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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2015/05/27 21:39:17 UTC

[jira] [Created] (SPARK-7903) PythonUDT shouldn't get serialized on the Scala side

Xiangrui Meng created SPARK-7903:
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             Summary: 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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