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[SPARK-24994][SQL][FOLLOW-UP] Handle foldable, timezone and cleanup #29775

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[SPARK-24994][SQL][FOLLOW-UP] Handle foldable, timezone and cleanup #29775

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[SPARK-24994][SQL][FOLLOW-UP] Handle foldable, timezone and cleanup
sunchao Sep 16, 2020
3a0f4b0
Replace cast with literal value
sunchao Sep 17, 2020
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7 changes: 5 additions & 2 deletions ...src/main/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparison.scala
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Expand Up @@ -184,7 +184,7 @@ object UnwrapCastInBinaryComparison extends Rule[LogicalPlan] {
} else {
// This means `value` is within range `(min, max)`. Optimize this by moving the cast to the
// literal side.
val lit = Cast(Literal(value), fromType)
val lit = Literal(Cast(Literal(value), fromType).eval(), fromType)
exp match {
case GreaterThan(_, _) => GreaterThan(fromExp, lit)
case GreaterThanOrEqual(_, _) => GreaterThanOrEqual(fromExp, lit)
Expand All @@ -202,9 +202,12 @@ object UnwrapCastInBinaryComparison extends Rule[LogicalPlan] {
* i.e., the conversion is injective. Note this only handles the case when both sides are of
* integral type.
*/
private def canImplicitlyCast(fromExp: Expression, toType: DataType,
private def canImplicitlyCast(
fromExp: Expression,
toType: DataType,
literalType: DataType): Boolean = {
toType.sameType(literalType) &&
!fromExp.foldable &&
fromExp.dataType.isInstanceOf[IntegralType] &&
toType.isInstanceOf[IntegralType] &&
Cast.canUpCast(fromExp.dataType, toType)
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10 changes: 6 additions & 4 deletions ...est/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparisonSuite.scala
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Expand Up @@ -26,14 +26,14 @@ import org.apache.spark.sql.catalyst.optimizer.UnwrapCastInBinaryComparison._
import org.apache.spark.sql.catalyst.plans.PlanTest
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules.RuleExecutor
import org.apache.spark.sql.types.{BooleanType, ByteType, DoubleType, IntegerType}
import org.apache.spark.sql.types._

class UnwrapCastInBinaryComparisonSuite extends PlanTest with ExpressionEvalHelper {

object Optimize extends RuleExecutor[LogicalPlan] {
val batches: List[Batch] =
Batch("Unwrap casts in binary comparison", FixedPoint(10),
NullPropagation, ConstantFolding, UnwrapCastInBinaryComparison) :: Nil
NullPropagation, UnwrapCastInBinaryComparison) :: Nil
}

val testRelation: LocalRelation = LocalRelation('a.short, 'b.float)
Expand Down Expand Up @@ -97,7 +97,7 @@ class UnwrapCastInBinaryComparisonSuite extends PlanTest with ExpressionEvalHelp
assertEquivalent(Literal(v.toInt) >= castInt(f), trueIfNotNull(f))
assertEquivalent(Literal(v.toInt) > castInt(f), f =!= v)

assertEquivalent(Literal(30) <= castInt(f), Literal(30.toShort) <= f)
assertEquivalent(Literal(30) <= castInt(f), Literal(30.toShort, ShortType) <= f)
}

test("unwrap cast should have no effect when input is not integral type") {
Expand All @@ -119,10 +119,12 @@ class UnwrapCastInBinaryComparisonSuite extends PlanTest with ExpressionEvalHelp
)
}

test("unwrap cast should skip when expression is non-deterministic") {
test("unwrap cast should skip when expression is non-deterministic or foldable") {
Seq(positiveInt, negativeInt).foreach (v => {
val e = Cast(First(f, ignoreNulls = true), IntegerType) <=> v
assertEquivalent(e, e, evaluate = false)
val e2 = Cast(Literal(30.toShort), IntegerType) >= v
assertEquivalent(e2, e2, evaluate = false)
})
}

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5 changes: 2 additions & 3 deletions sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
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Expand Up @@ -32,14 +32,13 @@ import org.apache.spark.scheduler.{SparkListener, SparkListenerTaskEnd}
import org.apache.spark.sql.TestingUDT.{IntervalUDT, NullData, NullUDT}
import org.apache.spark.sql.catalyst.expressions.AttributeReference
import org.apache.spark.sql.catalyst.expressions.IntegralLiteralTestUtils.{negativeInt, positiveInt}
import org.apache.spark.sql.catalyst.planning.PhysicalOperation
import org.apache.spark.sql.catalyst.plans.logical.Filter
import org.apache.spark.sql.execution.SimpleMode
import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
import org.apache.spark.sql.execution.datasources.FilePartition
import org.apache.spark.sql.execution.datasources.v2.{BatchScanExec, DataSourceV2ScanRelation, FileScan}
import org.apache.spark.sql.execution.datasources.v2.{BatchScanExec, FileScan}
import org.apache.spark.sql.execution.datasources.v2.orc.OrcScan
import org.apache.spark.sql.execution.datasources.v2.parquet.{ParquetScan, ParquetTable}
import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan
import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, SortMergeJoinExec}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.internal.SQLConf
Expand Down