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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