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Posted to issues@spark.apache.org by "Lekshmi Ramachandran (Jira)" <ji...@apache.org> on 2021/08/22 02:30:00 UTC
[jira] [Created] (SPARK-36554) Error message while trying to use
spark functions directly on dataframe columns without using select
expression
Lekshmi Ramachandran created SPARK-36554:
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Summary: Error message while trying to use spark functions directly on dataframe columns without using select expression
Key: SPARK-36554
URL: https://issues.apache.org/jira/browse/SPARK-36554
Project: Spark
Issue Type: Bug
Components: Documentation, Examples, PySpark
Affects Versions: 3.1.1
Reporter: Lekshmi Ramachandran
The below code generates a dataframe successfully . Here make_date function is used inside a select expression
from pyspark.sql.functions import expr, sum as sum_, max as max_
df = spark.createDataFrame([(2020, 6, 26), (1000, 2, 29), (-44, 1, 1)],['Y', 'M', 'D'])
df.select("*",expr("make_date(Y,M,D) as lk")).show()
The below code fails with a message "cannot import name 'make_date' from 'pyspark.sql.functions'" . Here the make_date function is directly called on dataframe columns without select expression
from pyspark.sql.functions import expr, make_date
df = spark.createDataFrame([(2020, 6, 26), (1000, 2, 29), (-44, 1, 1)],['Y', 'M', 'D'])
df.select(make_date(df.Y,df.M,df.D).alias("datefield")).show()
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