marios iliofotou created SPARK-24839:
----------------------------------------
Summary: Incorrect drop of lit column results in cross join.
Key: SPARK-24839
URL: https://issues.apache.org/jira/browse/SPARK-24839
Project: Spark
Issue Type: Bug
Components: Optimizer
Affects Versions: 2.3.1
Reporter: marios iliofotou
```
scala> val df1 = spark.createDataFrame(Seq((1, 2), (2,
4))).withColumn("index", org.apache.spark.sql.functions.lit("a"))
scala> df1.show
+---+---+-----+
| _1| _2|index|
+---+---+-----+
| 1| 2| a|
| 2| 4| a|
+---+---+-----+
scala> val df2 = spark.createDataFrame(Seq(("a", 1),("b", 2))).toDF("index",
"someval")
scala> df2.show()
+-----+-------+
|index|someval|
+-----+-------+
| a| 1|
| b| 2|
+-----+-------+
scala> df1.join(df2).show()
org.apache.spark.sql.AnalysisException: Detected implicit cartesian product for
INNER join between logical plans
LocalRelation [_1#370, _2#371]
and
LocalRelation [index#335, someval#336]
Join condition is missing or trivial.
Either: use the CROSS JOIN syntax to allow cartesian products between these
relations, or: enable implicit cartesian products by setting the configuration
variable spark.sql.crossJoin.enabled=true;
at
org.apache.spark.sql.catalyst.optimizer.CheckCartesianProducts$$anonfun$apply$21.applyOrElse(Optimizer.scala:1124)
at
org.apache.spark.sql.catalyst.optimizer.CheckCartesianProducts$$anonfun$apply$21.applyOrElse(Optimizer.scala:1121)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
at
org.apache.spark.sql.catalyst.optimizer.CheckCartesianProducts$.apply(Optimizer.scala:1121)
at
org.apache.spark.sql.catalyst.optimizer.CheckCartesianProducts$.apply(Optimizer.scala:1103)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:87)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:84)
at
scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
at
scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:35)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:76)
at scala.collection.immutable.List.foreach(List.scala:392)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)
at
org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:66)
at
org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:66)
at
org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:72)
at
org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:68)
at
org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:77)
at
org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:77)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3249)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
at org.apache.spark.sql.Dataset.show(Dataset.scala:691)
... 42 elided
```
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