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https://issues.apache.org/jira/browse/SPARK-25147?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16743590#comment-16743590
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Hyukjin Kwon commented on SPARK-25147:
--------------------------------------
[~msukmanowsky], can you try to set an environment variable
`OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES`, and try?
> GroupedData.apply pandas_udf crashing
> -------------------------------------
>
> Key: SPARK-25147
> URL: https://issues.apache.org/jira/browse/SPARK-25147
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.1
> Environment: OS: Mac OS 10.13.6
> Python: 2.7.15, 3.6.6
> PyArrow: 0.10.0
> Pandas: 0.23.4
> Numpy: 1.15.0
> Reporter: Mike Sukmanowsky
> Priority: Major
>
> Running the following example taken straight from the docs results in
> {{org.apache.spark.SparkException: Python worker exited unexpectedly
> (crashed)}} for reasons that aren't clear from any logs I can see:
> {code:java}
> from pyspark.sql import SparkSession
> from pyspark.sql import functions as F
> spark = (
> SparkSession
> .builder
> .appName("pandas_udf")
> .getOrCreate()
> )
> df = spark.createDataFrame(
> [(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)],
> ("id", "v")
> )
> @F.pandas_udf("id long, v double", F.PandasUDFType.GROUPED_MAP)
> def normalize(pdf):
> v = pdf.v
> return pdf.assign(v=(v - v.mean()) / v.std())
> (
> df
> .groupby("id")
> .apply(normalize)
> .show()
> )
> {code}
> See output.log for
> [stacktrace|https://gist.github.com/msukmanowsky/b9cb6700e8ccaf93f265962000403f28].
>
>
>
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