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[SPARK-28306][SQL][FOLLOWUP] Fix NormalizeFloatingNumbers rule idempotence for equi-join with <=> predicates #25126

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[SPARK-28306][SQL][FOLLOWUP] Fix NormalizeFloatingNumbers rule idempotence for equi-join with <=> predicates #25126

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1e2c297
fix for equal null safe
yeshengm Jul 11, 2019
fc456ef
fix join condition
yeshengm Jul 12, 2019
b1a6c0f
fix UT
yeshengm Jul 12, 2019
40cbad1
fix
yeshengm Jul 12, 2019
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16 changes: 10 additions & 6 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -118,19 +118,23 @@ object ExtractEquiJoinKeys extends Logging with PredicateHelper {
// Replace null with default value for joining key, then those rows with null in it could
// be joined together
case EqualNullSafe(l, r) if canEvaluate(l, left) && canEvaluate(r, right) =>
Some((Coalesce(Seq(l, Literal.default(l.dataType))),
Coalesce(Seq(r, Literal.default(r.dataType)))))
Seq((Coalesce(Seq(l, Literal.default(l.dataType))),
Coalesce(Seq(r, Literal.default(r.dataType)))),
(IsNull(l), IsNull(r))
)
case EqualNullSafe(l, r) if canEvaluate(l, right) && canEvaluate(r, left) =>
Some((Coalesce(Seq(r, Literal.default(r.dataType))),
Coalesce(Seq(l, Literal.default(l.dataType)))))
Seq((Coalesce(Seq(r, Literal.default(r.dataType))),
Coalesce(Seq(l, Literal.default(l.dataType)))),
(IsNull(r), IsNull(l))
)
case other => None
}
val otherPredicates = predicates.filterNot {
case EqualTo(l, r) if l.references.isEmpty || r.references.isEmpty => false
case EqualTo(l, r) =>
case Equality(l, r) =>
canEvaluate(l, left) && canEvaluate(r, right) ||
canEvaluate(l, right) && canEvaluate(r, left)
case other => false
case _ => false
}

if (joinKeys.nonEmpty) {
Expand Down
15 changes: 14 additions & 1 deletion ...st/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFloatingPointNumbersSuite.scala
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Expand Up @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.optimizer

import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.dsl.plans._
import org.apache.spark.sql.catalyst.expressions.KnownFloatingPointNormalized
import org.apache.spark.sql.catalyst.expressions.{And, IsNull, KnownFloatingPointNormalized}
import org.apache.spark.sql.catalyst.plans.PlanTest
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules.RuleExecutor
Expand Down Expand Up @@ -78,5 +78,18 @@ class NormalizeFloatingPointNumbersSuite extends PlanTest {

comparePlans(doubleOptimized, correctAnswer)
}

test("normalize floating points in join keys (equal null safe) - idempotence") {
val query = testRelation1.join(testRelation2, condition = Some(a <=> b))

val optimized = Optimize.execute(query)
val doubleOptimized = Optimize.execute(optimized)
val joinCond = IsNull(a) === IsNull(b) &&
KnownFloatingPointNormalized(NormalizeNaNAndZero(coalesce(a, 0.0))) ===
KnownFloatingPointNormalized(NormalizeNaNAndZero(coalesce(b, 0.0)))
val correctAnswer = testRelation1.join(testRelation2, condition = Some(joinCond))

comparePlans(doubleOptimized, correctAnswer)
}
}