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https://issues.apache.org/jira/browse/SPARK-16918?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15411282#comment-15411282
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Hyukjin Kwon commented on SPARK-16918:
--------------------------------------
FYI, it seems fine in current master fortunately.
{code}
>>> N = 100
>>> df = sqlContext.createDataFrame([{'value': 0}])
>>> udf_columns = [pyspark.sql.functions.udf(lambda x: 0)('value') for _ in
>>> range(N)]
>>> df.select(udf_columns).take(1)
[Row(<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0', <lambda>(value)=u'0', <lambda>(value)=u'0',
<lambda>(value)=u'0')]
{code}
> Weird error when selecting more than 100 spark udf columns
> ----------------------------------------------------------
>
> Key: SPARK-16918
> URL: https://issues.apache.org/jira/browse/SPARK-16918
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.6.1
> Reporter: Phi Hung LE
>
> Starting with a simple spark dataframe with only one value, I create N simple
> udf columns.
> {code}
> N = 100
> df = sqlContext.createDataFrame([{'value': 0}])
> udf_columns = [pyspark.sql.functions.udf(lambda x: 0)('value') for _ in
> range(N)]
> df.select(udf_columns).take(1)
> {code}
> For N <= 100 this code works perfectly. But as soon as N >= 101, I found the
> following error
> {code}
> Py4JJavaError: An error occurred while calling
> z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
> in stage 34.0 failed 1 times, most recent failure: Lost task 0.0 in stage
> 34.0 (TID 50, localhost): java.lang.UnsupportedOperationException: Cannot
> evaluate expression: PythonUDF#<lambda>(input[0, LongType])
> at
> org.apache.spark.sql.catalyst.expressions.Unevaluable$class.genCode(Expression.scala:239)
> at org.apache.spark.sql.execution.PythonUDF.genCode(python.scala:44)
> at
> org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$gen$2.apply(Expression.
> {code}
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