I think just match the Column’s expr as UnresolvedAttribute and use UnresolvedAttribute’s name to match schema’s field name is enough.
Seems no need to regard expr as a more general one. :) On May 30, 2015 at 11:14:05 PM, Girardot Olivier (o.girar...@lateral-thoughts.com) wrote: Jira done : https://issues.apache.org/jira/browse/SPARK-7969 I've already started working on it but it's less trivial than it seems because I don't exactly now the inner workings of the catalog, and how to get the qualified name of a column to match it against the schema/catalog. Regards, Olivier. Le sam. 30 mai 2015 à 09:54, Reynold Xin <r...@databricks.com> a écrit : Yea would be great to support a Column. Can you create a JIRA, and possibly a pull request? On Fri, May 29, 2015 at 2:45 AM, Olivier Girardot <o.girar...@lateral-thoughts.com> wrote: Actually, the Scala API too is only based on column name Le ven. 29 mai 2015 à 11:23, Olivier Girardot <o.girar...@lateral-thoughts.com> a écrit : Hi, Testing a bit more 1.4, it seems that the .drop() method in PySpark doesn't seem to accept a Column as input datatype : .join(only_the_best, only_the_best.pol_no == df.pol_no, "inner").drop(only_the_best.pol_no)\ File "/usr/local/lib/python2.7/site-packages/pyspark/sql/dataframe.py", line 1225, in drop jdf = self._jdf.drop(colName) File "/usr/local/lib/python2.7/site-packages/py4j/java_gateway.py", line 523, in __call__ (new_args, temp_args) = self._get_args(args) File "/usr/local/lib/python2.7/site-packages/py4j/java_gateway.py", line 510, in _get_args temp_arg = converter.convert(arg, self.gateway_client) File "/usr/local/lib/python2.7/site-packages/py4j/java_collections.py", line 490, in convert for key in object.keys(): TypeError: 'Column' object is not callable It doesn't seem very consistent with rest of the APIs - and is especially annoying when executing joins - because drop("my_key") is not a qualified reference to the column. What do you think about changing that ? or what is the best practice as a workaround ? Regards, Olivier.
