema.logicalType.TIMESTAMP.isAdjustedToUTC == true, we should set the time zone + cctz::time_zone* ctz = nullptr; + size_t offset_days = 0; + int64_t second_mask = 1; + int64_t scale_to_nano_factor = 1; + DecimalScaleParams decimal_scale; + FieldSchema* field_schema = nullptr; + size_t start_idx = 0; + + void init(FieldSchema* field_schema_, cctz::time_zone* ctz_) { + field_schema = field_schema_; + if (ctz_ != nullptr) { + ctz = ctz_; + } + const auto& schema = field_schema->parquet_schema; + if (schema.__isset.logicalType && schema.logicalType.__isset.TIMESTAMP) { + const auto& timestamp_info = schema.logicalType.TIMESTAMP; + if (!timestamp_info.isAdjustedToUTC) { + // should set timezone to utc+0 + ctz = const_cast<cctz::time_zone*>(&utc0); + } + const auto& time_unit = timestamp_info.unit; + if (time_unit.__isset.MILLIS) { + second_mask = 1000; + scale_to_nano_factor = 1000000; + } else if (time_unit.__isset.MICROS) { + second_mask = 1000000; + scale_to_nano_factor = 1000; + } else if (time_unit.__isset.NANOS) { + second_mask = 1000000000; + scale_to_nano_factor = 1; + } + } else if (schema.__isset.converted_type) { + const auto& converted_type = schema.converted_type; + if (converted_type == tparquet::ConvertedType::TIMESTAMP_MILLIS) { + second_mask = 1000; + scale_to_nano_factor = 1000000; + } else if (converted_type == tparquet::ConvertedType::TIMESTAMP_MICROS) { + second_mask = 1000000; + scale_to_nano_factor = 1000; + } + } + + if (ctz) { + VecDateTimeValue t; + t.from_unixtime(0, *ctz); + offset_days = t.day() == 31 ? 0 : 1; + } + } + + template <typename DecimalPrimitiveType> + void init_decimal_converter(DataTypePtr& data_type) { + if (field_schema == nullptr || decimal_scale.scale_type != DecimalScaleParams::NOT_INIT) { + return; + } + auto scale = field_schema->parquet_schema.scale; + auto* decimal_type = static_cast<DataTypeDecimal<Decimal<DecimalPrimitiveType>>*>( + const_cast<IDataType*>(remove_nullable(data_type).get())); + auto dest_scale = decimal_type->get_scale(); + if (dest_scale > scale) { + decimal_scale.scale_type = DecimalScaleParams::SCALE_UP; + decimal_scale.scale_factor = + DecimalScaleParams::get_scale_factor<DecimalPrimitiveType>(dest_scale - scale); + } else if (dest_scale < scale) { + decimal_scale.scale_type = DecimalScaleParams::SCALE_DOWN; + decimal_scale.scale_factor = + DecimalScaleParams::get_scale_factor<DecimalPrimitiveType>(scale - dest_scale); + } else { + decimal_scale.scale_type = DecimalScaleParams::NO_SCALE; + decimal_scale.scale_factor = 1; + } + } +}; + +Status convert_data_type_from_parquet(tparquet::Type::type parquet_type, PrimitiveType, + vectorized::DataTypePtr& ans_data_type, DataTypePtr& src_type, + bool* need_convert); + +struct ColumnConvert { + virtual Status convert(const IColumn* src_col, IColumn* dst_col) { return Status::OK(); } + + virtual ~ColumnConvert() = default; + + void convert_null(const IColumn** src_col, IColumn** dst_col) const { + size_t rows = (*src_col)->size(); + if ((*src_col)->is_nullable()) { + auto src_nullable_column = static_cast<const ColumnNullable*>(*src_col); + auto dst_nullable_column = static_cast<ColumnNullable*>(*dst_col); + auto& src_null_data = src_nullable_column->get_null_map_column().get_data(); + dst_nullable_column->get_null_map_column().resize(_convert_params->start_idx + rows); + auto& dst_null_data = dst_nullable_column->get_null_map_column().get_data(); + for (auto j = 0; j < rows; j++) { + dst_null_data[_convert_params->start_idx + j] = src_null_data[j]; + } + + *src_col = &src_nullable_column->get_nested_column(); + *dst_col = &dst_nullable_column->get_nested_column(); + } + } + +public: + ConvertParams* _convert_params; +}; + +template <typename src_type, typename dst_type, bool is_nullable> +struct NumberColumnConvert : public ColumnConvert { + Status convert(const IColumn* src_col, IColumn* dst_col) override; +}; + +template <typename src_type, typename dst_type, bool is_nullable> +Status NumberColumnConvert<src_type, dst_type, is_nullable>::convert(const IColumn* src_col, + IColumn* dst_col) { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + auto& src_data = static_cast<const ColumnVector<src_type>*>(src_col)->get_data(); + dst_col->resize(_convert_params->start_idx + rows); + auto& data = static_cast<ColumnVector<dst_type>*>(dst_col)->get_data(); + + for (int i = 0; i < rows; i++) { + dst_type value = static_cast<dst_type>(src_data[i]); + data[_convert_params->start_idx + i] = value; + } + + return Status::OK(); +} +template <typename src_type, bool is_nullable> +struct NumberColumnToStringConvert : public ColumnConvert { + Status convert(const IColumn* src_col, IColumn* dst_col) override; +}; + +template <typename src_type, bool is_nullable> +Status NumberColumnToStringConvert<src_type, is_nullable>::convert(const IColumn* src_col, + IColumn* dst_col) { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + auto& src_data = static_cast<const ColumnVector<src_type>*>(src_col)->get_data(); + auto str_col = static_cast<ColumnString*>(dst_col); + for (int i = 0; i < rows; i++) { + std::string value = std::to_string(src_data[i]); + str_col->insert_data(value.data(), value.size()); + } + return Status::OK(); +} + +template <bool is_nullable> +struct int128totimestamp : public ColumnConvert { +public: + [[nodiscard]] static uint64_t to_timestamp_micros(uint32_t hi, uint64_t lo) { + return (hi - ParquetInt96::JULIAN_EPOCH_OFFSET_DAYS) * ParquetInt96::MICROS_IN_DAY + + lo / ParquetInt96::NANOS_PER_MICROSECOND; + } + Status convert(const IColumn* src_col, IColumn* dst_col) override { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + auto& src_data = static_cast<const ColumnVector<Int128>*>(src_col)->get_data(); + dst_col->resize(_convert_params->start_idx + rows); + auto& data = static_cast<ColumnVector<UInt64>*>(dst_col)->get_data(); + + for (int i = 0; i < rows; i++) { + __int128 x = src_data[i]; + uint32_t hi = x >> 64; + uint64_t lo = (x << 64) >> 64; + auto& num = data[_convert_params->start_idx + i]; + auto& value = reinterpret_cast<DateV2Value<DateTimeV2ValueType>&>(num); + int64_t micros = to_timestamp_micros(hi, lo); + value.from_unixtime(micros / 1000000, *_convert_params->ctz); + value.set_microsecond(micros % 1000000); + } + return Status::OK(); + } +}; + +template <bool is_nullable> +struct int64totimestamp : public ColumnConvert { +public: + Status convert(const IColumn* src_col, IColumn* dst_col) override { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + dst_col->resize(_convert_params->start_idx + rows); + + auto& src_data = static_cast<const ColumnVector<Int64>*>(src_col)->get_data(); + auto& data = static_cast<ColumnVector<UInt64>*>(dst_col)->get_data(); + for (int i = 0; i < rows; i++) { + int64 x = src_data[i]; + dst_col = static_cast<ColumnVector<UInt64>*>(dst_col); + auto& num = data[_convert_params->start_idx + i]; + auto& value = reinterpret_cast<DateV2Value<DateTimeV2ValueType>&>(num); + value.from_unixtime(x / _convert_params->second_mask, *_convert_params->ctz); + value.set_microsecond((x % _convert_params->second_mask) * + _convert_params->scale_to_nano_factor / 1000); + } + return Status::OK(); + } +}; + +template <bool is_nullable> +class int32todate : public ColumnConvert { +public: + Status convert(const IColumn* src_col, IColumn* dst_col) override { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + dst_col->resize(_convert_params->start_idx + rows); + + auto& src_data = static_cast<const ColumnVector<int32>*>(src_col)->get_data(); + auto& data = static_cast<ColumnDateV2*>(dst_col)->get_data(); + date_day_offset_dict& date_dict = date_day_offset_dict::get(); + + for (int i = 0; i < rows; i++) { + auto& value = reinterpret_cast<DateV2Value<DateV2ValueType>&>( + data[_convert_params->start_idx + i]); + int64_t date_value = (int64_t)src_data[i] + _convert_params->offset_days; + value = date_dict[date_value]; + } + + return Status::OK(); + } +}; + +template <typename DecimalType, bool is_nullable, DecimalScaleParams::ScaleType ScaleType> +class stringtodecimal : public ColumnConvert { +public: + Status convert(const IColumn* src_col, IColumn* dst_col) override { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + DecimalScaleParams& scale_params = _convert_params->decimal_scale; + auto buf = static_cast<const ColumnString*>(src_col)->get_chars().data(); + auto& offset = static_cast<const ColumnString*>(src_col)->get_offsets(); + dst_col->resize(_convert_params->start_idx + rows); + + auto& data = static_cast<ColumnDecimal<DecimalType>*>(dst_col)->get_data(); + for (int i = 0; i < rows; i++) { + int len = offset[i] - offset[i - 1]; + // When Decimal in parquet is stored in byte arrays, binary and fixed, + // the unscaled number must be encoded as two's complement using big-endian byte order. + Int128 value = 0; + memcpy(reinterpret_cast<char*>(&value), buf + offset[i - 1], len); + value = BitUtil::big_endian_to_host(value); + value = value >> ((sizeof(value) - len) * 8); + if constexpr (ScaleType == DecimalScaleParams::SCALE_UP) { + value *= scale_params.scale_factor; + } else if constexpr (ScaleType == DecimalScaleParams::SCALE_DOWN) { + value /= scale_params.scale_factor; + } else if constexpr (ScaleType == DecimalScaleParams::NO_SCALE) { + // do nothing + } else { + LOG(FATAL) << "__builtin_unreachable"; + __builtin_unreachable(); + } + auto& v = reinterpret_cast<DecimalType&>(data[_convert_params->start_idx + i]); + v = (DecimalType)value; + } + + return Status::OK(); + } +}; +template <typename NumberType, typename DecimalPhysicalType, bool is_nullable, + DecimalScaleParams::ScaleType ScaleType> +class numbertodecimal : public ColumnConvert { +public: + Status convert(const IColumn* src_col, IColumn* dst_col) override { + size_t rows = src_col->size(); + if constexpr (is_nullable) { + convert_null(&src_col, &dst_col); + } + auto* src_data = static_cast<const ColumnVector<NumberType>*>(src_col)->get_data().data(); + dst_col->resize(_convert_params->start_idx + rows); + + DecimalScaleParams& scale_params = _convert_params->decimal_scale; + auto* data = static_cast<ColumnDecimal<Decimal<DecimalPhysicalType>>*>(dst_col) + ->get_data() + .data(); + + for (int i = 0; i < rows; i++) { + Int128 value = src_data[i]; Review Comment: PR https://github.com/apache/doris/pull/25012 has optimized the performance of reading decimal, why still use int128 here? -- This is an automated message from the Apache Git Service. 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