amorynan commented on code in PR #42269: URL: https://github.com/apache/doris/pull/42269#discussion_r1870955132
########## be/test/vec/columns/common_column_test.h: ########## @@ -0,0 +1,766 @@ +// 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 "olap/schema.h" +#include "vec/columns/column.h" +#include "vec/columns/column_array.h" +#include "vec/columns/column_map.h" +#include "vec/columns/columns_number.h" +#include "vec/core/field.h" +#include "vec/core/sort_block.h" +#include "vec/core/sort_description.h" +#include "vec/core/types.h" +#include "vec/data_types/data_type.h" +#include "vec/data_types/data_type_array.h" +#include "vec/data_types/data_type_map.h" + +// this test is gonna to be a column test template for all column which should make ut test to coverage the function defined in column +// for example column_array should test this function: +// size, reserve, resize, empty, byte_size, allocated_bytes, clone_resized, +// get_shrinked_column, filter, filter_by_selector, serialize_vec, deserialize_vec, get_max_row_byte_size +// +namespace doris::vectorized { + +class CommonColumnTest : public ::testing::Test { +public: + void SetUp() override { + col_str = ColumnString::create(); + col_str->insert_data("aaa", 3); + col_str->insert_data("bb", 2); + col_str->insert_data("cccc", 4); + + col_int = ColumnInt64::create(); + col_int->insert_value(1); + col_int->insert_value(2); + col_int->insert_value(3); + + col_dcm = ColumnDecimal64::create(0, 3); + col_dcm->insert_value(1.23); + col_dcm->insert_value(4.56); + col_dcm->insert_value(7.89); + + col_arr = ColumnArray::create(ColumnInt64::create(), ColumnArray::ColumnOffsets::create()); + Array array1 = {1, 2, 3}; + Array array2 = {4}; + col_arr->insert(array1); + col_arr->insert(Array()); + col_arr->insert(array2); + + col_map = ColumnMap::create(ColumnString::create(), ColumnInt64::create(), + ColumnArray::ColumnOffsets::create()); + Array k1 = {"a", "b", "c"}; + Array v1 = {1, 2, 3}; + Array k2 = {"d"}; + Array v2 = {4}; + Array a = Array(); + Map map1, map2, map3; + map1.push_back(k1); + map1.push_back(v1); + col_map->insert(map1); + map3.push_back(a); + map3.push_back(a); + col_map->insert(map3); + map2.push_back(k2); + map2.push_back(v2); + col_map->insert(map2); + } + + ColumnString::MutablePtr col_str; + ColumnInt64::MutablePtr col_int; + ColumnDecimal64::MutablePtr col_dcm; + ColumnArray::MutablePtr col_arr; + ColumnMap::MutablePtr col_map; + + void checkColumn(const IColumn& col1, const IColumn& col2, const IDataType& dataType, + size_t column_size) { + if (WhichDataType(dataType).is_map()) { + auto map1 = check_and_get_column<ColumnMap>(col1); + auto map2 = check_and_get_column<ColumnMap>(col2); + const DataTypeMap& rhs_map = static_cast<const DataTypeMap&>(dataType); + checkColumn(map1->get_keys(), map2->get_keys(), *rhs_map.get_key_type(), + map1->get_keys().size()); + checkColumn(map2->get_values(), map2->get_values(), *rhs_map.get_value_type(), + map1->get_values().size()); + } else { + if (WhichDataType(dataType).is_int8()) { + auto c1 = check_and_get_column<ColumnInt8>(col1); + auto c2 = check_and_get_column<ColumnInt8>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_int16()) { + auto c1 = check_and_get_column<ColumnInt16>(col1); + auto c2 = check_and_get_column<ColumnInt16>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_int32()) { + auto c1 = check_and_get_column<ColumnInt32>(col1); + auto c2 = check_and_get_column<ColumnInt32>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_int64()) { + auto c1 = check_and_get_column<ColumnInt64>(col1); + auto c2 = check_and_get_column<ColumnInt64>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_int128()) { + auto c1 = check_and_get_column<ColumnInt128>(col1); + auto c2 = check_and_get_column<ColumnInt128>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_float32()) { + auto c1 = check_and_get_column<ColumnFloat32>(col1); + auto c2 = check_and_get_column<ColumnFloat32>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_float64()) { + auto c1 = check_and_get_column<ColumnFloat64>(col1); + auto c2 = check_and_get_column<ColumnFloat64>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_uint8()) { + auto c1 = check_and_get_column<ColumnUInt8>(col1); + auto c2 = check_and_get_column<ColumnUInt8>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_uint16()) { + auto c1 = check_and_get_column<ColumnUInt16>(col1); + auto c2 = check_and_get_column<ColumnUInt16>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_uint32()) { + auto c1 = check_and_get_column<ColumnUInt32>(col1); + auto c2 = check_and_get_column<ColumnUInt32>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_uint64()) { + auto c1 = check_and_get_column<ColumnUInt64>(col1); + auto c2 = check_and_get_column<ColumnUInt64>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal()) { + auto c1 = check_and_get_column<ColumnDecimal64>(col1); + auto c2 = check_and_get_column<ColumnDecimal64>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal32()) { + auto c1 = check_and_get_column<ColumnDecimal32>(col1); + auto c2 = check_and_get_column<ColumnDecimal32>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal64()) { + auto c1 = check_and_get_column<ColumnDecimal64>(col1); + auto c2 = check_and_get_column<ColumnDecimal64>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal128v2()) { + auto c1 = check_and_get_column<ColumnDecimal128V2>(col1); + auto c2 = check_and_get_column<ColumnDecimal128V2>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal128v3()) { + auto c1 = check_and_get_column<ColumnDecimal128V3>(col1); + auto c2 = check_and_get_column<ColumnDecimal128V3>(col2); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else if (WhichDataType(dataType).is_decimal256()) { + auto c1 = check_and_get_column<ColumnDecimal<Decimal256>>(col1); + auto c2 = check_and_get_column<ColumnDecimal<Decimal256>>(col1); + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(c1->get_element(i), c2->get_element(i)); + } + } else { + for (size_t i = 0; i < column_size; ++i) { + EXPECT_EQ(col1.get_data_at(i), col2.get_data_at(i)); + } + } + } + } + + void printColumn(const IColumn& column, const IDataType& dataType) { + std::cout << "column total size: " << column.size() << std::endl; + if (WhichDataType(dataType).is_map()) { + auto map = check_and_get_column<ColumnMap>(column); + std::cout << "map {keys, values}" << std::endl; + const DataTypeMap& rhs_map = static_cast<const DataTypeMap&>(dataType); + printColumn(map->get_keys(), *rhs_map.get_key_type()); + printColumn(map->get_values(), *rhs_map.get_value_type()); + } else if (WhichDataType(dataType).is_array()) { + auto array = check_and_get_column<ColumnArray>(column); + std::cout << "array: " << std::endl; + const auto& rhs_array = static_cast<const DataTypeArray&>(dataType); + printColumn(array->get_data(), *rhs_array.get_nested_type()); + } else { + size_t column_size = column.size(); + std::cout << column.get_name() << ": " << std::endl; + if (WhichDataType(dataType).is_int8()) { + auto col = check_and_get_column<ColumnInt8>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_int16()) { + auto col = check_and_get_column<ColumnInt16>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_int32()) { + auto col = check_and_get_column<ColumnInt32>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_int64()) { + auto col = check_and_get_column<ColumnInt64>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_int128()) { + auto col = check_and_get_column<ColumnInt128>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_float32()) { + auto col = check_and_get_column<ColumnFloat32>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_float64()) { + auto col = check_and_get_column<ColumnFloat64>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_uint8()) { + auto col = check_and_get_column<ColumnUInt8>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_uint16()) { + auto col = check_and_get_column<ColumnUInt16>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_uint32()) { + auto col = check_and_get_column<ColumnUInt32>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_uint64()) { + auto col = check_and_get_column<ColumnUInt64>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_uint128()) { + auto col = check_and_get_column<ColumnUInt128>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_data_at(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal()) { + auto col = check_and_get_column<ColumnDecimal64>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal32()) { + auto col = check_and_get_column<ColumnDecimal32>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal64()) { + auto col = check_and_get_column<ColumnDecimal64>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal128v2()) { + auto col = check_and_get_column<ColumnDecimal128V2>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal128v3()) { + auto col = check_and_get_column<ColumnDecimal128V3>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_decimal256()) { + auto col = check_and_get_column<ColumnDecimal<Decimal256>>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_element(i) << " "; + } + } else if (WhichDataType(dataType).is_date()) { + auto col = check_and_get_column<ColumnDate>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_data_at(i) << " "; + } + } else if (WhichDataType(dataType).is_date_time()) { + auto col = check_and_get_column<ColumnDateTime>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_data_at(i) << " "; + } + } else if (WhichDataType(dataType).is_date_v2()) { + auto col = check_and_get_column<ColumnDateV2>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_data_at(i) << " "; + } + } else if (WhichDataType(dataType).is_date_time_v2()) { + auto col = check_and_get_column<ColumnDateTimeV2>(column); + for (size_t i = 0; i < column_size; ++i) { + std::cout << col->get_data_at(i) << " "; + } + } else { + std::cout << "data type: " << dataType.get_name() << std::endl; + std::cout << "column type: " << column.get_name() << std::endl; + for (size_t i = 0; i < column_size; ++i) { + std::cout << column.get_data_at(i).to_string() << " "; + } + } + std::cout << std::endl; + } + } + // column size changed calculation: + // size, reserve, resize, empty, byte_size, allocated_bytes, clone_resized, get_shrinked_column + // cut(LIMIT operation), shrink + void sizeAssert(MutableColumnPtr col, size_t expect_size) { + EXPECT_EQ(col->size(), expect_size); + } + + // empty just use size() == 0 to impl as default behavior + void emptyAssert(MutableColumnPtr col) { EXPECT_EQ(col->size(), 0); } + + // reserve, resize, byte_size, allocated_bytes, clone_resized, get_shrinked_column + void reserveAssert(MutableColumnPtr col, size_t expect_size) { + col->reserve(expect_size); + EXPECT_EQ(col->allocated_bytes(), expect_size); + } + + // cut(LIMIT operation) will cut the column with the given from and to, and return the new column + // notice return column is clone from origin column + void cutAssert(MutableColumnPtr col, size_t from, size_t to, size_t expect_size) { + auto ori = col->size(); + auto ptr = col->cut(from, to); + EXPECT_EQ(ptr->size(), expect_size); + EXPECT_EQ(col->size(), ori); + } + + // shrink is cut/append the column with the given size, which called from Block::set_num_rows + // and some Operator may call this set_num_rows to make rows satisfied, like limit operation + // but different from cut behavior which + // return column is mutate from origin column + void shrinkAssert(MutableColumnPtr col, size_t shrink_size) { + auto ptr = col->shrink(shrink_size); + EXPECT_EQ(ptr->size(), shrink_size); + EXPECT_EQ(col->size(), shrink_size); + } + + // resize has fixed-column implementation and variable-column implementation + // like string column, the resize will resize the offsets column but not the data column (because it doesn't matter the size of data column, all operation for string column is based on the offsets column) + // like vector column, the resize will resize the data column + // like array column, the resize will resize the offsets column and the data column (which in creator we have check staff for the size of data column is the same as the size of offsets column) + void resizeAssert(MutableColumnPtr col, size_t expect_size) { + col->resize(expect_size); + EXPECT_EQ(col->size(), expect_size); + } + + // replicate is clone with new column from the origin column, always from ColumnConst to expand the column + void replicateAssert(MutableColumnPtr col, IColumn::Offsets& offsets) { + auto new_col = col->replicate(offsets); + EXPECT_EQ(new_col->size(), offsets.back()); + } + + // byte size is just appriximate size of the column + // as fixed column type, like column_vector, the byte size is sizeof(columnType) * size() + // as variable column type, like column_string, the byte size is sum of chars size() and offsets size * sizeof(offsetType) + void byteSizeAssert(MutableColumnPtr col, size_t expect_size) { + EXPECT_EQ(col->byte_size(), expect_size); + } + + // allocated bytes is the real size of the column + void allocatedBytesAssert(MutableColumnPtr col, size_t expect_size) { + EXPECT_EQ(col->allocated_bytes(), expect_size); + } + + // clone_resized will clone the column and cut/append to the new column with the size of the original column + void cloneResizedAssert(MutableColumnPtr col, size_t expect_size) { + auto new_col = col->clone_resized(expect_size); + EXPECT_EQ(new_col->size(), expect_size); + } + + // get_shrinked_column should only happened in char-type column or nested char-type column + // just shrink the end zeros for char-type column which happened in segmentIterator + // eg. column_desc: char(6), insert into char(3), the char(3) will padding the 3 zeros at the end for writing to disk. + // but we select should just print the char(3) without the padding zeros + // limit and topN operation will trigger this function call + void getShrinkedColumnAssert(MutableColumnPtr col, size_t spcific_size_defined) { + EXPECT_TRUE(col->could_shrinked_column()); + auto new_col = col->get_shrinked_column(); + for (size_t i = 0; i < new_col->size(); i++) { + EXPECT_EQ(col->get_data_at(i).size, spcific_size_defined); + } + } + + //serialize and deserialize which usually used in AGG function: + // serialize_value_into_arena, deserialize_and_insert_from_arena (called by AggregateFunctionDistinctMultipleGenericData, group_array_intersect, nested-types serder like: DataTypeArraySerDe::write_one_cell_to_jsonb) + void ser_deserialize_with_arena_impl(MutableColumns& columns, const DataTypes& data_types) { + /// check serialization is reversible. + Arena arena; + MutableColumns argument_columns(data_types.size()); + const char* pos = nullptr; + StringRef key(pos, 0); + { + // serialize + for (size_t r = 0; r < columns[0]->size(); ++r) { + for (size_t i = 0; i < columns.size(); ++i) { + auto cur_ref = columns[i]->serialize_value_into_arena(r, arena, pos); + key.data = cur_ref.data - key.size; + key.size += cur_ref.size; + printColumn(*columns[i], *data_types[i]); + } + } + } + + { + // deserialize + for (size_t i = 0; i < data_types.size(); ++i) { + argument_columns[i] = data_types[i]->create_column(); + } + const char* begin = key.data; + for (size_t r = 0; r < columns[0]->size(); ++r) { + for (size_t i = 0; i < argument_columns.size(); ++i) { + begin = argument_columns[i]->deserialize_and_insert_from_arena(begin); + printColumn(*argument_columns[i], *data_types[i]); + } + } + // for (size_t i = 0; i < argument_columns.size(); ++i) { + // auto& column = argument_columns[i]; + // begin = column->deserialize_and_insert_from_arena(begin); + // printColumn(*column, *data_types[i]); + // } + } + { + // check column data equal + for (size_t i = 0; i < columns.size(); ++i) { + EXPECT_EQ(columns[i]->size(), argument_columns[i]->size()); + checkColumn(*columns[i], *argument_columns[i], *data_types[i], columns[0]->size()); + } + } + } + + // serialize_vec, deserialize_vec (called by MethodSerialized.init_serialized_keys), here are some scenarios: + // 1/ AggState: groupby key column which be serialized to hash-table key, eg.AggLocalState::_emplace_into_hash_table + // 2/ JoinState: hash join key column which be serialized to hash-table key, or probe column which be serialized to hash-table key, eg.ProcessHashTableBuild, ProcessHashTableProbe<JoinOpType>::probe_side_output_column + // serialize_vec_with_null_map, deserialize_vec_with_null_map which only called by ColumnNullable serialize_vec and deserialize_vec, and derived by other columns + // get_max_row_byte_size used in MethodSerialized which calculating the memory size for vectorized serialization of aggregation keys. + void ser_deser_vec(MutableColumns& columns, DataTypes dataTypes) { + // step1. make input_keys with given rows for a block + size_t rows = columns[0]->size(); + std::vector<StringRef> input_keys; + input_keys.resize(rows); + MutableColumns check_columns(columns.size()); + int c = 0; + for (auto& column : columns) { + check_columns[c] = column->clone_empty(); + ++c; + } + + // step2. calculate the needed memory size for vectorized serialization of aggregation keys + size_t max_one_row_byte_size = 0; + for (const auto& column : columns) { + max_one_row_byte_size += column->get_max_row_byte_size(); + } + size_t memory_size = max_one_row_byte_size * rows; + Arena arena(memory_size); + auto* serialized_key_buffer = reinterpret_cast<uint8_t*>(arena.alloc(memory_size)); + + // serialize the keys into arena + { + // step3. serialize the keys into arena + for (size_t i = 0; i < rows; ++i) { + input_keys[i].data = + reinterpret_cast<char*>(serialized_key_buffer + i * max_one_row_byte_size); + input_keys[i].size = 0; + std::cout << "input:" << input_keys[i].to_string() << std::endl; + } + for (const auto& column : columns) { + column->serialize_vec(input_keys, rows, max_one_row_byte_size); + } + } + // deserialize the keys from arena into columns + { + // step4. deserialize the keys from arena into columns + for (auto& column : check_columns) { + column->deserialize_vec(input_keys, rows); + } + } + // check the deserialized columns + { + for (size_t i = 0; i < columns.size(); ++i) { + EXPECT_EQ(columns[i]->size(), check_columns[i]->size()); + checkColumn(*columns[i], *check_columns[i], *dataTypes[i], rows); + } + } + } + + PaddedPODArray<UInt8> create_filter(std::vector<uint8_t> data) { + PaddedPODArray<UInt8> filter; + filter.insert(filter.end(), data.begin(), data.end()); + return filter; + } + + // filter calculation: + // filter (called in Block::filter_block_internal to filter data with filter filled with 0or1 array, like: [0,1,0,1]) + // used in join to filter next block by row_ids, and filter column by row_ids in first read which called in SegmentIterator + void filterAssert(MutableColumnPtr col, std::vector<uint8_t> filter, size_t expect_size) { + EXPECT_EQ(col->size(), filter.size()); + auto filted_col = col->filter(create_filter(filter), expect_size); + EXPECT_EQ(filted_col->size(), expect_size); + int iter = 0; + for (size_t i = 0; i < filter.size(); i++) { + if (filter[i]) { + iter++; + } + } + } + + // filter_by_selector (called SegmentIterator::copy_column_data_by_selector, + // now just used in filter column, according to the selector to + // select size of row_ids for column by given column, which only used for predict_column and column_dictionary, column_nullable sometimes in Schema::get_predicate_column_ptr() also will return) + void filterBySelectorAssert(vectorized::IColumn::MutablePtr col, std::vector<uint16_t> selector, + const IDataType& dt, MutableColumnPtr should_sel_col, + size_t expect_size) { + // only used in column_nullable and predict_column, column_dictionary + EXPECT_TRUE(col->is_nullable() || col->is_column_dictionary() || + col->is_predicate_column()); + // for every data type should assert behavior in own UT case + col->clear(); + col->insert_many_defaults(should_sel_col->size()); + std::cout << "col size:" << col->size() << std::endl; + auto sel = should_sel_col->clone_empty(); + Status st = col->filter_by_selector(selector.data(), expect_size, sel); + EXPECT_EQ(st, Status::OK()); + EXPECT_EQ(sel->size(), expect_size); + printColumn(*sel, dt); + } + + void assertPermutationsWithLimit(const IColumn::Permutation& lhs, + const IColumn::Permutation& rhs, size_t limit) { + if (limit == 0) { + limit = lhs.size(); + } + + for (size_t i = 0; i < limit; ++i) { + ASSERT_EQ(lhs[i], rhs[i]); + } + } + + // this function is common function to produce column, according to ColumnValueGetter + // this range_size can be set, and it is helpfully make common column data which can be inserted into columns. + template <typename ColumnValueGetter> + void generateRanges(std::vector<std::vector<Field>>& ranges, size_t range_size, + ColumnValueGetter getter) { + for (auto& range : ranges) { + range.clear(); + } + + size_t ranges_size = ranges.size(); + + for (size_t range_index = 0; range_index < ranges_size; ++range_index) { + for (size_t index_in_range = 0; index_in_range < range_size; ++index_in_range) { + auto value = getter(range_index, index_in_range); + ranges[range_index].emplace_back(value); + } + } + } + + void insertRangesIntoColumn(std::vector<std::vector<Field>>& ranges, + IColumn::Permutation& ranges_permutations, + vectorized::IColumn& column) { + for (const auto& range_permutation : ranges_permutations) { + auto& range = ranges[range_permutation]; + for (auto& value : range) { + column.insert(value); + } + } + } + + // this function helps to check sort permutation behavior for column + void stableGetColumnPermutation(const IColumn& column, bool ascending, size_t limit, + int nan_direction_hint, IColumn::Permutation& out_permutation) { + (void)(limit); Review Comment: to get column permutation in order by compare_at() function which can make a sequence result for ```column.get_permutation``` -- This is an automated message from the Apache Git Service. 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