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[SPARK-33338][SQL] GROUP BY using literal map should not fail #30246

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[SPARK-33338][SQL] GROUP BY using literal map should not fail #30246

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[SPARK-33338][SQL] semanticEquals should handle static GetMapValue co…
dongjoon-hyun Nov 4, 2020
b7367d7
Add more test cases
dongjoon-hyun Nov 4, 2020
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2 changes: 2 additions & 0 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala
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Expand Up @@ -316,6 +316,8 @@ case class Literal (value: Any, dataType: DataType) extends LeafExpression {
(value, o.value) match {
case (null, null) => true
case (a: Array[Byte], b: Array[Byte]) => util.Arrays.equals(a, b)
case (a: ArrayBasedMapData, b: ArrayBasedMapData) =>
a.keyArray == b.keyArray && a.valueArray == b.valueArray
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GenericArrayData has equals.

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Quick question, why we don't have equals in ArrayBasedMapData?

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I also considered that way first, but I didn't do that because of this.

/**
 * This is an internal data representation for map type in Spark SQL. This should not implement
 * `equals` and `hashCode` because the type cannot be used as join keys, grouping keys, or
 * in equality tests. See SPARK-9415 and PR#13847 for the discussions.
 */
abstract class MapData extends Serializable

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That's the reason why I focused on literal map equality only.

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Thanks!

case (a, b) => a != null && a.equals(b)
}
case _ => false
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15 changes: 15 additions & 0 deletions sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ComplexTypeSuite.scala
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Expand Up @@ -22,6 +22,7 @@ import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, UnresolvedExtractValue}
import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext
import org.apache.spark.sql.catalyst.util._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._
import org.apache.spark.unsafe.types.UTF8String
Expand Down Expand Up @@ -471,4 +472,18 @@ class ComplexTypeSuite extends SparkFunSuite with ExpressionEvalHelper {
CreateNamedStruct(Seq("a", "x", "b", 2.0)).genCode(ctx)
assert(ctx.inlinedMutableStates.isEmpty)
}

test("SPARK-33338: semanticEquals should handle static GetMapValue correctly") {
val keys = new Array[UTF8String](1)
val values = new Array[UTF8String](1)
keys(0) = UTF8String.fromString("key")
values(0) = UTF8String.fromString("value")

val d1 = new ArrayBasedMapData(new GenericArrayData(keys), new GenericArrayData(values))
val d2 = new ArrayBasedMapData(new GenericArrayData(keys), new GenericArrayData(values))
val m1 = GetMapValue(Literal.create(d1, MapType(StringType, StringType)), Literal("a"))
val m2 = GetMapValue(Literal.create(d2, MapType(StringType, StringType)), Literal("a"))

assert(m1.semanticEquals(m2))
}
}
12 changes: 12 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Expand Up @@ -3706,6 +3706,18 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
}
}
}

test("SPARK-33338: GROUP BY using literal map should not fail") {
withTempDir { dir =>
sql(s"CREATE TABLE t USING ORC LOCATION '${dir.toURI}' AS SELECT map('k1', 'v1') m, 'k1' k")
Seq(
"SELECT map('k1', 'v1')[k] FROM t GROUP BY 1",
"SELECT map('k1', 'v1')[k] FROM t GROUP BY map('k1', 'v1')[k]",
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how about SELECT map('k1', 'v1', 'k2', 'v2')[k] FROM t GROUP BY map('k2', 'v2', 'k1', 'v1')[k]?

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Since we don't normalize the literal maps, they are not the same maps, @cloud-fan . We should not handle it here, @cloud-fan .

"SELECT map('k1', 'v1')[k] a FROM t GROUP BY a").foreach { statement =>
checkAnswer(sql(statement), Row("v1"))
}
}
}
}

case class Foo(bar: Option[String])