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doris/be/src/vec/aggregate_functions/aggregate_function_collect.h
plat1ko 6dd60c6ebb [Enhance](BE) Add -Wshadow-field compile option to avoid unexpected shadowing behavior (#25698)
* Fix `Tablet::_meta_lock` shadows member inherited from `BaseTablet`

* Add -Wshadow-field compile option to avoid unexpected shadowing behavior
2023-10-26 10:00:28 +08:00

674 lines
25 KiB
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// 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.
#pragma once
#include <assert.h>
#include <glog/logging.h>
#include <string.h>
#include <limits>
#include <memory>
#include <new>
#include <string>
#include "vec/aggregate_functions/aggregate_function.h"
#include "vec/columns/column.h"
#include "vec/columns/column_array.h"
#include "vec/columns/column_decimal.h"
#include "vec/columns/column_nullable.h"
#include "vec/columns/column_string.h"
#include "vec/columns/columns_number.h"
#include "vec/common/assert_cast.h"
#include "vec/common/hash_table/hash_set.h"
#include "vec/common/pod_array_fwd.h"
#include "vec/common/string_buffer.hpp"
#include "vec/common/string_ref.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_nullable.h"
#include "vec/io/io_helper.h"
#include "vec/io/var_int.h"
namespace doris {
namespace vectorized {
class Arena;
} // namespace vectorized
} // namespace doris
template <typename, typename>
struct DefaultHash;
namespace doris::vectorized {
template <typename T, typename HasLimit>
struct AggregateFunctionCollectSetData {
using ElementType = T;
using ColVecType = ColumnVectorOrDecimal<ElementType>;
using ElementNativeType = typename NativeType<T>::Type;
using SelfType = AggregateFunctionCollectSetData;
using Set = HashSetWithStackMemory<ElementNativeType, DefaultHash<ElementNativeType>, 4>;
Set data_set;
Int64 max_size = -1;
size_t size() const { return data_set.size(); }
void add(const IColumn& column, size_t row_num) {
data_set.insert(assert_cast<const ColVecType&>(column).get_data()[row_num]);
}
void merge(const SelfType& rhs) {
if constexpr (HasLimit::value) {
if (max_size == -1) {
max_size = rhs.max_size;
}
for (auto& rhs_elem : rhs.data_set) {
if (size() >= max_size) {
return;
}
data_set.insert(rhs_elem.get_value());
}
} else {
data_set.merge(rhs.data_set);
}
}
void write(BufferWritable& buf) const {
data_set.write(buf);
write_var_int(max_size, buf);
}
void read(BufferReadable& buf) {
data_set.read(buf);
read_var_int(max_size, buf);
}
void insert_result_into(IColumn& to) const {
auto& vec = assert_cast<ColVecType&>(to).get_data();
vec.reserve(size());
for (const auto& item : data_set) {
vec.push_back(item.key);
}
}
void reset() { data_set.clear(); }
};
template <typename HasLimit>
struct AggregateFunctionCollectSetData<StringRef, HasLimit> {
using ElementType = StringRef;
using ColVecType = ColumnString;
using SelfType = AggregateFunctionCollectSetData<ElementType, HasLimit>;
using Set = HashSetWithStackMemory<ElementType, DefaultHash<ElementType>, 4>;
Set data_set;
Int64 max_size = -1;
size_t size() const { return data_set.size(); }
void add(const IColumn& column, size_t row_num, Arena* arena) {
Set::LookupResult it;
bool inserted;
auto key = column.get_data_at(row_num);
key.data = arena->insert(key.data, key.size);
data_set.emplace(key, it, inserted);
}
void merge(const SelfType& rhs, Arena* arena) {
bool inserted;
Set::LookupResult it;
if (max_size == -1) {
max_size = rhs.max_size;
}
max_size = rhs.max_size;
for (auto& rhs_elem : rhs.data_set) {
if constexpr (HasLimit::value) {
if (size() >= max_size) {
return;
}
}
assert(arena != nullptr);
StringRef key = rhs_elem.get_value();
key.data = arena->insert(key.data, key.size);
data_set.emplace(key, it, inserted);
}
}
void write(BufferWritable& buf) const {
write_var_uint(size(), buf);
for (const auto& elem : data_set) {
write_string_binary(elem.get_value(), buf);
}
write_var_int(max_size, buf);
}
void read(BufferReadable& buf) {
UInt64 size;
read_var_uint(size, buf);
StringRef ref;
for (size_t i = 0; i < size; ++i) {
read_string_binary(ref, buf);
data_set.insert(ref);
}
read_var_int(max_size, buf);
}
void insert_result_into(IColumn& to) const {
auto& vec = assert_cast<ColVecType&>(to);
vec.reserve(size());
for (const auto& item : data_set) {
vec.insert_data(item.key.data, item.key.size);
}
}
void reset() { data_set.clear(); }
};
template <typename T, typename HasLimit>
struct AggregateFunctionCollectListData {
using ElementType = T;
using ColVecType = ColumnVectorOrDecimal<ElementType>;
using SelfType = AggregateFunctionCollectListData<ElementType, HasLimit>;
PaddedPODArray<ElementType> data;
Int64 max_size = -1;
size_t size() const { return data.size(); }
void add(const IColumn& column, size_t row_num) {
const auto& vec = assert_cast<const ColVecType&>(column).get_data();
data.push_back(vec[row_num]);
}
void merge(const SelfType& rhs) {
if constexpr (HasLimit::value) {
if (max_size == -1) {
max_size = rhs.max_size;
}
max_size = rhs.max_size;
for (auto& rhs_elem : rhs.data) {
if (size() >= max_size) {
return;
}
data.push_back(rhs_elem);
}
} else {
data.insert(rhs.data.begin(), rhs.data.end());
}
}
void write(BufferWritable& buf) const {
write_var_uint(size(), buf);
buf.write(data.raw_data(), size() * sizeof(ElementType));
write_var_int(max_size, buf);
}
void read(BufferReadable& buf) {
UInt64 rows = 0;
read_var_uint(rows, buf);
data.resize(rows);
buf.read(reinterpret_cast<char*>(data.data()), rows * sizeof(ElementType));
read_var_int(max_size, buf);
}
void reset() { data.clear(); }
void insert_result_into(IColumn& to) const {
auto& vec = assert_cast<ColVecType&>(to).get_data();
size_t old_size = vec.size();
vec.resize(old_size + size());
memcpy(vec.data() + old_size, data.data(), size() * sizeof(ElementType));
}
};
template <typename HasLimit>
struct AggregateFunctionCollectListData<StringRef, HasLimit> {
using ElementType = StringRef;
using ColVecType = ColumnString;
MutableColumnPtr data;
Int64 max_size = -1;
AggregateFunctionCollectListData() { data = ColVecType::create(); }
size_t size() const { return data->size(); }
void add(const IColumn& column, size_t row_num) { data->insert_from(column, row_num); }
void merge(const AggregateFunctionCollectListData& rhs) {
if constexpr (HasLimit::value) {
if (max_size == -1) {
max_size = rhs.max_size;
}
max_size = rhs.max_size;
data->insert_range_from(*rhs.data, 0,
std::min(assert_cast<size_t>(max_size - size()), rhs.size()));
} else {
data->insert_range_from(*rhs.data, 0, rhs.size());
}
}
void write(BufferWritable& buf) const {
auto& col = assert_cast<ColVecType&>(*data);
write_var_uint(col.size(), buf);
buf.write(col.get_offsets().raw_data(), col.size() * sizeof(IColumn::Offset));
write_var_uint(col.get_chars().size(), buf);
buf.write(col.get_chars().raw_data(), col.get_chars().size());
write_var_int(max_size, buf);
}
void read(BufferReadable& buf) {
auto& col = assert_cast<ColVecType&>(*data);
UInt64 offs_size = 0;
read_var_uint(offs_size, buf);
col.get_offsets().resize(offs_size);
buf.read(reinterpret_cast<char*>(col.get_offsets().data()),
offs_size * sizeof(IColumn::Offset));
UInt64 chars_size = 0;
read_var_uint(chars_size, buf);
col.get_chars().resize(chars_size);
buf.read(reinterpret_cast<char*>(col.get_chars().data()), chars_size);
read_var_int(max_size, buf);
}
void reset() { data->clear(); }
void insert_result_into(IColumn& to) const {
auto& to_str = assert_cast<ColVecType&>(to);
to_str.insert_range_from(*data, 0, size());
}
};
template <typename T>
struct AggregateFunctionArrayAggData {
using ElementType = T;
using ColVecType = ColumnVectorOrDecimal<ElementType>;
MutableColumnPtr column_data;
ColVecType* nested_column;
NullMap* null_map;
AggregateFunctionArrayAggData(const DataTypes& argument_types) {
if constexpr (IsDecimalNumber<T>) {
DataTypePtr column_type = make_nullable(argument_types[0]);
column_data = column_type->create_column();
null_map = &(assert_cast<ColumnNullable&>(*column_data).get_null_map_data());
nested_column = assert_cast<ColVecType*>(
assert_cast<ColumnNullable&>(*column_data).get_nested_column_ptr().get());
}
}
AggregateFunctionArrayAggData() {
if constexpr (!IsDecimalNumber<T>) {
column_data = ColumnNullable::create(ColVecType::create(), ColumnUInt8::create());
null_map = &(assert_cast<ColumnNullable&>(*column_data).get_null_map_data());
nested_column = assert_cast<ColVecType*>(
assert_cast<ColumnNullable&>(*column_data).get_nested_column_ptr().get());
}
}
void add(const IColumn& column, size_t row_num) {
const auto& col = assert_cast<const ColumnNullable&>(column);
const auto& vec = assert_cast<const ColVecType&>(col.get_nested_column()).get_data();
null_map->push_back(col.get_null_map_data()[row_num]);
nested_column->get_data().push_back(vec[row_num]);
DCHECK(null_map->size() == nested_column->size());
}
void deserialize_and_merge(const IColumn& column, size_t row_num) {
auto& to_arr = assert_cast<const ColumnArray&>(column);
auto& to_nested_col = to_arr.get_data();
auto col_null = reinterpret_cast<const ColumnNullable*>(&to_nested_col);
const auto& vec = assert_cast<const ColVecType&>(col_null->get_nested_column()).get_data();
auto start = to_arr.get_offsets()[row_num - 1];
auto end = start + to_arr.get_offsets()[row_num] - to_arr.get_offsets()[row_num - 1];
for (auto i = start; i < end; ++i) {
null_map->push_back(col_null->get_null_map_data()[i]);
nested_column->get_data().push_back(vec[i]);
}
}
void reset() {
null_map->clear();
nested_column->clear();
}
void insert_result_into(IColumn& to) const {
auto& to_arr = assert_cast<ColumnArray&>(to);
auto& to_nested_col = to_arr.get_data();
auto col_null = reinterpret_cast<ColumnNullable*>(&to_nested_col);
auto& vec = assert_cast<ColVecType&>(col_null->get_nested_column()).get_data();
size_t num_rows = null_map->size();
auto& nested_column_data = nested_column->get_data();
for (size_t i = 0; i < num_rows; ++i) {
col_null->get_null_map_data().push_back((*null_map)[i]);
vec.push_back(nested_column_data[i]);
}
to_arr.get_offsets().push_back(to_nested_col.size());
}
};
template <>
struct AggregateFunctionArrayAggData<StringRef> {
using ElementType = StringRef;
using ColVecType = ColumnString;
MutableColumnPtr column_data;
ColVecType* nested_column;
NullMap* null_map;
AggregateFunctionArrayAggData() {
column_data = ColumnNullable::create(ColVecType::create(), ColumnUInt8::create());
null_map = &(assert_cast<ColumnNullable&>(*column_data).get_null_map_data());
nested_column = assert_cast<ColVecType*>(
assert_cast<ColumnNullable&>(*column_data).get_nested_column_ptr().get());
}
void add(const IColumn& column, size_t row_num) {
const auto& col = assert_cast<const ColumnNullable&>(column);
const auto& vec = assert_cast<const ColVecType&>(col.get_nested_column());
null_map->push_back(col.get_null_map_data()[row_num]);
nested_column->insert_from(vec, row_num);
DCHECK(null_map->size() == nested_column->size());
}
void deserialize_and_merge(const IColumn& column, size_t row_num) {
auto& to_arr = assert_cast<const ColumnArray&>(column);
auto& to_nested_col = to_arr.get_data();
auto col_null = reinterpret_cast<const ColumnNullable*>(&to_nested_col);
const auto& vec = assert_cast<const ColVecType&>(col_null->get_nested_column());
auto start = to_arr.get_offsets()[row_num - 1];
auto end = start + to_arr.get_offsets()[row_num] - to_arr.get_offsets()[row_num - 1];
for (auto i = start; i < end; ++i) {
null_map->push_back(col_null->get_null_map_data()[i]);
nested_column->insert_from(vec, i);
}
}
void reset() {
null_map->clear();
nested_column->clear();
}
void insert_result_into(IColumn& to) const {
auto& to_arr = assert_cast<ColumnArray&>(to);
auto& to_nested_col = to_arr.get_data();
auto col_null = reinterpret_cast<ColumnNullable*>(&to_nested_col);
auto& vec = assert_cast<ColVecType&>(col_null->get_nested_column());
size_t num_rows = null_map->size();
for (size_t i = 0; i < num_rows; ++i) {
col_null->get_null_map_data().push_back((*null_map)[i]);
vec.insert_from(*nested_column, i);
}
to_arr.get_offsets().push_back(to_nested_col.size());
}
};
//ShowNull is just used to support array_agg because array_agg needs to display NULL
//todo: Supports order by sorting for array_agg
template <typename Data, typename HasLimit, typename ShowNull>
class AggregateFunctionCollect
: public IAggregateFunctionDataHelper<Data,
AggregateFunctionCollect<Data, HasLimit, ShowNull>> {
using GenericType = AggregateFunctionCollectSetData<StringRef, HasLimit>;
static constexpr bool ENABLE_ARENA = std::is_same_v<Data, GenericType>;
public:
using BaseHelper = IAggregateFunctionHelper<AggregateFunctionCollect<Data, HasLimit, ShowNull>>;
AggregateFunctionCollect(const DataTypes& argument_types_,
UInt64 max_size_ = std::numeric_limits<UInt64>::max())
: IAggregateFunctionDataHelper<Data,
AggregateFunctionCollect<Data, HasLimit, ShowNull>>(
{argument_types_}),
return_type(argument_types_[0]) {}
std::string get_name() const override {
if constexpr (ShowNull::value) {
return "array_agg";
} else if constexpr (std::is_same_v<AggregateFunctionCollectListData<
typename Data::ElementType, HasLimit>,
Data>) {
return "collect_list";
} else {
return "collect_set";
}
}
void create(AggregateDataPtr __restrict place) const override {
if constexpr (ShowNull::value) {
if constexpr (IsDecimalNumber<typename Data::ElementType>) {
new (place) Data(argument_types);
} else {
new (place) Data();
}
} else {
new (place) Data();
}
}
DataTypePtr get_return_type() const override {
return std::make_shared<DataTypeArray>(make_nullable(return_type));
}
bool allocates_memory_in_arena() const override { return ENABLE_ARENA; }
void add(AggregateDataPtr __restrict place, const IColumn** columns, size_t row_num,
Arena* arena) const override {
auto& data = this->data(place);
if constexpr (HasLimit::value) {
if (data.max_size == -1) {
data.max_size =
(UInt64)assert_cast<const ColumnInt32*>(columns[1])->get_element(row_num);
}
if (data.size() >= data.max_size) {
return;
}
}
if constexpr (ENABLE_ARENA) {
data.add(*columns[0], row_num, arena);
} else {
data.add(*columns[0], row_num);
}
}
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs,
Arena* arena) const override {
auto& data = this->data(place);
auto& rhs_data = this->data(rhs);
if constexpr (ENABLE_ARENA) {
data.merge(rhs_data, arena);
} else if constexpr (!ShowNull::value) {
data.merge(rhs_data);
}
}
void serialize(ConstAggregateDataPtr __restrict place, BufferWritable& buf) const override {
if constexpr (!ShowNull::value) {
this->data(place).write(buf);
}
}
void deserialize(AggregateDataPtr __restrict place, BufferReadable& buf,
Arena*) const override {
if constexpr (!ShowNull::value) {
this->data(place).read(buf);
}
}
void insert_result_into(ConstAggregateDataPtr __restrict place, IColumn& to) const override {
auto& to_arr = assert_cast<ColumnArray&>(to);
auto& to_nested_col = to_arr.get_data();
if constexpr (ShowNull::value) {
DCHECK(to_nested_col.is_nullable());
this->data(place).insert_result_into(to);
} else {
if (to_nested_col.is_nullable()) {
auto col_null = reinterpret_cast<ColumnNullable*>(&to_nested_col);
this->data(place).insert_result_into(col_null->get_nested_column());
col_null->get_null_map_data().resize_fill(col_null->get_nested_column().size(), 0);
} else {
this->data(place).insert_result_into(to_nested_col);
}
to_arr.get_offsets().push_back(to_nested_col.size());
}
}
void serialize_without_key_to_column(ConstAggregateDataPtr __restrict place,
IColumn& to) const override {
if constexpr (ShowNull::value) {
this->data(place).insert_result_into(to);
} else {
return BaseHelper::serialize_without_key_to_column(place, to);
}
}
void deserialize_and_merge_from_column(AggregateDataPtr __restrict place, const IColumn& column,
Arena* arena) const override {
if constexpr (ShowNull::value) {
const size_t num_rows = column.size();
for (size_t i = 0; i != num_rows; ++i) {
this->data(place).deserialize_and_merge(column, i);
}
} else {
return BaseHelper::deserialize_and_merge_from_column(place, column, arena);
}
}
void deserialize_and_merge_vec(const AggregateDataPtr* places, size_t offset,
AggregateDataPtr rhs, const ColumnString* column, Arena* arena,
const size_t num_rows) const override {
if constexpr (ShowNull::value) {
for (size_t i = 0; i != num_rows; ++i) {
this->data(places[i]).deserialize_and_merge(*assert_cast<const IColumn*>(column),
i);
}
} else {
return BaseHelper::deserialize_and_merge_vec(places, offset, rhs, column, arena,
num_rows);
}
}
void deserialize_from_column(AggregateDataPtr places, const IColumn& column, Arena* arena,
size_t num_rows) const override {
if constexpr (ShowNull::value) {
for (size_t i = 0; i != num_rows; ++i) {
this->data(places).deserialize_and_merge(column, i);
}
} else {
return BaseHelper::deserialize_from_column(places, column, arena, num_rows);
}
}
void deserialize_and_merge_from_column_range(AggregateDataPtr __restrict place,
const IColumn& column, size_t begin, size_t end,
Arena* arena) const override {
if constexpr (ShowNull::value) {
DCHECK(end <= column.size() && begin <= end) << ", begin:" << begin << ", end:" << end
<< ", column.size():" << column.size();
for (size_t i = begin; i <= end; ++i) {
this->data(place).deserialize_and_merge(column, i);
}
} else {
return BaseHelper::deserialize_and_merge_from_column_range(place, column, begin, end,
arena);
}
}
void deserialize_and_merge_vec_selected(const AggregateDataPtr* places, size_t offset,
AggregateDataPtr rhs, const ColumnString* column,
Arena* arena, const size_t num_rows) const override {
if constexpr (ShowNull::value) {
for (size_t i = 0; i != num_rows; ++i) {
if (places[i]) {
this->data(places[i]).deserialize_and_merge(
*assert_cast<const IColumn*>(column), i);
}
}
} else {
return BaseHelper::deserialize_and_merge_vec_selected(places, offset, rhs, column,
arena, num_rows);
}
}
void serialize_to_column(const std::vector<AggregateDataPtr>& places, size_t offset,
MutableColumnPtr& dst, const size_t num_rows) const override {
if constexpr (ShowNull::value) {
for (size_t i = 0; i != num_rows; ++i) {
Data& data_ = this->data(places[i] + offset);
data_.insert_result_into(*dst);
}
} else {
return BaseHelper::serialize_to_column(places, offset, dst, num_rows);
}
}
void streaming_agg_serialize_to_column(const IColumn** columns, MutableColumnPtr& dst,
const size_t num_rows, Arena* arena) const override {
if constexpr (ShowNull::value) {
auto& to_arr = assert_cast<ColumnArray&>(*dst);
auto& to_nested_col = to_arr.get_data();
DCHECK(num_rows == columns[0]->size());
auto col_null = reinterpret_cast<ColumnNullable*>(&to_nested_col);
const auto& col_src = assert_cast<const ColumnNullable&>(*(columns[0]));
for (size_t i = 0; i < num_rows; ++i) {
col_null->get_null_map_data().push_back(col_src.get_null_map_data()[i]);
if constexpr (std::is_same_v<StringRef, typename Data::ElementType>) {
auto& vec = assert_cast<ColumnString&>(col_null->get_nested_column());
const auto& vec_src =
assert_cast<const ColumnString&>(col_src.get_nested_column());
vec.insert_from(vec_src, i);
} else {
using ColVecType = ColumnVectorOrDecimal<typename Data::ElementType>;
auto& vec = assert_cast<ColVecType&>(col_null->get_nested_column()).get_data();
auto& vec_src =
assert_cast<const ColVecType&>(col_src.get_nested_column()).get_data();
vec.push_back(vec_src[i]);
}
to_arr.get_offsets().push_back(to_nested_col.size());
}
} else {
return BaseHelper::streaming_agg_serialize_to_column(columns, dst, num_rows, arena);
}
}
[[nodiscard]] MutableColumnPtr create_serialize_column() const override {
if constexpr (ShowNull::value) {
return get_return_type()->create_column();
} else {
return ColumnString::create();
}
}
[[nodiscard]] DataTypePtr get_serialized_type() const override {
if constexpr (ShowNull::value) {
return std::make_shared<DataTypeArray>(make_nullable(return_type));
} else {
return IAggregateFunction::get_serialized_type();
}
}
private:
DataTypePtr return_type;
using IAggregateFunction::argument_types;
};
} // namespace doris::vectorized