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[SPARK-40610][SQL] Support unwrap date type to string type #40294

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[SPARK-40610][SQL] Support unwrap date type to string type #40294

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8 changes: 7 additions & 1 deletion ...src/main/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparison.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -133,6 +133,11 @@ object UnwrapCastInBinaryComparison extends Rule[LogicalPlan] {
if canImplicitlyCast(fromExp, toType, literalType) =>
simplifyNumericComparison(be, fromExp, toType, value)

case be @ BinaryComparison(
Cast(fromExp, _, timeZoneId, evalMode), date @ Literal(value, DateType))
if fromExp.dataType == StringType && value != null =>
be.withNewChildren(Seq(fromExp, Cast(date, StringType, timeZoneId, evalMode)))
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@cloud-fan cloud-fan Mar 7, 2023

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This is tricky, as we need to be very careful about the reverse of date string parsing. Can we reference the detail of date string parsing in Cast and prove it's safe to do this optimization?

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@beryllw beryllw Mar 29, 2023

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UnwrapCastInBinaryComparison class is only responsible for processing casts related to numeric types, and it is dangerous to cast date types. Can we add the related conversion of partition columns to the PruneHiveTablePartitions rule?


// As the analyzer makes sure that the list of In is already of the same data type, then the
// rule can simply check the first literal in `in.list` can implicitly cast to `toType` or not,
// and note that:
Expand Down Expand Up @@ -350,7 +355,7 @@ object UnwrapCastInBinaryComparison extends Rule[LogicalPlan] {
literalType: DataType): Boolean = {
toType.sameType(literalType) &&
!fromExp.foldable &&
toType.isInstanceOf[NumericType] &&
(toType.isInstanceOf[NumericType] || toType.isInstanceOf[DateType]) &&
canUnwrapCast(fromExp.dataType, toType)
}

Expand All @@ -361,6 +366,7 @@ object UnwrapCastInBinaryComparison extends Rule[LogicalPlan] {
case (IntegerType, FloatType) => false
case (LongType, FloatType) => false
case (LongType, DoubleType) => false
case (StringType, DateType) => true
case _ if from.isInstanceOf[NumericType] => Cast.canUpCast(from, to)
case _ => false
}
Expand Down
31 changes: 31 additions & 0 deletions ...est/scala/org/apache/spark/sql/catalyst/optimizer/UnwrapCastInBinaryComparisonSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,8 @@

package org.apache.spark.sql.catalyst.optimizer

import java.sql.Date

import scala.collection.immutable.HashSet

import org.apache.spark.sql.catalyst.dsl.expressions._
Expand Down Expand Up @@ -368,6 +370,35 @@ class UnwrapCastInBinaryComparisonSuite extends PlanTest with ExpressionEvalHelp
assertEquivalent(castInt(f4) < t, trueIfNotNull(f4))
}

test("SPARK-40610: Support unwrap date type to string type") {
val relation = LocalRelation($"a".string, $"b".string)
val dateLit = Literal.create(Date.valueOf("2023-01-01"), DateType)
val nullLit = Literal.create(null, DateType)

def assertUnwrapStringToDateType(e1: Expression, e2: Expression): Unit = {
val plan = relation.where(e1).analyze
val actual = Optimize.execute(plan)
val expected = relation.where(e2).analyze
comparePlans(actual, expected)
}

Seq(EqualTo, EqualNullSafe, GreaterThan, GreaterThanOrEqual, LessThan, LessThanOrEqual)
.foreach { binaryComparison =>
assertUnwrapStringToDateType(
binaryComparison(Cast($"a", DateType), dateLit),
binaryComparison($"a", Cast(dateLit, StringType)))
}

assertUnwrapStringToDateType(
dateLit =!= Cast($"a", DateType),
Cast(dateLit, StringType) =!= $"a")

// Null date literal should be handled by NullPropagation
assertUnwrapStringToDateType(
Cast($"a", DateType) > nullLit,
Literal.create(null, BooleanType))
}

private def castInt(e: Expression): Expression = Cast(e, IntegerType)
private def castDouble(e: Expression): Expression = Cast(e, DoubleType)
private def castDecimal2(e: Expression): Expression = Cast(e, DecimalType(10, 4))
Expand Down