Github user xuanyuanking commented on a diff in the pull request:

    https://github.com/apache/spark/pull/22326#discussion_r220432728
  
    --- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/joins.scala 
---
    @@ -152,3 +153,56 @@ object EliminateOuterJoin extends Rule[LogicalPlan] 
with PredicateHelper {
           if (j.joinType == newJoinType) f else Filter(condition, 
j.copy(joinType = newJoinType))
       }
     }
    +
    +/**
    + * Correctly handle PythonUDF which need access both side of join side by 
changing the new join
    + * type to Cross.
    + */
    +object HandlePythonUDFInJoinCondition extends Rule[LogicalPlan] with 
PredicateHelper {
    +  def hasPythonUDF(expression: Expression): Boolean = {
    +    expression.collectFirst { case udf: PythonUDF => udf }.isDefined
    +  }
    +
    +  override def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
    +    case j @ Join(_, _, joinType, condition)
    +      if 
condition.map(splitConjunctivePredicates).getOrElse(Nil).exists(hasPythonUDF) =>
    +      if (!joinType.isInstanceOf[InnerLike] && joinType != LeftSemi) {
    +        // The current strategy only support InnerLike and LeftSemi join 
because for other type,
    +        // it breaks SQL semantic if we run the join condition as a filter 
after join. If we pass
    +        // the plan here, it'll still get a an invalid PythonUDF 
RuntimeException with message
    +        // `requires attributes from more than one child`, we throw 
firstly here for better
    +        // readable information.
    +        throw new AnalysisException("Using PythonUDF in join condition of 
join type" +
    +          s" $joinType is not supported.")
    +      }
    +      if (SQLConf.get.crossJoinEnabled) {
    --- End diff --
    
    ```
    What about just doing the change?
    ```
    If just do the change here, the udf check in `CheckCartesianProducts` is 
not work because we have pulled out the udf in join condition.


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