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https://issues.apache.org/jira/browse/SPARK-7903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Armbrust updated SPARK-7903:
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Target Version/s: 1.6.0 (was: 1.5.0)
> PythonUDT shouldn't get serialized on the Scala side
> ----------------------------------------------------
>
> Key: SPARK-7903
> URL: https://issues.apache.org/jira/browse/SPARK-7903
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.4.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
>
> A round trip for a pure Python UDT should be: Python UDT -> Python SQL
> internal types -> Scala/Java SQL internal types -> transformation ->
> Scala/Java SQL internal types -> Python SQL internal types -> Python UDT. So
> the serialization shouldn't be invoked on the Scala side if no Scala code is
> applied to the UDT.
> Code (from [~rams]) to reproduce this bug:
> {code}
> from pyspark.mllib.linalg import SparseVector
> from pyspark.sql.functions import udf
> from pyspark.sql.types import IntegerType
> df = sqlContext.createDataFrame([(SparseVector(2, {0: 0.0}),)], ["features"])
> sz = udf(lambda s: s.size, IntegerType())
> df.select(sz(df.features).alias("sz")).collect()
> {code}
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