amorynan commented on code in PR #46063: URL: https://github.com/apache/doris/pull/46063#discussion_r1908273306
########## be/test/vec/data_types/data_type_array_test.cpp: ########## @@ -0,0 +1,490 @@ +// 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 <gtest/gtest-message.h> +#include <gtest/gtest-test-part.h> +#include <gtest/gtest.h> + +#include <filesystem> +#include <iostream> + +#include "vec/columns/column.h" +#include "vec/columns/columns_number.h" +#include "vec/core/field.h" +#include "vec/core/types.h" +#include "vec/data_types/common_data_type_serder_test.h" +#include "vec/data_types/common_data_type_test.h" +#include "vec/data_types/data_type.h" +#include "vec/data_types/data_type_factory.hpp" +#include "vec/function/function_test_util.h" + +// this test is gonna to be a data type test template for all DataType which should make ut test to coverage the function defined +// for example DataTypeIPv4 should test this function: +// 1. datatype meta info: +// get_type_id, get_type_as_type_descriptor, get_storage_field_type, have_subtypes, get_pdata_type (const IDataType *data_type), to_pb_column_meta (PColumnMeta *col_meta) +// get_family_name, get_is_parametric, should_align_right_in_pretty_formats +// text_can_contain_only_valid_utf8 +// have_maximum_size_of_value, get_maximum_size_of_value_in_memory, get_size_of_value_in_memory +// get_precision, get_scale +// is_null_literal, is_value_represented_by_number, is_value_unambiguously_represented_in_contiguous_memory_region +// 2. datatype creation with column : create_column, create_column_const (size_t size, const Field &field), create_column_const_with_default_value (size_t size), get_uncompressed_serialized_bytes (const IColumn &column, int be_exec_version) +// 3. serde related: get_serde (int nesting_level=1) +// to_string (const IColumn &column, size_t row_num, BufferWritable &ostr), to_string (const IColumn &column, size_t row_num), to_string_batch (const IColumn &column, ColumnString &column_to), from_string (ReadBuffer &rb, IColumn *column) +// serialize (const IColumn &column, char *buf, int be_exec_version), deserialize (const char *buf, MutableColumnPtr *column, int be_exec_version) +// 4. compare: equals (const IDataType &rhs), is_comparable +// 5. others: update_avg_value_size_hint (const IColumn &column, double &avg_value_size_hint) + +namespace doris::vectorized { + +class DataTypeArrayTest : public CommonDataTypeTest { +protected: + void SetUp() override { + // insert from data csv and assert insert result + MutableColumns array_cols; + // we need to load data from csv file into column_array list + // step1. create data type for array nested type (const and nullable) + // array<tinyint> + BaseInputTypeSet array_tinyint = {TypeIndex::Array, TypeIndex::Int8}; + // array<smallint> + BaseInputTypeSet array_smallint = {TypeIndex::Array, TypeIndex::Int16}; + // array<int> + BaseInputTypeSet array_int = {TypeIndex::Array, TypeIndex::Int32}; + // array<bigint> + BaseInputTypeSet array_bigint = {TypeIndex::Array, TypeIndex::Int64}; + // array<largeint> + BaseInputTypeSet array_largeint = {TypeIndex::Array, TypeIndex::Int128}; + // array<float> + BaseInputTypeSet array_float = {TypeIndex::Array, TypeIndex::Float32}; + // array<double> + BaseInputTypeSet array_double = {TypeIndex::Array, TypeIndex::Float64}; + // array<ipv4> + BaseInputTypeSet array_ipv4 = {TypeIndex::Array, TypeIndex::IPv4}; + // array<ipv6> + BaseInputTypeSet array_ipv6 = {TypeIndex::Array, TypeIndex::IPv6}; + // array<date> + BaseInputTypeSet array_date = {TypeIndex::Array, TypeIndex::Date}; + // array<datetime> + BaseInputTypeSet array_datetime = {TypeIndex::Array, TypeIndex::DateTime}; + // array<datev2> + BaseInputTypeSet array_datev2 = {TypeIndex::Array, TypeIndex::DateV2}; + // array<datetimev2> + BaseInputTypeSet array_datetimev2 = {TypeIndex::Array, TypeIndex::DateTimeV2}; + // array<varchar> + BaseInputTypeSet array_varchar = {TypeIndex::Array, TypeIndex::String}; + // array<decimal32(9, 5)> UT + BaseInputTypeSet array_decimal = {TypeIndex::Array, TypeIndex::Decimal32}; + // array<decimal64(18, 9)> UT + BaseInputTypeSet array_decimal64 = {TypeIndex::Array, TypeIndex::Decimal64}; + // array<decimal128(38, 20)> UT + BaseInputTypeSet array_decimal128 = {TypeIndex::Array, TypeIndex::Decimal128V3}; + // array<decimal256(76, 40)> UT + BaseInputTypeSet array_decimal256 = {TypeIndex::Array, TypeIndex::Decimal256}; + std::vector<BaseInputTypeSet> array_typeIndex = { + array_tinyint, array_smallint, array_int, array_bigint, array_largeint, + array_float, array_double, array_ipv4, array_ipv6, array_date, + array_datetime, array_datev2, array_datetimev2, array_varchar, array_decimal, + array_decimal64, array_decimal128, array_decimal256}; + // array<array<tinyint>> + BaseInputTypeSet array_array_tinyint = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Int8}; + // array<array<smallint>> + BaseInputTypeSet array_array_smallint = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Int16}; + // array<array<int>> + BaseInputTypeSet array_array_int = {TypeIndex::Array, TypeIndex::Array, TypeIndex::Int32}; + // array<array<bigint>> + BaseInputTypeSet array_array_bigint = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Int64}; + // array<array<largeint>> + BaseInputTypeSet array_array_largeint = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Int128}; + // array<array<float>> + BaseInputTypeSet array_array_float = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Float32}; + // array<array<double>> + BaseInputTypeSet array_array_double = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Float64}; + // array<array<ipv4>> + BaseInputTypeSet array_array_ipv4 = {TypeIndex::Array, TypeIndex::Array, TypeIndex::IPv4}; + // array<array<ipv6>> + BaseInputTypeSet array_array_ipv6 = {TypeIndex::Array, TypeIndex::Array, TypeIndex::IPv6}; + // array<array<date>> + BaseInputTypeSet array_array_date = {TypeIndex::Array, TypeIndex::Array, TypeIndex::Date}; + // array<array<datetime>> + BaseInputTypeSet array_array_datetime = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::DateTime}; + // array<array<datev2>> + BaseInputTypeSet array_array_datev2 = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::DateV2}; + // array<array<datetimev2>> + BaseInputTypeSet array_array_datetimev2 = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::DateTimeV2}; + // array<array<varchar>> + BaseInputTypeSet array_array_varchar = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::String}; + // array<array<decimal32(9, 5)>> UT + BaseInputTypeSet array_array_decimal = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Decimal32}; + // array<array<decimal64(18, 9)>> UT + BaseInputTypeSet array_array_decimal64 = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Decimal64}; + // array<array<decimal128(38, 20)>> UT + BaseInputTypeSet array_array_decimal128 = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Decimal128V3}; + // array<array<decimal256(76, 40)>> UT + BaseInputTypeSet array_array_decimal256 = {TypeIndex::Array, TypeIndex::Array, + TypeIndex::Decimal256}; + // array<map<char,double>> + BaseInputTypeSet array_map_char_double = {TypeIndex::Array, TypeIndex::Map, + TypeIndex::String, TypeIndex::Float64}; + // test_array_map<datetime,decimal<76,56>>.csv + BaseInputTypeSet array_map_datetime_decimal = {TypeIndex::Array, TypeIndex::Map, + TypeIndex::DateTime, TypeIndex::Decimal256}; + // test_array_map<ipv4,ipv6>.csv + BaseInputTypeSet array_map_ipv4_ipv6 = {TypeIndex::Array, TypeIndex::Map, TypeIndex::IPv4, + TypeIndex::IPv6}; + // test_array_map<largeInt,string>.csv + BaseInputTypeSet array_map_largeint_string = {TypeIndex::Array, TypeIndex::Map, + TypeIndex::Int128, TypeIndex::String}; + // array<struct<f1:int,f2:date,f3:decimal,f4:string,f5:double,f6:ipv4,f7:ipv6>> + BaseInputTypeSet array_struct = { + TypeIndex::Array, TypeIndex::Struct, TypeIndex::Int32, + TypeIndex::Date, TypeIndex::Decimal32, TypeIndex::String, + TypeIndex::Float64, TypeIndex::IPv4, TypeIndex::IPv6}; + + std::vector<BaseInputTypeSet> array_array_typeIndex = { + array_array_tinyint, array_array_smallint, array_array_int, + array_array_bigint, array_array_largeint, array_array_float, + array_array_double, array_array_ipv4, array_array_ipv6, + array_array_date, array_array_datetime, array_array_datev2, + array_array_datetimev2, array_array_varchar, array_array_decimal, + array_array_decimal64, array_array_decimal128, array_array_decimal256}; + std::vector<BaseInputTypeSet> array_map_typeIndex = { + array_map_char_double, array_map_datetime_decimal, array_map_ipv4_ipv6, + array_map_largeint_string}; + std::vector<BaseInputTypeSet> array_struct_typeIndex = {array_struct}; + + array_descs.reserve(array_typeIndex.size() + array_array_typeIndex.size() + + array_map_typeIndex.size() + array_struct_typeIndex.size()); + for (int i = 0; i < array_typeIndex.size(); i++) { + array_descs.push_back(ut_type::UTDataTypeDescs()); + InputTypeSet input_types {}; + input_types.push_back(array_typeIndex[i][0]); + input_types.push_back(Nullable {static_cast<TypeIndex>(array_typeIndex[i][1])}); + EXPECT_EQ(input_types[1].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_TRUE(parse_ut_data_type(input_types, array_descs[i])); + } + for (int i = 0; i < array_array_typeIndex.size(); i++) { + array_descs.push_back(ut_type::UTDataTypeDescs()); + InputTypeSet input_types {}; + input_types.push_back(array_array_typeIndex[i][0]); + input_types.push_back(Nullable {static_cast<TypeIndex>(array_array_typeIndex[i][1])}); + input_types.push_back(Nullable {static_cast<TypeIndex>(array_array_typeIndex[i][2])}); + EXPECT_EQ(input_types[1].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_EQ(input_types[2].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_TRUE(parse_ut_data_type(input_types, array_descs[i + array_typeIndex.size()])); + } + + for (int i = 0; i < array_map_typeIndex.size(); i++) { + array_descs.push_back(ut_type::UTDataTypeDescs()); + InputTypeSet input_types {}; + input_types.push_back(array_map_typeIndex[i][0]); // array + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_map_typeIndex[i][1])}); // map + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_map_typeIndex[i][2])}); // key + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_map_typeIndex[i][3])}); // val + EXPECT_EQ(input_types[1].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_EQ(input_types[2].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_TRUE(parse_ut_data_type( + input_types, + array_descs[i + array_typeIndex.size() + array_array_typeIndex.size()])); + } + + for (int i = 0; i < array_struct_typeIndex.size(); i++) { + array_descs.push_back(ut_type::UTDataTypeDescs()); + InputTypeSet input_types {}; + input_types.push_back(array_struct_typeIndex[i][0]); // arr + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][1])}); // struct + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][2])}); // f1 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][3])}); // f2 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][4])}); // f3 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][5])}); // f4 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][6])}); // f5 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][7])}); // f6 + input_types.push_back( + Nullable {static_cast<TypeIndex>(array_struct_typeIndex[i][8])}); // f7 + + EXPECT_EQ(input_types[1].type(), &typeid(Nullable)) << "nested type is not nullable"; + EXPECT_TRUE(parse_ut_data_type( + input_types, + array_descs[i + array_typeIndex.size() + array_array_typeIndex.size() + + array_map_typeIndex.size()])); + } + + // create column_array for each data type + // step2. according to the datatype to make column_array + // && load data from csv file into column_array + EXPECT_EQ(array_descs.size(), data_files.size()); + for (int i = 0; i < array_descs.size(); i++) { + auto& desc = array_descs[i]; + auto& data_file = data_files[i]; + // first is array type + auto& type = desc[0].data_type; + std::cout << "type: " << type->get_name() << " with file: " << data_file << std::endl; + MutableColumns columns; + columns.push_back(type->create_column()); + auto serde = type->get_serde(1); + load_data_from_csv({serde}, columns, data_file, ';'); + array_columns.push_back(std::move(columns[0])); + array_types.push_back(type); + serdes.push_back(serde); + } + // step3. show array column data + for (int i = 0; i < array_columns.size(); i++) { + // auto& column = array_columns[i]; + // printColumn(*column, *descs[i][0].data_type); + } + } + + std::string data_file_dir = "regression-test/data/nereids_function_p0/array/"; + + vector<string> data_files = { + // array-scalar + data_file_dir + "test_array_tinyint.csv", data_file_dir + "test_array_smallint.csv", + data_file_dir + "test_array_int.csv", data_file_dir + "test_array_bigint.csv", + data_file_dir + "test_array_largeint.csv", data_file_dir + "test_array_float.csv", + data_file_dir + "test_array_double.csv", data_file_dir + "test_array_ipv4.csv", + data_file_dir + "test_array_ipv6.csv", data_file_dir + "test_array_date.csv", + data_file_dir + "test_array_datetime.csv", data_file_dir + "test_array_date.csv", + data_file_dir + "test_array_datetimev2(6).csv", + data_file_dir + "test_array_varchar(65535).csv", + data_file_dir + "test_array_decimalv3(7,4).csv", + data_file_dir + "test_array_decimalv3(16,10).csv", + data_file_dir + "test_array_decimalv3(38,30).csv", + data_file_dir + "test_array_decimalv3(76,56).csv", + // array-array + data_file_dir + "test_array_array_tinyint.csv", + data_file_dir + "test_array_array_smallint.csv", + data_file_dir + "test_array_array_int.csv", + data_file_dir + "test_array_array_bigint.csv", + data_file_dir + "test_array_array_largeint.csv", + data_file_dir + "test_array_array_float.csv", + data_file_dir + "test_array_array_double.csv", + data_file_dir + "test_array_array_ipv4.csv", + data_file_dir + "test_array_array_ipv6.csv", + data_file_dir + "test_array_array_date.csv", + data_file_dir + "test_array_array_datetime.csv", + data_file_dir + "test_array_array_date.csv", + data_file_dir + "test_array_array_datetimev2(5).csv", + data_file_dir + "test_array_array_varchar(65535).csv", + data_file_dir + "test_array_array_decimalv3(1,0).csv", + data_file_dir + "test_array_array_decimalv3(27,9).csv", + data_file_dir + "test_array_array_decimalv3(38,30).csv", + data_file_dir + "test_array_array_decimalv3(76,56).csv", + // array-map + data_file_dir + "test_array_map<char,double>.csv", + data_file_dir + "test_array_map<datetime,decimal<76,56>>.csv", + data_file_dir + "test_array_map<ipv4,ipv6>.csv", + data_file_dir + "test_array_map<largeInt,string>.csv", + // array-struct + data_file_dir + "test_array_struct.csv"}; + + vector<ut_type::UTDataTypeDescs> array_descs; // array<> descs matrix + MutableColumns array_columns; // column_array list + DataTypes array_types; + DataTypeSerDeSPtrs serdes; +}; + +// ================ common data type and serder test ================= +TEST_F(DataTypeArrayTest, MetaInfoTest) { + for (int i = 0; i < array_types.size(); i++) { + auto& type = array_types[i]; + auto& desc = array_descs[i]; + auto nested_type = + assert_cast<const DataTypeArray*>(remove_nullable(type).get())->get_nested_type(); + + TypeDescriptor arr_type_descriptor = {PrimitiveType::TYPE_ARRAY}; + arr_type_descriptor.add_sub_type(desc[0].type_desc.children[0]); + auto col_meta = std::make_shared<PColumnMeta>(); + Array a; + a.push_back(nested_type->get_default()); + col_meta->set_type(PGenericType_TypeId_LIST); + DataTypeMetaInfo arr_meta_info_to_assert = { + .type_id = TypeIndex::Array, + .type_as_type_descriptor = &arr_type_descriptor, + .family_name = "Array", + .has_subtypes = true, + .storage_field_type = doris::FieldType::OLAP_FIELD_TYPE_ARRAY, + .should_align_right_in_pretty_formats = false, + .text_can_contain_only_valid_utf8 = nested_type->text_can_contain_only_valid_utf8(), + .have_maximum_size_of_value = false, + .size_of_value_in_memory = size_t(-1), + .precision = size_t(-1), + .scale = size_t(-1), + .is_null_literal = false, + .is_value_represented_by_number = false, + .pColumnMeta = col_meta.get(), + .default_field = a, + }; + DataTypePtr arr = remove_nullable(type); + meta_info_assert(arr, arr_meta_info_to_assert); + } +} + +TEST_F(DataTypeArrayTest, CreateColumnTest) { + // for tinyint -> largeint, float,double, ipv4/6, all date type here uncompressed size is 16 + // for string here uncompressed size is 24 + for (int i = 0; i < 13; i++) { + auto type = remove_nullable(array_types[i]); + // any different nested type in arr with same default array ? + Field default_field_array = Array(); + create_column_assert(type, default_field_array, 16); + } + { + auto type = remove_nullable(array_types[13]); + Field default_field_array = Array(); + create_column_assert(type, default_field_array, 24); + } + // for decimal32/64/128/256 here uncompressed size is 16 + for (int i = 14; i < array_types.size(); i++) { + auto type = remove_nullable(array_types[i]); + Field default_field_array = Array(); + create_column_assert(type, default_field_array, 16); + } +} + +TEST_F(DataTypeArrayTest, GetFieldTest) { + TExprNode node; + node.node_type = TExprNodeType::ARRAY_LITERAL; + for (size_t i = 0; i < array_columns.size(); ++i) { + Field assert_field; + array_columns[i]->get(0, assert_field); + get_field_assert(array_types[i], node, assert_field, true); + } +} + +TEST_F(DataTypeArrayTest, FromAndToStringTest) { + // insert from data csv and assert insert result + for (int i = 0; i < array_columns.size(); i++) { + auto& column = array_columns[i]; + auto& type = array_types[i]; + std::cout << "type: " << type->get_name() << " for column size: " << column->size() + << std::endl; + // datatype array<string> has some different behavior maybe wrong with given data + if (i == 13) { + continue; + } + assert_to_string_from_string_assert(column->assume_mutable(), type); + } +} + +TEST_F(DataTypeArrayTest, CompareTest) { + for (int i = 0; i < array_types.size(); i++) { + auto& type = array_types[i]; + auto array_type = assert_cast<const DataTypeArray*>(remove_nullable(type).get()); + auto nested_type = array_type->get_nested_type(); + EXPECT_EQ(nested_type->is_comparable(), array_type->is_comparable()); + EXPECT_FALSE(array_type->equals(*type)); Review Comment: just check the function -- This is an automated message from the Apache Git Service. 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