141d9b3bb8
Reviewers: buda, florijan Reviewed By: buda, florijan Subscribers: mislav.bradac, pullbot Differential Revision: https://phabricator.memgraph.io/D392
598 lines
21 KiB
C++
598 lines
21 KiB
C++
//
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// Copyright 2017 Memgraph
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// Created by Florijan Stamenkovic on 14.03.17.
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//
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#include <algorithm>
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#include <iterator>
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#include <memory>
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#include <vector>
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#include "gmock/gmock.h"
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#include "gtest/gtest.h"
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#include "communication/result_stream_faker.hpp"
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#include "dbms/dbms.hpp"
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#include "query/context.hpp"
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#include "query/exceptions.hpp"
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#include "query/plan/operator.hpp"
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#include "query_plan_common.hpp"
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using namespace query;
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using namespace query::plan;
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using testing::UnorderedElementsAre;
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using query::test_common::ToInt64List;
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TEST(QueryPlan, Accumulate) {
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// simulate the following two query execution on an empty db
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// CREATE ({x:0})-[:T]->({x:0})
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// MATCH (n)--(m) SET n.x = n.x + 1, m.x = m.x + 1 RETURN n.x, m.x
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// without accumulation we expected results to be [[1, 1], [2, 2]]
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// with accumulation we expect them to be [[2, 2], [2, 2]]
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auto check = [&](bool accumulate) {
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Dbms dbms;
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auto dba = dbms.active();
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auto prop = dba->property("x");
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auto v1 = dba->insert_vertex();
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v1.PropsSet(prop, 0);
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auto v2 = dba->insert_vertex();
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v2.PropsSet(prop, 0);
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dba->insert_edge(v1, v2, dba->edge_type("T"));
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dba->advance_command();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto r_m = MakeExpand(storage, symbol_table, n.op_, n.sym_, "r",
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EdgeAtom::Direction::BOTH, false, "m", false);
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auto one = LITERAL(1);
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auto n_p = PROPERTY_LOOKUP("n", prop);
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symbol_table[*n_p->expression_] = n.sym_;
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auto set_n_p =
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std::make_shared<plan::SetProperty>(r_m.op_, n_p, ADD(n_p, one));
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auto m_p = PROPERTY_LOOKUP("m", prop);
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symbol_table[*m_p->expression_] = r_m.node_sym_;
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auto set_m_p =
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std::make_shared<plan::SetProperty>(set_n_p, m_p, ADD(m_p, one));
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std::shared_ptr<LogicalOperator> last_op = set_m_p;
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if (accumulate) {
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last_op = std::make_shared<Accumulate>(
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last_op, std::vector<Symbol>{n.sym_, r_m.node_sym_});
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}
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auto n_p_ne = NEXPR("n.p", n_p);
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symbol_table[*n_p_ne] = symbol_table.CreateSymbol("n_p_ne", true);
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auto m_p_ne = NEXPR("m.p", m_p);
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symbol_table[*m_p_ne] = symbol_table.CreateSymbol("m_p_ne", true);
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auto produce = MakeProduce(last_op, n_p_ne, m_p_ne);
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auto results = CollectProduce(produce.get(), symbol_table, *dba);
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std::vector<int> results_data;
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for (const auto &row : results)
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for (const auto &column : row)
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results_data.emplace_back(column.Value<int64_t>());
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if (accumulate)
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EXPECT_THAT(results_data, testing::ElementsAre(2, 2, 2, 2));
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else
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EXPECT_THAT(results_data, testing::ElementsAre(1, 1, 2, 2));
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};
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check(false);
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check(true);
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}
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TEST(QueryPlan, AccumulateAdvance) {
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// we simulate 'CREATE (n) WITH n AS n MATCH (m) RETURN m'
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// to get correct results we need to advance the command
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auto check = [&](bool advance) {
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Dbms dbms;
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auto dba = dbms.active();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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auto node = NODE("n");
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auto sym_n = symbol_table.CreateSymbol("n", true);
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symbol_table[*node->identifier_] = sym_n;
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auto create = std::make_shared<CreateNode>(node, nullptr);
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auto accumulate = std::make_shared<Accumulate>(
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create, std::vector<Symbol>{sym_n}, advance);
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auto match = MakeScanAll(storage, symbol_table, "m", accumulate);
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EXPECT_EQ(advance ? 1 : 0, PullAll(match.op_, *dba, symbol_table));
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};
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check(false);
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check(true);
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}
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std::shared_ptr<Produce> MakeAggregationProduce(
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std::shared_ptr<LogicalOperator> input, SymbolTable &symbol_table,
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AstTreeStorage &storage, const std::vector<Expression *> aggr_inputs,
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const std::vector<Aggregation::Op> aggr_ops,
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const std::vector<Expression *> group_by_exprs,
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const std::vector<Symbol> remember) {
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// prepare all the aggregations
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std::vector<Aggregate::Element> aggregates;
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std::vector<NamedExpression *> named_expressions;
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auto aggr_inputs_it = aggr_inputs.begin();
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for (auto aggr_op : aggr_ops) {
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// TODO change this from using IDENT to using AGGREGATION
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// once AGGREGATION is handled properly in ExpressionEvaluation
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auto named_expr = NEXPR("", IDENT("aggregation"));
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named_expressions.push_back(named_expr);
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symbol_table[*named_expr->expression_] =
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symbol_table.CreateSymbol("aggregation", true);
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symbol_table[*named_expr] =
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symbol_table.CreateSymbol("named_expression", true);
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aggregates.emplace_back(*aggr_inputs_it++, aggr_op,
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symbol_table[*named_expr->expression_]);
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}
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// Produce will also evaluate group_by expressions
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// and return them after the aggregations
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for (auto group_by_expr : group_by_exprs) {
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auto named_expr = NEXPR("", group_by_expr);
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named_expressions.push_back(named_expr);
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symbol_table[*named_expr] =
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symbol_table.CreateSymbol("named_expression", true);
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}
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auto aggregation =
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std::make_shared<Aggregate>(input, aggregates, group_by_exprs, remember);
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return std::make_shared<Produce>(aggregation, named_expressions);
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}
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/** Test fixture for all the aggregation ops in one return */
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class QueryPlanAggregateOps : public ::testing::Test {
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protected:
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Dbms dbms;
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std::unique_ptr<GraphDbAccessor> dba = dbms.active();
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GraphDbTypes::Property prop = dba->property("prop");
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AstTreeStorage storage;
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SymbolTable symbol_table;
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void AddData() {
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// setup is several nodes most of which have an int property set
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// we will take the sum, avg, min, max and count
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// we won't group by anything
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dba->insert_vertex().PropsSet(prop, 5);
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dba->insert_vertex().PropsSet(prop, 7);
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dba->insert_vertex().PropsSet(prop, 12);
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// a missing property (null) gets ignored by all aggregations except
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// COUNT(*)
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dba->insert_vertex();
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dba->advance_command();
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}
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auto AggregationResults(bool with_group_by,
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std::vector<Aggregation::Op> ops = {
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Aggregation::Op::COUNT, Aggregation::Op::COUNT,
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Aggregation::Op::MIN, Aggregation::Op::MAX,
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Aggregation::Op::SUM, Aggregation::Op::AVG,
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Aggregation::Op::COLLECT}) {
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// match all nodes and perform aggregations
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_p = PROPERTY_LOOKUP("n", prop);
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symbol_table[*n_p->expression_] = n.sym_;
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std::vector<Expression *> aggregation_expressions(7, n_p);
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std::vector<Expression *> group_bys;
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if (with_group_by) group_bys.push_back(n_p);
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aggregation_expressions[0] = nullptr;
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auto produce =
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MakeAggregationProduce(n.op_, symbol_table, storage,
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aggregation_expressions, ops, group_bys, {});
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return CollectProduce(produce.get(), symbol_table, *dba);
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}
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};
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TEST_F(QueryPlanAggregateOps, WithData) {
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AddData();
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auto results = AggregationResults(false);
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ASSERT_EQ(results.size(), 1);
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ASSERT_EQ(results[0].size(), 7);
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// count(*)
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ASSERT_EQ(results[0][0].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][0].Value<int64_t>(), 4);
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// count
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ASSERT_EQ(results[0][1].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][1].Value<int64_t>(), 3);
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// min
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ASSERT_EQ(results[0][2].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][2].Value<int64_t>(), 5);
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// max
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ASSERT_EQ(results[0][3].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][3].Value<int64_t>(), 12);
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// sum
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ASSERT_EQ(results[0][4].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][4].Value<int64_t>(), 24);
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// avg
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ASSERT_EQ(results[0][5].type(), TypedValue::Type::Double);
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EXPECT_FLOAT_EQ(results[0][5].Value<double>(), 24 / 3.0);
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// collect
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ASSERT_EQ(results[0][6].type(), TypedValue::Type::List);
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EXPECT_THAT(ToInt64List(results[0][6]), UnorderedElementsAre(5, 7, 12));
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}
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TEST_F(QueryPlanAggregateOps, WithoutDataWithGroupBy) {
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{
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auto results = AggregationResults(true, {Aggregation::Op::COUNT});
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EXPECT_EQ(results.size(), 0);
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}
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{
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auto results = AggregationResults(true, {Aggregation::Op::SUM});
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EXPECT_EQ(results.size(), 0);
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}
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{
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auto results = AggregationResults(true, {Aggregation::Op::AVG});
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EXPECT_EQ(results.size(), 0);
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}
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{
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auto results = AggregationResults(true, {Aggregation::Op::MIN});
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EXPECT_EQ(results.size(), 0);
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}
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{
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auto results = AggregationResults(true, {Aggregation::Op::MAX});
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EXPECT_EQ(results.size(), 0);
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}
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{
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auto results = AggregationResults(true, {Aggregation::Op::COLLECT});
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EXPECT_EQ(results.size(), 0);
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}
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}
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TEST_F(QueryPlanAggregateOps, WithoutDataWithoutGroupBy) {
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auto results = AggregationResults(false);
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ASSERT_EQ(results.size(), 1);
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ASSERT_EQ(results[0].size(), 7);
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// count(*)
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ASSERT_EQ(results[0][0].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][0].Value<int64_t>(), 0);
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// count
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ASSERT_EQ(results[0][1].type(), TypedValue::Type::Int);
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EXPECT_EQ(results[0][1].Value<int64_t>(), 0);
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// min
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EXPECT_TRUE(results[0][2].IsNull());
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// max
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EXPECT_TRUE(results[0][3].IsNull());
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// sum
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EXPECT_TRUE(results[0][4].IsNull());
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// avg
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EXPECT_TRUE(results[0][5].IsNull());
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// collect
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ASSERT_EQ(results[0][6].type(), TypedValue::Type::List);
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EXPECT_THAT(ToInt64List(results[0][6]), UnorderedElementsAre());
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}
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TEST(QueryPlan, AggregateGroupByValues) {
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// tests that distinct groups are aggregated properly
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// for values of all types
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// also test the "remember" part of the Aggregation API
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// as final results are obtained via a property lookup of
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// a remembered node
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Dbms dbms;
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auto dba = dbms.active();
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// a vector of TypedValue to be set as property values on vertices
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// most of them should result in a distinct group (commented where not)
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std::vector<TypedValue> group_by_vals;
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group_by_vals.emplace_back(4);
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group_by_vals.emplace_back(7);
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group_by_vals.emplace_back(7.3);
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group_by_vals.emplace_back(7.2);
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group_by_vals.emplace_back("Johhny");
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group_by_vals.emplace_back("Jane");
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group_by_vals.emplace_back("1");
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group_by_vals.emplace_back(true);
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group_by_vals.emplace_back(false);
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group_by_vals.emplace_back(std::vector<TypedValue>{1});
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group_by_vals.emplace_back(std::vector<TypedValue>{1, 2});
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group_by_vals.emplace_back(std::vector<TypedValue>{2, 1});
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group_by_vals.emplace_back(TypedValue::Null);
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// should NOT result in another group because 7.0 == 7
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group_by_vals.emplace_back(7.0);
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// should NOT result in another group
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group_by_vals.emplace_back(std::vector<TypedValue>{1, 2.0});
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// generate a lot of vertices and set props on them
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auto prop = dba->property("prop");
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for (int i = 0; i < 1000; ++i)
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dba->insert_vertex().PropsSet(prop,
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group_by_vals[i % group_by_vals.size()]);
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dba->advance_command();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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// match all nodes and perform aggregations
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_p = PROPERTY_LOOKUP("n", prop);
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symbol_table[*n_p->expression_] = n.sym_;
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auto produce =
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MakeAggregationProduce(n.op_, symbol_table, storage, {n_p},
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{Aggregation::Op::COUNT}, {n_p}, {n.sym_});
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auto results = CollectProduce(produce.get(), symbol_table, *dba);
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ASSERT_EQ(results.size(), group_by_vals.size() - 2);
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TypedValue::unordered_set result_group_bys;
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for (const auto &row : results) {
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ASSERT_EQ(2, row.size());
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result_group_bys.insert(row[1]);
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}
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ASSERT_EQ(result_group_bys.size(), group_by_vals.size() - 2);
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EXPECT_TRUE(
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std::is_permutation(group_by_vals.begin(), group_by_vals.end() - 2,
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result_group_bys.begin(), TypedValue::BoolEqual{}));
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}
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TEST(QueryPlan, AggregateMultipleGroupBy) {
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// in this test we have 3 different properties that have different values
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// for different records and assert that we get the correct combination
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// of values in our groups
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Dbms dbms;
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auto dba = dbms.active();
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auto prop1 = dba->property("prop1");
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auto prop2 = dba->property("prop2");
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auto prop3 = dba->property("prop3");
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for (int i = 0; i < 2 * 3 * 5; ++i) {
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auto v = dba->insert_vertex();
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v.PropsSet(prop1, (bool)(i % 2));
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v.PropsSet(prop2, i % 3);
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v.PropsSet(prop3, "value" + std::to_string(i % 5));
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}
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dba->advance_command();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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// match all nodes and perform aggregations
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_p1 = PROPERTY_LOOKUP("n", prop1);
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auto n_p2 = PROPERTY_LOOKUP("n", prop2);
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auto n_p3 = PROPERTY_LOOKUP("n", prop3);
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symbol_table[*n_p1->expression_] = n.sym_;
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symbol_table[*n_p2->expression_] = n.sym_;
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symbol_table[*n_p3->expression_] = n.sym_;
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auto produce = MakeAggregationProduce(n.op_, symbol_table, storage, {n_p1},
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{Aggregation::Op::COUNT},
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{n_p1, n_p2, n_p3}, {n.sym_});
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auto results = CollectProduce(produce.get(), symbol_table, *dba);
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EXPECT_EQ(results.size(), 2 * 3 * 5);
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}
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TEST(QueryPlan, AggregateNoInput) {
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Dbms dbms;
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auto dba = dbms.active();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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auto two = LITERAL(2);
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auto output = NEXPR("two", IDENT("two"));
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symbol_table[*output->expression_] = symbol_table.CreateSymbol("two", true);
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auto produce = MakeAggregationProduce(nullptr, symbol_table, storage, {two},
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{Aggregation::Op::COUNT}, {}, {});
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auto results = CollectProduce(produce.get(), symbol_table, *dba);
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EXPECT_EQ(1, results.size());
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EXPECT_EQ(1, results[0].size());
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EXPECT_EQ(TypedValue::Type::Int, results[0][0].type());
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EXPECT_EQ(1, results[0][0].Value<int64_t>());
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}
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TEST(QueryPlan, AggregateCountEdgeCases) {
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// tests for detected bugs in the COUNT aggregation behavior
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// ensure that COUNT returns correctly for
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// - 0 vertices in database
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// - 1 vertex in database, property not set
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// - 1 vertex in database, property set
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// - 2 vertices in database, property set on one
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// - 2 vertices in database, property set on both
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Dbms dbms;
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auto dba = dbms.active();
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auto prop = dba->property("prop");
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AstTreeStorage storage;
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SymbolTable symbol_table;
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_p = PROPERTY_LOOKUP("n", prop);
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symbol_table[*n_p->expression_] = n.sym_;
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// returns -1 when there are no results
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// otherwise returns MATCH (n) RETURN count(n.prop)
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auto count = [&]() {
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auto produce = MakeAggregationProduce(n.op_, symbol_table, storage, {n_p},
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{Aggregation::Op::COUNT}, {}, {});
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auto results = CollectProduce(produce.get(), symbol_table, *dba);
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if (results.size() == 0) return -1L;
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EXPECT_EQ(1, results.size());
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EXPECT_EQ(1, results[0].size());
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EXPECT_EQ(TypedValue::Type::Int, results[0][0].type());
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return results[0][0].Value<int64_t>();
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};
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// no vertices yet in database
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EXPECT_EQ(0, count());
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// one vertex, no property set
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dba->insert_vertex();
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dba->advance_command();
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EXPECT_EQ(0, count());
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// one vertex, property set
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for (VertexAccessor va : dba->vertices(false)) va.PropsSet(prop, 42);
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dba->advance_command();
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EXPECT_EQ(1, count());
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// two vertices, one with property set
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dba->insert_vertex();
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dba->advance_command();
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EXPECT_EQ(1, count());
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// two vertices, both with property set
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for (VertexAccessor va : dba->vertices(false)) va.PropsSet(prop, 42);
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dba->advance_command();
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EXPECT_EQ(2, count());
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}
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TEST(QueryPlan, AggregateFirstValueTypes) {
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// testing exceptions that get emitted by the first-value
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// type check
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Dbms dbms;
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auto dba = dbms.active();
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auto v1 = dba->insert_vertex();
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auto prop_string = dba->property("string");
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v1.PropsSet(prop_string, "johhny");
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auto prop_int = dba->property("int");
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v1.PropsSet(prop_int, 12);
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dba->advance_command();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_prop_string = PROPERTY_LOOKUP("n", prop_string);
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symbol_table[*n_prop_string->expression_] = n.sym_;
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auto n_prop_int = PROPERTY_LOOKUP("n", prop_int);
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symbol_table[*n_prop_int->expression_] = n.sym_;
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auto n_id = n_prop_string->expression_;
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auto aggregate = [&](Expression *expression, Aggregation::Op aggr_op) {
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auto produce = MakeAggregationProduce(n.op_, symbol_table, storage,
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{expression}, {aggr_op}, {}, {});
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CollectProduce(produce.get(), symbol_table, *dba);
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};
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// everything except for COUNT fails on a Vertex
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aggregate(n_id, Aggregation::Op::COUNT);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::MIN), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::MAX), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::AVG), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::SUM), TypedValueException);
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// on strings AVG and SUM fail
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aggregate(n_prop_string, Aggregation::Op::COUNT);
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aggregate(n_prop_string, Aggregation::Op::MIN);
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aggregate(n_prop_string, Aggregation::Op::MAX);
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EXPECT_THROW(aggregate(n_prop_string, Aggregation::Op::AVG),
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TypedValueException);
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EXPECT_THROW(aggregate(n_prop_string, Aggregation::Op::SUM),
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TypedValueException);
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// on ints nothing fails
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aggregate(n_prop_int, Aggregation::Op::COUNT);
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aggregate(n_prop_int, Aggregation::Op::MIN);
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aggregate(n_prop_int, Aggregation::Op::MAX);
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aggregate(n_prop_int, Aggregation::Op::AVG);
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aggregate(n_prop_int, Aggregation::Op::SUM);
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}
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TEST(QueryPlan, AggregateTypes) {
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// testing exceptions that can get emitted by an aggregation
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// does not check all combinations that can result in an exception
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// (that logic is defined and tested by TypedValue)
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Dbms dbms;
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auto dba = dbms.active();
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auto p1 = dba->property("p1"); // has only string props
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dba->insert_vertex().PropsSet(p1, "string");
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dba->insert_vertex().PropsSet(p1, "str2");
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auto p2 = dba->property("p2"); // combines int and bool
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dba->insert_vertex().PropsSet(p2, 42);
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dba->insert_vertex().PropsSet(p2, true);
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dba->advance_command();
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AstTreeStorage storage;
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SymbolTable symbol_table;
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|
|
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auto n = MakeScanAll(storage, symbol_table, "n");
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auto n_p1 = PROPERTY_LOOKUP("n", p1);
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symbol_table[*n_p1->expression_] = n.sym_;
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auto n_p2 = PROPERTY_LOOKUP("n", p2);
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symbol_table[*n_p2->expression_] = n.sym_;
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auto aggregate = [&](Expression *expression, Aggregation::Op aggr_op) {
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auto produce = MakeAggregationProduce(n.op_, symbol_table, storage,
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{expression}, {aggr_op}, {}, {});
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CollectProduce(produce.get(), symbol_table, *dba);
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};
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|
|
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// everything except for COUNT fails on a Vertex
|
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auto n_id = n_p1->expression_;
|
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aggregate(n_id, Aggregation::Op::COUNT);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::MIN), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::MAX), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::AVG), TypedValueException);
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EXPECT_THROW(aggregate(n_id, Aggregation::Op::SUM), TypedValueException);
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|
|
|
// on strings AVG and SUM fail
|
|
aggregate(n_p1, Aggregation::Op::COUNT);
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|
aggregate(n_p1, Aggregation::Op::MIN);
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aggregate(n_p1, Aggregation::Op::MAX);
|
|
EXPECT_THROW(aggregate(n_p1, Aggregation::Op::AVG), TypedValueException);
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|
EXPECT_THROW(aggregate(n_p1, Aggregation::Op::SUM), TypedValueException);
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|
|
|
// combination of int and bool, everything except count fails
|
|
aggregate(n_p2, Aggregation::Op::COUNT);
|
|
EXPECT_THROW(aggregate(n_p2, Aggregation::Op::MIN), TypedValueException);
|
|
EXPECT_THROW(aggregate(n_p2, Aggregation::Op::MAX), TypedValueException);
|
|
EXPECT_THROW(aggregate(n_p2, Aggregation::Op::AVG), TypedValueException);
|
|
EXPECT_THROW(aggregate(n_p2, Aggregation::Op::SUM), TypedValueException);
|
|
}
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|
|
|
TEST(QueryPlan, Unwind) {
|
|
Dbms dbms;
|
|
auto dba = dbms.active();
|
|
AstTreeStorage storage;
|
|
SymbolTable symbol_table;
|
|
|
|
// UNWIND [ [1, true, "x"], [], ["bla"] ] AS x UNWIND x as y RETURN x, y
|
|
auto input_expr = storage.Create<PrimitiveLiteral>(std::vector<TypedValue>{
|
|
std::vector<TypedValue>{1, true, "x"}, std::vector<TypedValue>{},
|
|
std::vector<TypedValue>{"bla"}});
|
|
|
|
auto x = symbol_table.CreateSymbol("x", true);
|
|
auto unwind_0 = std::make_shared<plan::Unwind>(nullptr, input_expr, x);
|
|
auto x_expr = IDENT("x");
|
|
symbol_table[*x_expr] = x;
|
|
auto y = symbol_table.CreateSymbol("y", true);
|
|
auto unwind_1 = std::make_shared<plan::Unwind>(unwind_0, x_expr, y);
|
|
|
|
auto x_ne = NEXPR("x", x_expr);
|
|
symbol_table[*x_ne] = symbol_table.CreateSymbol("x_ne", true);
|
|
auto y_ne = NEXPR("y", IDENT("y"));
|
|
symbol_table[*y_ne->expression_] = y;
|
|
symbol_table[*y_ne] = symbol_table.CreateSymbol("y_ne", true);
|
|
auto produce = MakeProduce(unwind_1, x_ne, y_ne);
|
|
|
|
auto results = CollectProduce(produce.get(), symbol_table, *dba);
|
|
ASSERT_EQ(4, results.size());
|
|
const std::vector<int> expected_x_card{3, 3, 3, 1};
|
|
auto expected_x_card_it = expected_x_card.begin();
|
|
const std::vector<TypedValue> expected_y{1, true, "x", "bla"};
|
|
auto expected_y_it = expected_y.begin();
|
|
for (const auto &row : results) {
|
|
ASSERT_EQ(2, row.size());
|
|
ASSERT_EQ(row[0].type(), TypedValue::Type::List);
|
|
EXPECT_EQ(row[0].Value<std::vector<TypedValue>>().size(),
|
|
*expected_x_card_it);
|
|
EXPECT_EQ(row[1].type(), expected_y_it->type());
|
|
expected_x_card_it++;
|
|
expected_y_it++;
|
|
}
|
|
}
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