[jira] [Created] (SPARK-32551) Ambiguous self join error in non self join with window

["kanika dhuria (Jira)" <ji...@apache.org>]

kanika dhuria created SPARK-32551:
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             Summary: Ambiguous self join error in non self join with window
                 Key: SPARK-32551
                 URL: https://issues.apache.org/jira/browse/SPARK-32551
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 3.0.0
            Reporter: kanika dhuria


Following code hits ambiguous join error even when it doesn't have self join 

val v1 = spark.range(3).toDF("m")
 val v2 = spark.range(3).toDF("d")
 val v3 = v1.join(v2, v1("m").===(v2("d")))
 val v4 = v3("d");
 val w1 = Window.partitionBy(v4)
 val out = v3.select(v4.as("a"), sum(v4).over(w1).as("b"))

org.apache.spark.sql.AnalysisException: Column a#45L are ambiguous. It's probably because you joined several Datasets together, and some of these Datasets are the same. This column points to one of the Datasets but Spark is unable to figure out which one. Please alias the Datasets with different names via `Dataset.as` before joining them, and specify the column using qualified name, e.g. `df.as("a").join(df.as("b"), $"a.id" > $"b.id")`. You can also set spark.sql.analyzer.failAmbiguousSelfJoin to false to disable this check.;

 



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