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https://issues.apache.org/jira/browse/SPARK-42752?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-42752:
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Affects Version/s: (was: 3.1.3)
(was: 3.2.4)
(was: 3.4.1)
(was: 3.3.3)
> Unprintable IllegalArgumentException with Hive catalog enabled in "Hadoop
> Free" distibution
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-42752
> URL: https://issues.apache.org/jira/browse/SPARK-42752
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Affects Versions: 3.5.0
> Environment: local
> Reporter: Gera Shegalov
> Assignee: Gera Shegalov
> Priority: Minor
> Fix For: 3.5.0
>
>
> Reproduction steps:
> 1. download a standard "Hadoop Free" build
> 2. Start pyspark REPL with Hive support
> {code:java}
> SPARK_DIST_CLASSPATH=$(~/dist/hadoop-3.4.0-SNAPSHOT/bin/hadoop classpath)
> ~/dist/spark-3.2.3-bin-without-hadoop/bin/pyspark --conf
> spark.sql.catalogImplementation=hive
> {code}
> 3. Execute any simple dataframe operation
> {code:java}
> >>> spark.range(100).show()
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File
> "/home/user/dist/spark-3.2.3-bin-without-hadoop/python/pyspark/sql/session.py",
> line 416, in range
> jdf = self._jsparkSession.range(0, int(start), int(step),
> int(numPartitions))
> File
> "/home/user/dist/spark-3.2.3-bin-without-hadoop/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py",
> line 1321, in __call__
> File
> "/home/user/dist/spark-3.2.3-bin-without-hadoop/python/pyspark/sql/utils.py",
> line 117, in deco
> raise converted from None
> pyspark.sql.utils.IllegalArgumentException: <exception str() failed>
> {code}
> 4. In fact you can just call spark.conf to trigger this issue
> {code:java}
> >>> spark.conf
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> ...
> {code}
> There are probably two issues here:
> 1) that Hive support should be gracefully disabled if it the dependency not
> on the classpath as claimed by
> https://spark.apache.org/docs/latest/sql-data-sources-hive-tables.html
> 2) but at the very least the user should be able to see the exception to
> understand the issue, and take an action
>
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