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doris/be/src/olap/memtable.cpp

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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.
#include "olap/memtable.h"
#include <fmt/format.h>
#include <gen_cpp/olap_file.pb.h>
#include <algorithm>
#include <limits>
#include <shared_mutex>
#include <string>
#include <utility>
#include "common/config.h"
#include "common/consts.h"
#include "common/logging.h"
#include "olap/olap_define.h"
#include "olap/rowset/beta_rowset.h"
#include "olap/rowset/rowset_writer.h"
#include "olap/rowset/segment_v2/segment.h"
#include "olap/schema.h"
#include "olap/schema_change.h"
#include "olap/tablet_schema.h"
#include "runtime/descriptors.h"
#include "runtime/exec_env.h"
#include "runtime/load_channel_mgr.h"
#include "runtime/thread_context.h"
#include "util/doris_metrics.h"
#include "util/runtime_profile.h"
#include "util/stopwatch.hpp"
#include "vec/aggregate_functions/aggregate_function_reader.h"
#include "vec/aggregate_functions/aggregate_function_simple_factory.h"
#include "vec/columns/column.h"
#include "vec/columns/column_object.h"
#include "vec/columns/column_string.h"
#include "vec/common/assert_cast.h"
#include "vec/core/column_with_type_and_name.h"
#include "vec/data_types/data_type.h"
#include "vec/json/path_in_data.h"
#include "vec/jsonb/serialize.h"
namespace doris {
using namespace ErrorCode;
MemTable::MemTable(TabletSharedPtr tablet, Schema* schema, const TabletSchema* tablet_schema,
const std::vector<SlotDescriptor*>* slot_descs, TupleDescriptor* tuple_desc,
RowsetWriter* rowset_writer, std::shared_ptr<MowContext> mow_context,
const std::shared_ptr<MemTracker>& insert_mem_tracker,
const std::shared_ptr<MemTracker>& flush_mem_tracker)
: _tablet(std::move(tablet)),
_keys_type(_tablet->keys_type()),
_schema(schema),
_tablet_schema(tablet_schema),
_insert_mem_tracker(insert_mem_tracker),
_flush_mem_tracker(flush_mem_tracker),
_schema_size(_schema->schema_size()),
_rowset_writer(rowset_writer),
_is_first_insertion(true),
_agg_functions(schema->num_columns()),
_offsets_of_aggregate_states(schema->num_columns()),
_total_size_of_aggregate_states(0),
_mem_usage(0),
_mow_context(mow_context) {
#ifndef BE_TEST
_insert_mem_tracker_use_hook = std::make_unique<MemTracker>(
fmt::format("MemTableHookInsert:TabletId={}", std::to_string(tablet_id())),
ExecEnv::GetInstance()->load_channel_mgr()->mem_tracker());
#else
_insert_mem_tracker_use_hook = std::make_unique<MemTracker>(
fmt::format("MemTableHookInsert:TabletId={}", std::to_string(tablet_id())));
#endif
_arena = std::make_unique<vectorized::Arena>();
_vec_row_comparator = std::make_shared<RowInBlockComparator>(_schema);
// TODO: Support ZOrderComparator in the future
_vec_skip_list = std::make_unique<VecTable>(_vec_row_comparator.get(), _arena.get(),
_keys_type == KeysType::DUP_KEYS);
_init_columns_offset_by_slot_descs(slot_descs, tuple_desc);
_num_columns = _tablet_schema->num_columns();
if (_tablet_schema->is_partial_update()) {
_num_columns = _tablet_schema->partial_input_column_size();
}
}
void MemTable::_init_columns_offset_by_slot_descs(const std::vector<SlotDescriptor*>* slot_descs,
const TupleDescriptor* tuple_desc) {
for (auto slot_desc : *slot_descs) {
const auto& slots = tuple_desc->slots();
for (int j = 0; j < slots.size(); ++j) {
if (slot_desc->id() == slots[j]->id()) {
_column_offset.emplace_back(j);
break;
}
}
}
}
void MemTable::_init_agg_functions(const vectorized::Block* block) {
for (uint32_t cid = _schema->num_key_columns(); cid < _num_columns; ++cid) {
vectorized::AggregateFunctionPtr function;
if (_keys_type == KeysType::UNIQUE_KEYS && _tablet->enable_unique_key_merge_on_write()) {
// In such table, non-key column's aggregation type is NONE, so we need to construct
// the aggregate function manually.
function = vectorized::AggregateFunctionSimpleFactory::instance().get(
"replace_load", {block->get_data_type(cid)},
block->get_data_type(cid)->is_nullable());
} else {
function =
_tablet_schema->column(cid).get_aggregate_function(vectorized::AGG_LOAD_SUFFIX);
}
DCHECK(function != nullptr);
_agg_functions[cid] = function;
}
for (uint32_t cid = _schema->num_key_columns(); cid < _num_columns; ++cid) {
_offsets_of_aggregate_states[cid] = _total_size_of_aggregate_states;
_total_size_of_aggregate_states += _agg_functions[cid]->size_of_data();
// If not the last aggregate_state, we need pad it so that next aggregate_state will be aligned.
if (cid + 1 < _num_columns) {
size_t alignment_of_next_state = _agg_functions[cid + 1]->align_of_data();
/// Extend total_size to next alignment requirement
/// Add padding by rounding up 'total_size_of_aggregate_states' to be a multiplier of alignment_of_next_state.
_total_size_of_aggregate_states =
(_total_size_of_aggregate_states + alignment_of_next_state - 1) /
alignment_of_next_state * alignment_of_next_state;
}
}
}
MemTable::~MemTable() {
if (_vec_skip_list != nullptr && _keys_type != KeysType::DUP_KEYS) {
VecTable::Iterator it(_vec_skip_list.get());
for (it.SeekToFirst(); it.Valid(); it.Next()) {
// We should release agg_places here, because they are not released when a
// load is canceled.
for (size_t i = _schema->num_key_columns(); i < _num_columns; ++i) {
auto function = _agg_functions[i];
DCHECK(function != nullptr);
DCHECK(it.key()->agg_places(i) != nullptr);
function->destroy(it.key()->agg_places(i));
}
}
}
std::for_each(_row_in_blocks.begin(), _row_in_blocks.end(), std::default_delete<RowInBlock>());
_insert_mem_tracker->release(_mem_usage);
_flush_mem_tracker->set_consumption(0);
DCHECK_EQ(_insert_mem_tracker->consumption(), 0)
<< std::endl
<< MemTracker::log_usage(_insert_mem_tracker->make_snapshot());
DCHECK_EQ(_flush_mem_tracker->consumption(), 0);
}
int RowInBlockComparator::operator()(const RowInBlock* left, const RowInBlock* right) const {
return _pblock->compare_at(left->_row_pos, right->_row_pos, _schema->num_key_columns(),
*_pblock, -1);
}
void MemTable::insert(const vectorized::Block* input_block, const std::vector<int>& row_idxs,
bool is_append) {
SCOPED_CONSUME_MEM_TRACKER(_insert_mem_tracker_use_hook.get());
vectorized::Block target_block = *input_block;
if (!_tablet_schema->is_dynamic_schema()) {
// This insert may belong to a rollup tablet, rollup columns is a subset of base table
// but for dynamic table, it's need full columns, so input_block should ignore _column_offset
// of each column and avoid copy_block
target_block = input_block->copy_block(_column_offset);
}
if (_is_first_insertion) {
_is_first_insertion = false;
auto cloneBlock = target_block.clone_without_columns();
_input_mutable_block = vectorized::MutableBlock::build_mutable_block(&cloneBlock);
_vec_row_comparator->set_block(&_input_mutable_block);
_output_mutable_block = vectorized::MutableBlock::build_mutable_block(&cloneBlock);
if (_keys_type != KeysType::DUP_KEYS) {
_init_agg_functions(&target_block);
}
}
auto num_rows = row_idxs.size();
size_t cursor_in_mutableblock = _input_mutable_block.rows();
if (is_append) {
// Append the block, call insert range from
_input_mutable_block.add_rows(&target_block, 0, target_block.rows());
num_rows = target_block.rows();
} else {
_input_mutable_block.add_rows(&target_block, row_idxs.data(), row_idxs.data() + num_rows);
}
size_t input_size = target_block.allocated_bytes() * num_rows / target_block.rows();
_mem_usage += input_size;
_insert_mem_tracker->consume(input_size);
for (int i = 0; i < num_rows; i++) {
_row_in_blocks.emplace_back(new RowInBlock {cursor_in_mutableblock + i});
_insert_one_row_from_block(_row_in_blocks.back());
}
}
void MemTable::_insert_one_row_from_block(RowInBlock* row_in_block) {
_rows++;
bool overwritten = false;
if (_keys_type == KeysType::DUP_KEYS) {
// for dup keys, already store row_in_block in vector and will sort it on flush stage.
DCHECK(!overwritten) << "Duplicate key model meet overwrite in SkipList";
return;
}
bool is_exist = _vec_skip_list->Find(row_in_block, &_vec_hint);
if (is_exist) {
_merged_rows++;
_aggregate_two_row_in_block(row_in_block, _vec_hint.curr->key);
} else {
row_in_block->init_agg_places(_arena->aligned_alloc(_total_size_of_aggregate_states, 16),
_offsets_of_aggregate_states.data());
for (auto cid = _schema->num_key_columns(); cid < _num_columns; cid++) {
try {
auto col_ptr = _input_mutable_block.mutable_columns()[cid].get();
auto data = row_in_block->agg_places(cid);
_agg_functions[cid]->create(data);
_agg_functions[cid]->add(data,
const_cast<const doris::vectorized::IColumn**>(&col_ptr),
row_in_block->_row_pos, nullptr);
} catch (...) {
for (size_t i = _schema->num_key_columns(); i < cid; ++i) {
_agg_functions[i]->destroy(row_in_block->agg_places(i));
}
throw;
}
}
_vec_skip_list->InsertWithHint(row_in_block, is_exist, &_vec_hint);
}
}
void MemTable::_aggregate_two_row_in_block(RowInBlock* new_row, RowInBlock* row_in_skiplist) {
if (_tablet_schema->has_sequence_col()) {
auto sequence_idx = _tablet_schema->sequence_col_idx();
DCHECK_LT(sequence_idx, _input_mutable_block.columns());
auto col_ptr = _input_mutable_block.mutable_columns()[sequence_idx].get();
auto res = col_ptr->compare_at(row_in_skiplist->_row_pos, new_row->_row_pos, *col_ptr, -1);
// dst sequence column larger than src, don't need to update
if (res > 0) {
return;
}
// need to update the row pos in skiplist to the new row pos when has
// sequence column
row_in_skiplist->_row_pos = new_row->_row_pos;
}
// dst is non-sequence row, or dst sequence is smaller
for (uint32_t cid = _schema->num_key_columns(); cid < _num_columns; ++cid) {
auto col_ptr = _input_mutable_block.mutable_columns()[cid].get();
_agg_functions[cid]->add(row_in_skiplist->agg_places(cid),
const_cast<const doris::vectorized::IColumn**>(&col_ptr),
new_row->_row_pos, nullptr);
}
}
template <bool is_final>
void MemTable::_collect_vskiplist_results() {
if (_keys_type == KeysType::DUP_KEYS) {
if (_schema->num_key_columns() > 0) {
_collect_dup_table_with_keys();
} else {
// skip sort if the table is dup table without keys
_collect_dup_table_without_keys();
}
} else {
VecTable::Iterator it(_vec_skip_list.get());
vectorized::Block in_block = _input_mutable_block.to_block();
size_t idx = 0;
for (it.SeekToFirst(); it.Valid(); it.Next()) {
auto& block_data = in_block.get_columns_with_type_and_name();
// move key columns
for (size_t i = 0; i < _schema->num_key_columns(); ++i) {
_output_mutable_block.get_column_by_position(i)->insert_from(
*block_data[i].column.get(), it.key()->_row_pos);
}
// get value columns from agg_places
for (size_t i = _schema->num_key_columns(); i < _num_columns; ++i) {
auto function = _agg_functions[i];
auto agg_place = it.key()->agg_places(i);
auto col_ptr = _output_mutable_block.get_column_by_position(i).get();
function->insert_result_into(agg_place, *col_ptr);
if constexpr (is_final) {
function->destroy(agg_place);
} else {
function->reset(agg_place);
function->add(agg_place,
const_cast<const doris::vectorized::IColumn**>(&col_ptr), idx,
nullptr);
}
}
if constexpr (!is_final) {
// re-index the row_pos in VSkipList
it.key()->_row_pos = idx;
idx++;
}
}
if constexpr (!is_final) {
// if is not final, we collect the agg results to input_block and then continue to insert
size_t shrunked_after_agg = _output_mutable_block.allocated_bytes();
// flush will not run here, so will not duplicate `_flush_mem_tracker`
_insert_mem_tracker->consume(shrunked_after_agg - _mem_usage);
_mem_usage = shrunked_after_agg;
_input_mutable_block.swap(_output_mutable_block);
//TODO(weixang):opt here.
std::unique_ptr<vectorized::Block> empty_input_block =
in_block.create_same_struct_block(0);
_output_mutable_block =
vectorized::MutableBlock::build_mutable_block(empty_input_block.get());
_output_mutable_block.clear_column_data();
}
}
if (is_final) {
_vec_skip_list.reset();
}
}
void MemTable::_collect_dup_table_with_keys() {
vectorized::Block in_block = _input_mutable_block.to_block();
vectorized::MutableBlock mutable_block =
vectorized::MutableBlock::build_mutable_block(&in_block);
_vec_row_comparator->set_block(&mutable_block);
std::sort(_row_in_blocks.begin(), _row_in_blocks.end(),
[this](const RowInBlock* l, const RowInBlock* r) -> bool {
auto value = (*(this->_vec_row_comparator))(l, r);
if (value == 0) {
return l->_row_pos > r->_row_pos;
} else {
return value < 0;
}
});
std::vector<int> row_pos_vec;
DCHECK(in_block.rows() <= std::numeric_limits<int>::max());
row_pos_vec.reserve(in_block.rows());
for (int i = 0; i < _row_in_blocks.size(); i++) {
row_pos_vec.emplace_back(_row_in_blocks[i]->_row_pos);
}
_output_mutable_block.add_rows(&in_block, row_pos_vec.data(),
row_pos_vec.data() + in_block.rows());
}
void MemTable::_collect_dup_table_without_keys() {
_output_mutable_block.swap(_input_mutable_block);
}
void MemTable::shrink_memtable_by_agg() {
SCOPED_CONSUME_MEM_TRACKER(_insert_mem_tracker_use_hook.get());
if (_keys_type == KeysType::DUP_KEYS) {
return;
}
_collect_vskiplist_results<false>();
}
bool MemTable::need_flush() const {
auto max_size = config::write_buffer_size;
if (_tablet_schema->is_partial_update()) {
auto update_columns_size = _tablet_schema->partial_input_column_size();
max_size = max_size * update_columns_size / _tablet_schema->num_columns();
max_size = max_size > 1048576 ? max_size : 1048576;
}
return memory_usage() >= max_size;
}
bool MemTable::need_agg() const {
if (_keys_type == KeysType::AGG_KEYS) {
auto max_size = config::write_buffer_size_for_agg;
if (_tablet_schema->is_partial_update()) {
auto update_columns_size = _tablet_schema->partial_input_column_size();
max_size = max_size * update_columns_size / _tablet_schema->num_columns();
max_size = max_size > 1048576 ? max_size : 1048576;
}
return memory_usage() >= max_size;
}
return false;
}
Status MemTable::_generate_delete_bitmap(int64_t atomic_num_segments_before_flush,
int64_t atomic_num_segments_after_flush) {
// generate delete bitmap, build a tmp rowset and load recent segment
if (!_tablet->enable_unique_key_merge_on_write()) {
return Status::OK();
}
auto rowset = _rowset_writer->build_tmp();
auto beta_rowset = reinterpret_cast<BetaRowset*>(rowset.get());
std::vector<segment_v2::SegmentSharedPtr> segments;
if (atomic_num_segments_before_flush >= atomic_num_segments_after_flush) {
return Status::OK();
}
RETURN_IF_ERROR(beta_rowset->load_segments(atomic_num_segments_before_flush,
atomic_num_segments_after_flush, &segments));
std::shared_lock meta_rlock(_tablet->get_header_lock());
// tablet is under alter process. The delete bitmap will be calculated after conversion.
if (_tablet->tablet_state() == TABLET_NOTREADY &&
SchemaChangeHandler::tablet_in_converting(_tablet->tablet_id())) {
return Status::OK();
}
RETURN_IF_ERROR(_tablet->calc_delete_bitmap(rowset, segments, &_mow_context->rowset_ids,
_mow_context->delete_bitmap,
_mow_context->max_version));
return Status::OK();
}
Status MemTable::flush() {
VLOG_CRITICAL << "begin to flush memtable for tablet: " << tablet_id()
<< ", memsize: " << memory_usage() << ", rows: " << _rows;
int64_t duration_ns = 0;
// For merge_on_write table, it must get all segments in this flush.
// The id of new segment is set by the _num_segment of beta_rowset_writer,
// and new segment ids is between [atomic_num_segments_before_flush, atomic_num_segments_after_flush),
// and use the ids to load segment data file for calc delete bitmap.
int64_t atomic_num_segments_before_flush = _rowset_writer->get_atomic_num_segment();
RETURN_IF_ERROR(_do_flush(duration_ns));
int64_t atomic_num_segments_after_flush = _rowset_writer->get_atomic_num_segment();
if (!_tablet_schema->is_partial_update()) {
RETURN_IF_ERROR(_generate_delete_bitmap(atomic_num_segments_before_flush,
atomic_num_segments_after_flush));
}
DorisMetrics::instance()->memtable_flush_total->increment(1);
DorisMetrics::instance()->memtable_flush_duration_us->increment(duration_ns / 1000);
VLOG_CRITICAL << "after flush memtable for tablet: " << tablet_id()
<< ", flushsize: " << _flush_size;
return Status::OK();
}
Status MemTable::_do_flush(int64_t& duration_ns) {
SCOPED_CONSUME_MEM_TRACKER(_flush_mem_tracker);
SCOPED_RAW_TIMER(&duration_ns);
_collect_vskiplist_results<true>();
vectorized::Block block = _output_mutable_block.to_block();
if (_tablet_schema->is_dynamic_schema()) {
// Unfold variant column
unfold_variant_column(block);
}
RETURN_IF_ERROR(_rowset_writer->flush_single_memtable(&block, &_flush_size));
return Status::OK();
}
Status MemTable::close() {
return flush();
}
void MemTable::unfold_variant_column(vectorized::Block& block) {
if (block.rows() == 0) {
return;
}
vectorized::ColumnWithTypeAndName* variant_column =
block.try_get_by_name(BeConsts::DYNAMIC_COLUMN_NAME);
if (!variant_column) {
return;
}
// remove it
vectorized::ColumnObject& object_column =
assert_cast<vectorized::ColumnObject&>(variant_column->column->assume_mutable_ref());
// extend
for (auto& entry : object_column.get_subcolumns()) {
if (entry->path.get_path() == vectorized::ColumnObject::COLUMN_NAME_DUMMY) {
continue;
}
block.insert({entry->data.get_finalized_column().get_ptr(),
entry->data.get_least_common_type(), entry->path.get_path()});
}
block.erase(BeConsts::DYNAMIC_COLUMN_NAME);
}
void MemTable::serialize_block_to_row_column(vectorized::Block& block) {
if (block.rows() == 0) {
return;
}
MonotonicStopWatch watch;
watch.start();
// find row column id
int row_column_id = 0;
for (int i = 0; i < _num_columns; ++i) {
if (_tablet_schema->column(i).is_row_store_column()) {
row_column_id = i;
break;
}
}
if (row_column_id == 0) {
return;
}
vectorized::ColumnString* row_store_column =
static_cast<vectorized::ColumnString*>(block.get_by_position(row_column_id)
.column->assume_mutable_ref()
.assume_mutable()
.get());
row_store_column->clear();
vectorized::JsonbSerializeUtil::block_to_jsonb(*_tablet_schema, block, *row_store_column,
_num_columns);
VLOG_DEBUG << "serialize , num_rows:" << block.rows() << ", row_column_id:" << row_column_id
<< ", total_byte_size:" << block.allocated_bytes() << ", serialize_cost(us)"
<< watch.elapsed_time() / 1000;
}
} // namespace doris
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