mirror of https://gitee.com/bigwinds/arangodb
308 lines
10 KiB
C++
308 lines
10 KiB
C++
////////////////////////////////////////////////////////////////////////////////
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/// @brief AggregateNode
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///
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/// @file
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///
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/// DISCLAIMER
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///
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/// Copyright 2010-2014 triagens GmbH, Cologne, Germany
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///
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/// Licensed under the Apache License, Version 2.0 (the "License");
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/// you may not use this file except in compliance with the License.
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/// You may obtain a copy of the License at
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///
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/// http://www.apache.org/licenses/LICENSE-2.0
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///
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/// Unless required by applicable law or agreed to in writing, software
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/// distributed under the License is distributed on an "AS IS" BASIS,
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/// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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/// See the License for the specific language governing permissions and
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/// limitations under the License.
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///
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/// Copyright holder is triAGENS GmbH, Cologne, Germany
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///
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/// @author Jan Steemann
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/// @author Copyright 2014, triagens GmbH, Cologne, Germany
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////////////////////////////////////////////////////////////////////////////////
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#include "AggregateNode.h"
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#include "Aql/Ast.h"
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#include "Aql/ExecutionPlan.h"
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#include "Aql/WalkerWorker.h"
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using namespace std;
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using namespace triagens::basics;
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using namespace triagens::aql;
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// -----------------------------------------------------------------------------
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// --SECTION-- methods of AggregateNode
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// -----------------------------------------------------------------------------
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AggregateNode::AggregateNode (ExecutionPlan* plan,
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triagens::basics::Json const& base,
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Variable const* expressionVariable,
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Variable const* outVariable,
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std::vector<Variable const*> const& keepVariables,
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std::unordered_map<VariableId, std::string const> const& variableMap,
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std::vector<std::pair<Variable const*, Variable const*>> const& aggregateVariables,
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bool count,
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bool isDistinctCommand)
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: ExecutionNode(plan, base),
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_options(base),
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_aggregateVariables(aggregateVariables),
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_expressionVariable(expressionVariable),
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_outVariable(outVariable),
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_keepVariables(keepVariables),
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_variableMap(variableMap),
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_count(count),
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_isDistinctCommand(isDistinctCommand),
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_specialized(false) {
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}
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////////////////////////////////////////////////////////////////////////////////
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/// @brief toJson, for AggregateNode
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////////////////////////////////////////////////////////////////////////////////
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void AggregateNode::toJsonHelper (triagens::basics::Json& nodes,
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TRI_memory_zone_t* zone,
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bool verbose) const {
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triagens::basics::Json json(ExecutionNode::toJsonHelperGeneric(nodes, zone, verbose)); // call base class method
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if (json.isEmpty()) {
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return;
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}
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triagens::basics::Json values(triagens::basics::Json::Array, _aggregateVariables.size());
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for (auto it = _aggregateVariables.begin(); it != _aggregateVariables.end(); ++it) {
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triagens::basics::Json variable(triagens::basics::Json::Object);
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variable("outVariable", (*it).first->toJson())
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("inVariable", (*it).second->toJson());
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values(variable);
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}
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json("aggregates", values);
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// expression variable might be empty
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if (_expressionVariable != nullptr) {
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json("expressionVariable", _expressionVariable->toJson());
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}
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// output variable might be empty
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if (_outVariable != nullptr) {
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json("outVariable", _outVariable->toJson());
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}
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if (! _keepVariables.empty()) {
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triagens::basics::Json values(triagens::basics::Json::Array, _keepVariables.size());
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for (auto it = _keepVariables.begin(); it != _keepVariables.end(); ++it) {
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triagens::basics::Json variable(triagens::basics::Json::Object);
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variable("variable", (*it)->toJson());
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values(variable);
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}
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json("keepVariables", values);
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}
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json("count", triagens::basics::Json(_count));
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json("isDistinctCommand", triagens::basics::Json(_isDistinctCommand));
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json("specialized", triagens::basics::Json(_specialized));
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_options.toJson(json, zone);
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// And add it:
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nodes(json);
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}
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////////////////////////////////////////////////////////////////////////////////
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/// @brief clone ExecutionNode recursively
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////////////////////////////////////////////////////////////////////////////////
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ExecutionNode* AggregateNode::clone (ExecutionPlan* plan,
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bool withDependencies,
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bool withProperties) const {
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auto outVariable = _outVariable;
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auto expressionVariable = _expressionVariable;
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auto aggregateVariables = _aggregateVariables;
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if (withProperties) {
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if (expressionVariable != nullptr) {
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expressionVariable = plan->getAst()->variables()->createVariable(expressionVariable);
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}
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if (outVariable != nullptr) {
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outVariable = plan->getAst()->variables()->createVariable(outVariable);
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}
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// need to re-create all variables
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aggregateVariables.clear();
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for (auto& it : _aggregateVariables) {
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auto out = plan->getAst()->variables()->createVariable(it.first);
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auto in = plan->getAst()->variables()->createVariable(it.second);
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aggregateVariables.emplace_back(std::make_pair(out, in));
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}
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}
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auto c = new AggregateNode(
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plan,
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_id,
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_options,
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aggregateVariables,
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expressionVariable,
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outVariable,
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_keepVariables,
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_variableMap,
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_count,
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_isDistinctCommand
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);
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// specialize the cloned node
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if (isSpecialized()) {
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c->specialized();
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}
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cloneHelper(c, plan, withDependencies, withProperties);
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return static_cast<ExecutionNode*>(c);
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}
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////////////////////////////////////////////////////////////////////////////////
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/// @brief getVariablesUsedHere
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////////////////////////////////////////////////////////////////////////////////
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struct UserVarFinder final : public WalkerWorker<ExecutionNode> {
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explicit UserVarFinder (int mindepth)
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: mindepth(mindepth), depth(-1) {
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}
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~UserVarFinder () {
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}
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std::vector<Variable const*> userVars;
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int mindepth; // minimal depth to consider
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int depth;
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bool enterSubquery (ExecutionNode*, ExecutionNode*) override final {
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return false;
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}
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void after (ExecutionNode* en) override final {
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if (en->getType() == ExecutionNode::SINGLETON) {
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depth = 0;
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}
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else if (en->getType() == ExecutionNode::ENUMERATE_COLLECTION ||
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en->getType() == ExecutionNode::INDEX ||
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en->getType() == ExecutionNode::ENUMERATE_LIST ||
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en->getType() == ExecutionNode::TRAVERSAL ||
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en->getType() == ExecutionNode::AGGREGATE) {
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depth += 1;
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}
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// Now depth is set correct for this node.
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if (depth >= mindepth) {
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auto const& vars = en->getVariablesSetHere();
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for (auto const& v : vars) {
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if (v->isUserDefined()) {
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userVars.emplace_back(v);
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}
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}
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}
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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/// @brief getVariablesUsedHere, returning a vector
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////////////////////////////////////////////////////////////////////////////////
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std::vector<Variable const*> AggregateNode::getVariablesUsedHere () const {
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std::unordered_set<Variable const*> v;
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// actual work is done by that method
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getVariablesUsedHere(v);
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// copy result into vector
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std::vector<Variable const*> vv;
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vv.reserve(v.size());
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for (auto const& x : v) {
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vv.emplace_back(x);
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}
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return vv;
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}
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////////////////////////////////////////////////////////////////////////////////
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/// @brief getVariablesUsedHere, modifying the set in-place
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////////////////////////////////////////////////////////////////////////////////
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void AggregateNode::getVariablesUsedHere (std::unordered_set<Variable const*>& vars) const {
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for (auto const& p : _aggregateVariables) {
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vars.emplace(p.second);
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}
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if (_expressionVariable != nullptr) {
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vars.emplace(_expressionVariable);
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}
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if (_outVariable != nullptr && ! _count) {
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if (_keepVariables.empty()) {
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// Here we have to find all user defined variables in this query
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// amongst our dependencies:
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UserVarFinder finder(1);
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auto myselfAsNonConst = const_cast<AggregateNode*>(this);
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myselfAsNonConst->walk(&finder);
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if (finder.depth == 1) {
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// we are top level, let's run again with mindepth = 0
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finder.userVars.clear();
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finder.mindepth = 0;
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finder.depth = -1;
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finder.reset();
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myselfAsNonConst->walk(&finder);
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}
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for (auto& x : finder.userVars) {
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vars.emplace(x);
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}
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}
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else {
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for (auto& x : _keepVariables) {
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vars.emplace(x);
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}
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}
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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/// @brief estimateCost
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////////////////////////////////////////////////////////////////////////////////
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double AggregateNode::estimateCost (size_t& nrItems) const {
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double depCost = _dependencies.at(0)->getCost(nrItems);
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// As in the FilterNode case, we are pessimistic here by not reducing the
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// nrItems much, since the worst case for COLLECT is to return as many items
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// as there are input items. In any case, we have to look at all incoming
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// items, and in particular in the COLLECT ... INTO ... case, we have
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// to actually hand on all data anyway, albeit not as separate items.
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// Nevertheless, the optimizer does not do much with AggregateNodes
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// and thus this potential overestimation does not really matter.
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if (_count && _aggregateVariables.empty()) {
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// we are known to only produce a single output row
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nrItems = 1;
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}
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else {
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// we do not know how many rows the COLLECT with produce...
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// the worst case is that there will be as many output rows as input rows
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if (nrItems >= 10) {
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// we assume that the collect will reduce the number of results at least somewhat
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nrItems = static_cast<size_t>(nrItems * 0.80);
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}
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}
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return depCost + nrItems;
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}
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// Local Variables:
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// mode: outline-minor
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// outline-regexp: "^\\(/// @brief\\|/// {@inheritDoc}\\|/// @addtogroup\\|// --SECTION--\\|/// @\\}\\)"
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// End:
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