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https://issues.apache.org/jira/browse/SPARK-37690?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17464354#comment-17464354
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Robin commented on SPARK-37690:
-------------------------------
Someone
[here|https://community.databricks.com/s/question/0D53f00001Qugr7CAB/upgrading-from-spark-24-to-32-recursive-view-errors-when-using]
has suggested this is an intentional breaking change introduced in Spark 3.1:
>From [Migration Guide: SQL, Datasets and DataFrame - Spark 3.1.1 Documentation
>(apache.org)|https://spark.apache.org/docs/3.1.1/sql-migration-guide.html]]
> In Spark 3.1, the temporary view will have same behaviors with the permanent
> view, i.e. capture and store runtime SQL configs, SQL text, catalog and
> namespace. The capatured view properties will be applied during the parsing
> and analysis phases of the view resolution. To restore the behavior before
> Spark 3.1, {*}you can set spark.sql.legacy.storeAnalyzedPlanForView to
> true{*}.
Grateful if someone could clarify. Worth noting that the example code works in
Spark 3.1.2, just not 3.2.0. It's not obvious to me the above quote implies
`createOrReplaceTempView` would fail in the example code posted in the issue.
> 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
> Priority: Major
>
> 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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