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// Licensed to the Apache Software Foundation (ASF) under one
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// 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 "olap/block_column_predicate.h"
#include <string.h>
namespace roaring {
class Roaring;
} // namespace roaring
namespace doris {
class WrapperField;
namespace segment_v2 {
class InvertedIndexIterator;
} // namespace segment_v2
uint16_t SingleColumnBlockPredicate::evaluate(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size) const {
auto column_id = _predicate->column_id();
auto& column = block[column_id];
return _predicate->evaluate(*column, sel, selected_size);
}
void SingleColumnBlockPredicate::evaluate_and(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
auto column_id = _predicate->column_id();
auto& column = block[column_id];
_predicate->evaluate_and(*column, sel, selected_size, flags);
}
bool SingleColumnBlockPredicate::evaluate_and(
const std::pair<WrapperField*, WrapperField*>& statistic) const {
return _predicate->evaluate_and(statistic);
}
bool SingleColumnBlockPredicate::evaluate_and(const segment_v2::BloomFilter* bf) const {
return _predicate->evaluate_and(bf);
}
bool SingleColumnBlockPredicate::evaluate_and(const StringRef* dict_words,
const size_t dict_num) const {
return _predicate->evaluate_and(dict_words, dict_num);
}
void SingleColumnBlockPredicate::evaluate_or(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
auto column_id = _predicate->column_id();
auto& column = block[column_id];
_predicate->evaluate_or(*column, sel, selected_size, flags);
}
void SingleColumnBlockPredicate::evaluate_vec(vectorized::MutableColumns& block, uint16_t size,
bool* flags) const {
auto column_id = _predicate->column_id();
auto& column = block[column_id];
// Dictionary column should do something to initial.
if (PredicateTypeTraits::is_range(_predicate->type())) {
column->convert_dict_codes_if_necessary();
} else if (PredicateTypeTraits::is_bloom_filter(_predicate->type())) {
column->initialize_hash_values_for_runtime_filter();
}
_predicate->evaluate_vec(*column, size, flags);
}
uint16_t OrBlockColumnPredicate::evaluate(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size) const {
if (num_of_column_predicate() == 1) {
return _block_column_predicate_vec[0]->evaluate(block, sel, selected_size);
} else {
if (!selected_size) {
return 0;
}
std::vector<uint8_t> ret_flags(selected_size, 0);
for (int i = 0; i < num_of_column_predicate(); ++i) {
_block_column_predicate_vec[i]->evaluate_or(block, sel, selected_size,
(bool*)ret_flags.data());
}
uint16_t new_size = 0;
for (int i = 0; i < selected_size; ++i) {
if (ret_flags[i]) {
sel[new_size++] = sel[i];
}
}
return new_size;
}
}
void OrBlockColumnPredicate::evaluate_or(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
for (auto& block_column_predicate : _block_column_predicate_vec) {
block_column_predicate->evaluate_or(block, sel, selected_size, flags);
}
}
void OrBlockColumnPredicate::evaluate_and(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
if (num_of_column_predicate() == 1) {
_block_column_predicate_vec[0]->evaluate_and(block, sel, selected_size, flags);
} else {
std::vector<uint8_t> ret_flags(selected_size, 0);
for (int i = 0; i < num_of_column_predicate(); ++i) {
_block_column_predicate_vec[i]->evaluate_or(block, sel, selected_size,
(bool*)ret_flags.data());
}
for (int i = 0; i < selected_size; ++i) {
flags[i] &= ret_flags[i];
}
}
}
uint16_t AndBlockColumnPredicate::evaluate(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size) const {
for (auto& block_column_predicate : _block_column_predicate_vec) {
selected_size = block_column_predicate->evaluate(block, sel, selected_size);
}
return selected_size;
}
void AndBlockColumnPredicate::evaluate_and(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
for (auto& block_column_predicate : _block_column_predicate_vec) {
block_column_predicate->evaluate_and(block, sel, selected_size, flags);
}
}
bool AndBlockColumnPredicate::evaluate_and(
const std::pair<WrapperField*, WrapperField*>& statistic) const {
for (auto& block_column_predicate : _block_column_predicate_vec) {
if (!block_column_predicate->evaluate_and(statistic)) {
return false;
}
}
return true;
}
bool AndBlockColumnPredicate::evaluate_and(const segment_v2::BloomFilter* bf) const {
for (auto& block_column_predicate : _block_column_predicate_vec) {
if (!block_column_predicate->evaluate_and(bf)) {
return false;
}
}
return true;
}
bool AndBlockColumnPredicate::evaluate_and(const StringRef* dict_words,
const size_t dict_num) const {
for (auto& predicate : _block_column_predicate_vec) {
if (!predicate->evaluate_and(dict_words, dict_num)) {
return false;
}
}
return true;
}
void AndBlockColumnPredicate::evaluate_or(vectorized::MutableColumns& block, uint16_t* sel,
uint16_t selected_size, bool* flags) const {
if (num_of_column_predicate() == 1) {
_block_column_predicate_vec[0]->evaluate_or(block, sel, selected_size, flags);
} else {
std::vector<uint8_t> new_flags(selected_size, 1);
for (const auto& block_column_predicate : _block_column_predicate_vec) {
block_column_predicate->evaluate_and(block, sel, selected_size,
(bool*)new_flags.data());
}
for (uint16_t i = 0; i < selected_size; i++) {
flags[i] |= new_flags[i];
}
}
}
// todo(wb) Can the 'and' of multiple bitmaps be vectorized?
void AndBlockColumnPredicate::evaluate_vec(vectorized::MutableColumns& block, uint16_t size,
bool* flags) const {
if (num_of_column_predicate() == 1) {
_block_column_predicate_vec[0]->evaluate_vec(block, size, flags);
} else {
std::vector<uint8_t> new_flags(size);
bool initialized = false;
for (const auto& block_column_predicate : _block_column_predicate_vec) {
if (initialized) {
block_column_predicate->evaluate_vec(block, size, (bool*)new_flags.data());
for (uint16_t j = 0; j < size; j++) {
flags[j] &= new_flags[j];
}
} else {
block_column_predicate->evaluate_vec(block, size, flags);
initialized = true;
}
}
}
}
Status AndBlockColumnPredicate::evaluate(const std::string& column_name,
InvertedIndexIterator* iterator, uint32_t num_rows,
roaring::Roaring* bitmap) const {
return Status::Error<ErrorCode::INVERTED_INDEX_NOT_IMPLEMENTED>(
"Not Implemented evaluate with inverted index, please check the predicate");
}
} // namespace doris