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https://issues.apache.org/jira/browse/SPARK-12981?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Davies Liu resolved SPARK-12981.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12127
[https://github.com/apache/spark/pull/12127]
> Dataframe distinct() followed by a filter(udf) in pyspark throws a casting
> error
> --------------------------------------------------------------------------------
>
> Key: SPARK-12981
> URL: https://issues.apache.org/jira/browse/SPARK-12981
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.6.0
> Environment: Running on Mac OSX (El Capitan) with Spark 1.6 (Java 1.8)
> Reporter: Tom Arnfeld
> Priority: Critical
> Fix For: 2.0.0
>
>
> We noticed a regression when testing out an upgrade of Spark 1.6 for our
> systems, where pyspark throws a casting exception when using `filter(udf)`
> after a `distinct` operation on a DataFrame. This does not occur on Spark 1.5.
> Here's a little notebook that demonstrates the exception clearly...
> https://gist.github.com/tarnfeld/ab9b298ae67f697894cd
> Though for the sake of here... the following code will throw an exception...
> {code}
> data.select(col("a")).distinct().filter(my_filter(col("a"))).count()
> {code}
> {code}
> java.lang.ClassCastException:
> org.apache.spark.sql.catalyst.plans.logical.Project cannot be cast to
> org.apache.spark.sql.catalyst.plans.logical.Aggregate
> {code}
> Whereas not using a UDF does not throw any errors...
> {code}
> data.select(col("a")).distinct().filter("a = 1").count()
> {code}
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