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https://issues.apache.org/jira/browse/SPARK-22980?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16317100#comment-16317100
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Hyukjin Kwon commented on SPARK-22980:
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Could we just fix it by adding a simple note that the length of serises or
dataframe within pandas_udf is not of whole serises or dataframe but of batch
internally used, for now?
I think that's going to explain the difference of the results of len between
udf and pandas_udf more clearly because udf returns the length of the value
whereas pandas_udf returns the length of the batch.
> Using pandas_udf when inputs are not Pandas's Series or DataFrame
> -----------------------------------------------------------------
>
> Key: SPARK-22980
> URL: https://issues.apache.org/jira/browse/SPARK-22980
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Xiao Li
>
> {noformat}
> from pyspark.sql.functions import pandas_udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = pandas_udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> {noformat}
> from pyspark.sql.functions import udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> The results of pandas_udf are different from udf.
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