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https://issues.apache.org/jira/browse/SPARK-7035?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14529890#comment-14529890
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Reynold Xin commented on SPARK-7035:
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I talked to more people offline about this also, and I think it is best not to
change anything now. One thing we should do is to update the documentation to
indicate the danger of using df.attribute, and have df["attribute"] be the
standard in our documentations.
We need to update
https://github.com/apache/spark/blob/master/docs/sql-programming-guide.md
[~kalle] do you want to submit a patch to update the documentation to warn
users?
> Drop __getattr__ on pyspark.sql.DataFrame
> -----------------------------------------
>
> Key: SPARK-7035
> URL: https://issues.apache.org/jira/browse/SPARK-7035
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 1.4.0
> Reporter: Kalle Jepsen
>
> I think the {{\_\_getattr\_\_}} method on the DataFrame should be removed.
> There is no point in having the possibility to address the DataFrames columns
> as {{df.column}}, other than the questionable goal to please R developers.
> And it seems R people can use Spark from their native API in the future.
> I see the following problems with {{\_\_getattr\_\_}} for column selection:
> * It's un-pythonic: There should only be one obvious way to solve a problem,
> and we can already address columns on a DataFrame via the {{\_\_getitem\_\_}}
> method, which in my opinion is by far superior and a lot more intuitive.
> * It leads to confusing Exceptions. When we mistype a method-name the
> {{AttributeError}} will say 'No such column ... '.
> * And most importantly: we cannot load DataFrames that have columns with the
> same name as any attribute on the DataFrame-object. Imagine having a
> DataFrame with a column named {{cache}} or {{filter}}. Calling {{df.cache()}}
> will be ambiguous and lead to broken code.
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