Files
doris/be/src/exec/topn_node.cpp
HuangWei 10f822eb43 [MemTracker] make all MemTrackers shared (#4135)
We make all MemTrackers shared, in order to show MemTracker real-time consumptions on the web.
As follows:
1. nearly all MemTracker raw ptr -> shared_ptr
2. Use CreateTracker() to create new MemTracker(in order to add itself to its parent)
3. RowBatch & MemPool still use raw ptrs of MemTracker, it's easy to ensure RowBatch & MemPool destructor exec 
     before MemTracker's destructor. So we don't change these code.
4. MemTracker can use RuntimeProfile's counter to calc consumption. So RuntimeProfile's counter need to be shared 
    too. We add a shared counter pool to store the shared counter, don't change other counters of RuntimeProfile.
Note that, this PR doesn't change the MemTracker tree structure. So there still have some orphan trackers, e.g. RowBlockV2's MemTracker. If you find some shared MemTrackers are little memory consumption & too time-consuming, you could make them be the orphan, then it's fine to use the raw ptr.
2020-07-31 21:57:21 +08:00

262 lines
9.5 KiB
C++

// 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 "exec/topn_node.h"
#include <sstream>
#include "exprs/expr.h"
#include "gen_cpp/Exprs_types.h"
#include "gen_cpp/PlanNodes_types.h"
#include "runtime/descriptors.h"
#include "runtime/mem_pool.h"
#include "runtime/raw_value.h"
#include "runtime/row_batch.h"
#include "runtime/runtime_state.h"
#include "runtime/tuple.h"
#include "runtime/tuple_row.h"
#include "util/runtime_profile.h"
#include "util/tuple_row_compare.h"
#include <gperftools/profiler.h>
namespace doris {
TopNNode::TopNNode(ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs) :
ExecNode(pool, tnode, descs),
_offset(tnode.sort_node.__isset.offset ? tnode.sort_node.offset : 0),
_materialized_tuple_desc(NULL),
_tuple_row_less_than(NULL),
_tuple_pool(NULL),
_num_rows_skipped(0),
_priority_queue(NULL) {
}
TopNNode::~TopNNode() {
}
Status TopNNode::init(const TPlanNode& tnode, RuntimeState* state) {
RETURN_IF_ERROR(ExecNode::init(tnode, state));
RETURN_IF_ERROR(_sort_exec_exprs.init(tnode.sort_node.sort_info, _pool));
_is_asc_order = tnode.sort_node.sort_info.is_asc_order;
_nulls_first = tnode.sort_node.sort_info.nulls_first;
DCHECK_EQ(_conjuncts.size(), 0) << "TopNNode should never have predicates to evaluate.";
_abort_on_default_limit_exceeded = tnode.sort_node.is_default_limit;
return Status::OK();
}
Status TopNNode::prepare(RuntimeState* state) {
SCOPED_TIMER(_runtime_profile->total_time_counter());
RETURN_IF_ERROR(ExecNode::prepare(state));
_tuple_pool.reset(new MemPool(mem_tracker().get()));
RETURN_IF_ERROR(_sort_exec_exprs.prepare(
state, child(0)->row_desc(), _row_descriptor, expr_mem_tracker()));
// AddExprCtxsToFree(_sort_exec_exprs);
_tuple_row_less_than.reset(
new TupleRowComparator(_sort_exec_exprs, _is_asc_order, _nulls_first));
_abort_on_default_limit_exceeded = _abort_on_default_limit_exceeded &&
state->abort_on_default_limit_exceeded();
_materialized_tuple_desc = _row_descriptor.tuple_descriptors()[0];
return Status::OK();
}
Status TopNNode::open(RuntimeState* state) {
SCOPED_TIMER(_runtime_profile->total_time_counter());
RETURN_IF_ERROR(ExecNode::open(state));
RETURN_IF_CANCELLED(state);
RETURN_IF_ERROR(state->check_query_state("Top n, before open."));
RETURN_IF_ERROR(_sort_exec_exprs.open(state));
// Avoid creating them after every Reset()/Open().
// TODO: For some reason initializing _priority_queue in Prepare() causes a 30% perf
// regression. Why??
if (_priority_queue.get() == NULL) {
_priority_queue.reset(
new std::priority_queue<Tuple*, std::vector<Tuple*>, TupleRowComparator>(
*_tuple_row_less_than));
}
// Allocate memory for a temporary tuple.
_tmp_tuple = reinterpret_cast<Tuple*>(
_tuple_pool->allocate(_materialized_tuple_desc->byte_size()));
RETURN_IF_ERROR(child(0)->open(state));
// Limit of 0, no need to fetch anything from children.
if (_limit != 0) {
RowBatch batch(child(0)->row_desc(), state->batch_size(), mem_tracker().get());
bool eos = false;
do {
batch.reset();
RETURN_IF_ERROR(child(0)->get_next(state, &batch, &eos));
if (_abort_on_default_limit_exceeded && child(0)->rows_returned() > _limit) {
return Status::InternalError("DEFAULT_ORDER_BY_LIMIT has been exceeded.");
}
for (int i = 0; i < batch.num_rows(); ++i) {
insert_tuple_row(batch.get_row(i));
}
RETURN_IF_CANCELLED(state);
RETURN_IF_ERROR(state->check_query_state("Top n, while getting next from child 0."));
} while (!eos);
}
DCHECK_LE(_priority_queue->size(), _offset + _limit);
prepare_for_output();
// Unless we are inside a subplan expecting to call open()/get_next() on the child
// again, the child can be closed at this point.
// if (!is_in_subplan()) {
child(0)->close(state);
// }
return Status::OK();
}
Status TopNNode::get_next(RuntimeState* state, RowBatch* row_batch, bool* eos) {
SCOPED_TIMER(_runtime_profile->total_time_counter());
RETURN_IF_ERROR(exec_debug_action(TExecNodePhase::GETNEXT));
RETURN_IF_CANCELLED(state);
RETURN_IF_ERROR(state->check_query_state("Top n, before moving result to row_batch."));
while (!row_batch->at_capacity() && (_get_next_iter != _sorted_top_n.end())) {
if (_num_rows_skipped < _offset) {
++_get_next_iter;
_num_rows_skipped++;
continue;
}
int row_idx = row_batch->add_row();
TupleRow* dst_row = row_batch->get_row(row_idx);
Tuple* src_tuple = *_get_next_iter;
TupleRow* src_row = reinterpret_cast<TupleRow*>(&src_tuple);
row_batch->copy_row(src_row, dst_row);
++_get_next_iter;
row_batch->commit_last_row();
++_num_rows_returned;
COUNTER_SET(_rows_returned_counter, _num_rows_returned);
}
if (VLOG_ROW_IS_ON) {
VLOG_ROW << "TOPN-node output row: " << row_batch->to_string();
}
*eos = _get_next_iter == _sorted_top_n.end();
// Transfer ownership of tuple data to output batch.
// TODO: To improve performance for small inputs when this node is run multiple times
// inside a subplan, we might choose to only selectively transfer, e.g., when the
// block(s) in the pool are all full or when the pool has reached a certain size.
if (*eos) {
row_batch->tuple_data_pool()->acquire_data(_tuple_pool.get(), false);
}
return Status::OK();
}
Status TopNNode::close(RuntimeState* state) {
if (is_closed()) {
return Status::OK();
}
if (_tuple_pool.get() != NULL) {
_tuple_pool->free_all();
}
_sort_exec_exprs.close(state);
return ExecNode::close(state);
}
// Insert if either not at the limit or it's a new TopN tuple_row
void TopNNode::insert_tuple_row(TupleRow* input_row) {
Tuple* insert_tuple = NULL;
if (_priority_queue->size() < _offset + _limit) {
insert_tuple = reinterpret_cast<Tuple*>(
_tuple_pool->allocate(_materialized_tuple_desc->byte_size()));
insert_tuple->materialize_exprs<false>(input_row, *_materialized_tuple_desc,
_sort_exec_exprs.sort_tuple_slot_expr_ctxs(), _tuple_pool.get(), NULL, NULL);
} else {
DCHECK(!_priority_queue->empty());
Tuple* top_tuple = _priority_queue->top();
_tmp_tuple->materialize_exprs<false>(input_row, *_materialized_tuple_desc,
_sort_exec_exprs.sort_tuple_slot_expr_ctxs(), NULL, NULL, NULL);
if ((*_tuple_row_less_than)(_tmp_tuple, top_tuple)) {
// TODO: DeepCopy will allocate new buffers for the string data. This needs
// to be fixed to use a freelist
_tmp_tuple->deep_copy(top_tuple, *_materialized_tuple_desc, _tuple_pool.get());
insert_tuple = top_tuple;
_priority_queue->pop();
}
}
if (insert_tuple != NULL) {
_priority_queue->push(insert_tuple);
}
}
// Reverse the order of the tuples in the priority queue
void TopNNode::prepare_for_output() {
_sorted_top_n.resize(_priority_queue->size());
int index = _sorted_top_n.size() - 1;
while (_priority_queue->size() > 0) {
Tuple* tuple = _priority_queue->top();
_priority_queue->pop();
_sorted_top_n[index] = tuple;
--index;
}
_get_next_iter = _sorted_top_n.begin();
}
void TopNNode::debug_string(int indentation_level, std::stringstream* out) const {
*out << std::string(indentation_level * 2, ' ');
*out << "TopNNode("
// << " ordering_exprs=" << Expr::debug_string(_lhs_ordering_expr_ctxs)
<< Expr::debug_string(_sort_exec_exprs.lhs_ordering_expr_ctxs())
<< " sort_order=[";
for (int i = 0; i < _is_asc_order.size(); ++i) {
*out << (i > 0 ? " " : "")
<< (_is_asc_order[i] ? "asc" : "desc")
<< " nulls " << (_nulls_first[i] ? "first" : "last");
}
*out << "]";
ExecNode::debug_string(indentation_level, out);
*out << ")";
}
void TopNNode::push_down_predicate(
RuntimeState *state, std::list<ExprContext*> *expr_ctxs) {
std::list<ExprContext*>::iterator iter = expr_ctxs->begin();
while (iter != expr_ctxs->end()) {
if ((*iter)->root()->is_bound(&_tuple_ids)) {
// LOG(INFO) << "push down success expr is " << (*iter)->debug_string();
// (*iter)->get_child(0)->prepare(state, row_desc());
(*iter)->prepare(state, row_desc(), _expr_mem_tracker);
(*iter)->open(state);
_conjunct_ctxs.push_back(*iter);
iter = expr_ctxs->erase(iter);
} else {
++iter;
}
}
}
}