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[SPARK-20359][SQL] Avoid unnecessary execution in EliminateOuterJoin optimization that can lead to NPE #17660

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[SPARK-20359][SQL] Avoid unnecessary execution in EliminateOuterJoin optimization that can lead to NPE #17660

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7a759cc
catch NPE in EliminateOuterJoin and add test in DataFrameSuite to con…
koertkuipers Apr 17, 2017
5e2b828
add actual jira
koertkuipers Apr 17, 2017
975c850
use lazy vals instead of catching NPE
koertkuipers Apr 18, 2017
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11 changes: 10 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/joins.scala
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Expand Up @@ -19,6 +19,7 @@ package org.apache.spark.sql.catalyst.optimizer

import scala.annotation.tailrec

import org.apache.spark.SparkException
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.planning.ExtractFiltersAndInnerJoins
import org.apache.spark.sql.catalyst.plans._
Expand Down Expand Up @@ -124,7 +125,15 @@ case class EliminateOuterJoin(conf: SQLConf) extends Rule[LogicalPlan] with Pred
val emptyRow = new GenericInternalRow(attributes.length)
val boundE = BindReferences.bindReference(e, attributes)
if (boundE.find(_.isInstanceOf[Unevaluable]).isDefined) return false
val v = boundE.eval(emptyRow)
val v = try {
boundE.eval(emptyRow)

@gatorsmile gatorsmile Apr 17, 2017

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Could you check whether there exists the other similar cases in the code base that could trigger NullPointerException?

@koertkuipers koertkuipers Apr 17, 2017

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yeah sure i can do a scan for similar problems

} catch {
case e: SparkException =>
e.getCause match {
case _: NullPointerException => true
case _ => throw e
}
}
v == null || v == false
}

Expand Down
10 changes: 10 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
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Expand Up @@ -1722,4 +1722,14 @@ class DataFrameSuite extends QueryTest with SharedSQLContext {
"Cannot have map type columns in DataFrame which calls set operations"))
}
}

test("SPARK-20359: catalyst outer join optimization should not throw npe") {
val df1 = Seq("a", "b", "c").toDF("x")
.withColumn("y", udf{ (x: String) => x.substring(0, 1) + "!" }.apply($"x"))
val df2 = Seq("a", "b").toDF("x1")
df1
.join(df2, df1("x") === df2("x1"), "left_outer")
.filter($"x1".isNotNull || !$"y".isin("a!"))
.count
}
}