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Hyukjin Kwon commented on SPARK-22980: -------------------------------------- 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. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org