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PatternSelectivityCalculatorTest.scala
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PatternSelectivityCalculatorTest.scala
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/*
* Copyright (c) 2002-2017 "Neo Technology,"
* Network Engine for Objects in Lund AB [http://neotechnology.com]
*
* This file is part of Neo4j.
*
* Neo4j is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package org.neo4j.cypher.internal.compiler.v3_4.planner.logical.cardinality.assumeIndependence
import org.mockito.ArgumentMatchers.any
import org.mockito.Mockito._
import org.mockito.invocation.InvocationOnMock
import org.mockito.stubbing.Answer
import org.neo4j.cypher.internal.compiler.v3_4.planner.LogicalPlanConstructionTestSupport
import org.neo4j.cypher.internal.compiler.v3_4.planner.logical.cardinality.IndependenceCombiner
import org.neo4j.cypher.internal.compiler.v3_4.spi.GraphStatistics
import org.neo4j.cypher.internal.frontend.v3_4.ast.{AstConstructionTestSupport, HasLabels, LabelName}
import org.neo4j.cypher.internal.frontend.v3_4.test_helpers.CypherFunSuite
import org.neo4j.cypher.internal.frontend.v3_4.{LabelId, SemanticDirection, SemanticTable}
import org.neo4j.cypher.internal.ir.v3_4.{VarPatternLength, _}
import scala.collection.mutable
class PatternSelectivityCalculatorTest extends CypherFunSuite with LogicalPlanConstructionTestSupport with AstConstructionTestSupport {
test("should return zero if there are no nodes with the given labels") {
val stats: GraphStatistics = mock[GraphStatistics]
when(stats.nodesWithLabelCardinality(any())).thenReturn(Cardinality(0))
when(stats.cardinalityByLabelsAndRelationshipType(any(), any(), any())).thenReturn(Cardinality(42))
val calculator = PatternSelectivityCalculator(stats, IndependenceCombiner)
val relationship = PatternRelationship("r", ("a", "b"), SemanticDirection.OUTGOING, Seq.empty, SimplePatternLength)
val label = LabelName("L")(pos)
implicit val semanticTable = new SemanticTable(resolvedLabelIds = mutable.Map("L" -> LabelId(0)))
implicit val selections = Selections(Set(Predicate(Set[IdName]("a"), HasLabels(varFor("a"), Seq(label))(pos))))
val result = calculator.apply(relationship, Map(IdName("a") -> Set(label)))
result should equal(Selectivity.ZERO)
}
test("should not consider label selectivity twice") {
val stats: GraphStatistics = mock[GraphStatistics]
when(stats.nodesWithLabelCardinality(any())).thenReturn(Cardinality(1))
when(stats.cardinalityByLabelsAndRelationshipType(any(), any(), any())).thenReturn(Cardinality(42))
val calculator = PatternSelectivityCalculator(stats, IndependenceCombiner)
val relationship = PatternRelationship("r", ("a", "b"), SemanticDirection.OUTGOING, Seq.empty, SimplePatternLength)
val label = LabelName("L")(pos)
implicit val semanticTable = new SemanticTable(resolvedLabelIds = mutable.Map("L" -> LabelId(0)))
implicit val selections = Selections(Set(Predicate(Set[IdName]("a"), HasLabels(varFor("a"), Seq(label))(pos))))
val result = calculator.apply(relationship, Map(IdName("a") -> Set(label)))
result should equal(Selectivity.ONE)
}
test("handles variable length paths over 32 in length") {
val stats: GraphStatistics = mock[GraphStatistics]
when(stats.nodesWithLabelCardinality(any())).thenReturn(Cardinality(1))
when(stats.cardinalityByLabelsAndRelationshipType(any(), any(), any())).thenReturn(Cardinality(3))
val calculator = PatternSelectivityCalculator(stats, IndependenceCombiner)
val relationship = PatternRelationship("r", ("a", "b"), SemanticDirection.OUTGOING, Seq.empty, VarPatternLength(33, Some(33)))
val label = LabelName("L")(pos)
implicit val semanticTable = new SemanticTable(resolvedLabelIds = mutable.Map("L" -> LabelId(0)))
implicit val selections = Selections(Set(Predicate(Set[IdName]("a"), HasLabels(varFor("a"), Seq(label))(pos))))
val result = calculator.apply(relationship, Map(IdName("a") -> Set(label)))
result should equal(Selectivity.ONE)
}
test("should not produce selectivities larger than 1.0") {
val stats: GraphStatistics = mock[GraphStatistics]
when(stats.nodesWithLabelCardinality(any())).thenAnswer(new Answer[Cardinality] {
override def answer(invocationOnMock: InvocationOnMock): Cardinality = {
val arg:Option[LabelId] = invocationOnMock.getArgument(0)
arg match {
case None => Cardinality(10)
case Some(_) => Cardinality(1)
}
}
})
when(stats.cardinalityByLabelsAndRelationshipType(any(), any(), any())).thenReturn(Cardinality(42))
val calculator = PatternSelectivityCalculator(stats, IndependenceCombiner)
val relationship = PatternRelationship("r", ("a", "b"), SemanticDirection.OUTGOING, Seq.empty, SimplePatternLength)
val labels = new mutable.HashMap[String, LabelId]()
for (i <- 1 to 100) labels.put(i.toString, LabelId(i))
val labelNames = labels.keys.map(LabelName(_)(pos))
val predicates = labelNames.map(l => Predicate(Set[IdName]("a"), HasLabels(varFor("a"), Seq(l))(pos))).toSet
implicit val semanticTable = new SemanticTable(resolvedLabelIds = labels)
implicit val selections = Selections(predicates)
val result = calculator.apply(relationship, Map.empty)
result should equal(Selectivity.ONE)
}
}