[jira] [Created] (SPARK-37690) Recursive view `df` detected (cycle: `df` -> `df`)

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

Robin created SPARK-37690:
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             Summary: Recursive view `df` detected (cycle: `df` -> `df`)
                 Key: SPARK-37690
                 URL: https://issues.apache.org/jira/browse/SPARK-37690
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 3.2.0
            Reporter: Robin


In Spark 3.2.0, you can no longer reuse the same name for a temporary view.  This change is backwards incompatible, and means a common way of running pipelines of SQL queries no longer works.   The following is a simple reproducible example that works in Spark 2.x and 3.1.2, but not in 3.2.0: 

{code:python} from pyspark.context import SparkContext from pyspark.sql import SparkSession sc = SparkContext.getOrCreate() spark = SparkSession(sc) sql = """ SELECT id as col_1, rand() AS col_2 FROM RANGE(10); """ df = spark.sql(sql) df.createOrReplaceTempView("df") sql = """ SELECT * FROM df """ df = spark.sql(sql) df.createOrReplaceTempView("df") sql = """ SELECT * FROM df """ df = spark.sql(sql) {code}   The following error is now produced:   {code:python} AnalysisException: Recursive view `df` detected (cycle: `df` -> `df`) {code} 

I'm reasonably sure this change is unintentional in 3.2.0 since it breaks a lot of legacy code, and the `createOrReplaceTempView` method is named explicitly such that replacing an existing view should be allowed.   An internet search suggests other users have run into a similar problems, e.g. [here|https://community.databricks.com/s/question/0D53f00001Qugr7CAB/upgrading-from-spark-24-to-32-recursive-view-errors-when-using]  



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