yiguolei commented on code in PR #10355: URL: https://github.com/apache/doris/pull/10355#discussion_r919616378
########## be/src/olap/like_column_predicate.cpp: ########## @@ -0,0 +1,168 @@ +// 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 "udf/udf.h" +#include "olap/like_column_predicate.h" +#include "olap/field.h" +#include "runtime/string_value.hpp" +#include "runtime/vectorized_row_batch.h" + +namespace doris { + +LikeColumnPredicate::LikeColumnPredicate(bool opposite, uint32_t column_id, doris_udf::FunctionContext* fn_ctx, doris_udf::StringVal val) + : ColumnPredicate(column_id, opposite), _fn_ctx(fn_ctx), pattern(val) { + _state = reinterpret_cast<LikePredicateState*>(_fn_ctx->get_function_state(doris_udf::FunctionContext::THREAD_LOCAL)); +} + +void LikeColumnPredicate::evaluate(VectorizedRowBatch* batch) const { + uint16_t n = batch->size(); + uint16_t* sel = batch->selected(); + if (!batch->selected_in_use()) { + for (uint16_t i = 0; i != n; ++i) { + sel[i] = i; + } + } +} + +void LikeColumnPredicate::evaluate(ColumnBlock* block, uint16_t* sel, uint16_t* size) const { + if (block->is_nullable()) { + _base_evaluate<true>(block, sel, size); + } else { + _base_evaluate<false>(block, sel, size); + } +} + +void LikeColumnPredicate::evaluate(vectorized::IColumn& column, uint16_t* sel, uint16_t* size) const { + uint16_t new_size = 0; + + if (column.is_nullable()) { + auto* nullable_col = vectorized::check_and_get_column<vectorized::ColumnNullable>(column); + auto& null_map_data = nullable_col->get_null_map_column().get_data(); + auto& nested_col = nullable_col->get_nested_column(); + if (nested_col.is_column_dictionary()) { + auto* nested_col_ptr = vectorized::check_and_get_column<vectorized::ColumnDictionary<vectorized::Int32>>(nested_col); + auto& data_array = nested_col_ptr->get_data(); + for (uint16_t i = 0; i < *size; i++) { + uint16_t idx = sel[i]; + sel[new_size] = idx; + if (null_map_data[idx]) { + new_size += _opposite; + continue; + } + + StringValue cell_value = nested_col_ptr->get_value(data_array[idx]); + doris_udf::StringVal target; + cell_value.to_string_val(&target); + new_size += _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } + else + { + for (uint16_t i = 0; i < *size; i++) { + uint16_t idx = sel[i]; + sel[new_size] = idx; + if (null_map_data[idx]) { + new_size += _opposite; + continue; + } + + StringRef cell_value = nested_col.get_data_at(idx); + doris_udf::StringVal target = cell_value.to_string_val(); + new_size += _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } + } else { + if (column.is_column_dictionary()) { + auto* nested_col_ptr = vectorized::check_and_get_column<vectorized::ColumnDictionary<vectorized::Int32>>(column); + auto& data_array = nested_col_ptr->get_data(); + for (uint16_t i = 0; i < *size; i++) { + uint16_t idx = sel[i]; + sel[new_size] = idx; + StringValue cell_value = nested_col_ptr->get_value(data_array[idx]); + doris_udf::StringVal target; + cell_value.to_string_val(&target); + new_size += _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } else { + for (uint16_t i = 0; i < *size; i++) { + uint16_t idx = sel[i]; + sel[new_size] = idx; + StringRef cell_value = column.get_data_at(idx); + doris_udf::StringVal target = cell_value.to_string_val(); + new_size += _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } + } + + *size = new_size; +} + +void LikeColumnPredicate::evaluate_vec(vectorized::IColumn& column, uint16_t size, bool* flags) const { + if (column.is_nullable()) { + auto* nullable_col = vectorized::check_and_get_column<vectorized::ColumnNullable>(column); + auto& null_map_data = nullable_col->get_null_map_column().get_data(); + auto& nested_col = nullable_col->get_nested_column(); + if (nested_col.is_column_dictionary()) { + auto* nested_col_ptr = vectorized::check_and_get_column<vectorized::ColumnDictionary<vectorized::Int32>>(nested_col); + auto& data_array = nested_col_ptr->get_data(); + for (uint16_t i = 0; i < size; i++) { + if (null_map_data[i]) { + flags[i] = _opposite; + continue; + } + + StringValue cell_value = nested_col_ptr->get_value(data_array[i]); + doris_udf::StringVal target; + cell_value.to_string_val(&target); + flags[i] = _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } + else + { + for (uint16_t i = 0; i < size; i++) { + if (null_map_data[i]) { + flags[i] = _opposite; + continue; + } + + StringRef cell_value = nested_col.get_data_at(i); + doris_udf::StringVal target = cell_value.to_string_val(); + flags[i] = _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); + } + } + } else { + if (column.is_column_dictionary()) { + auto* nested_col_ptr = vectorized::check_and_get_column<vectorized::ColumnDictionary<vectorized::Int32>>(column); + auto& data_array = nested_col_ptr->get_data(); + for (uint16_t i = 0; i < size; i++) { + StringValue cell_value = nested_col_ptr->get_value(data_array[i]); + doris_udf::StringVal target; + cell_value.to_string_val(&target); + flags[i] = _opposite ^ ((_state->function)(_fn_ctx, target, pattern).val); Review Comment: better use _opposite as template parameters and use if const expr opposite here. 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