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From Olivier Girardot <o.girar...@lateral-thoughts.com>
Subject Re: Dataframe.fillna from 1.3.0
Date Fri, 24 Apr 2015 09:38:14 GMT
done : https://github.com/apache/spark/pull/5683 and
https://issues.apache.org/jira/browse/SPARK-7118
thx

Le ven. 24 avr. 2015 à 07:34, Olivier Girardot <
o.girardot@lateral-thoughts.com> a écrit :

> I'll try thanks
>
> Le ven. 24 avr. 2015 à 00:09, Reynold Xin <rxin@databricks.com> a écrit :
>
>> You can do it similar to the way countDistinct is done, can't you?
>>
>>
>> https://github.com/apache/spark/blob/master/python/pyspark/sql/functions.py#L78
>>
>>
>>
>> On Thu, Apr 23, 2015 at 1:59 PM, Olivier Girardot <
>> o.girardot@lateral-thoughts.com> wrote:
>>
>>> I found another way setting a SPARK_HOME on a released version and
>>> launching an ipython to load the contexts.
>>> I may need your insight however, I found why it hasn't been done at the
>>> same time, this method (like some others) uses a varargs in Scala and for
>>> now the way functions are called only one parameter is supported.
>>>
>>> So at first I tried to just generalise the helper function "_" in the
>>> functions.py file to multiple arguments, but py4j's handling of varargs
>>> forces me to create an Array[Column] if the target method is expecting
>>> varargs.
>>>
>>> But from Python's perspective, we have no idea of whether the target
>>> method will be expecting varargs or just multiple arguments (to un-tuple).
>>> I can create a special case for "coalesce" or "for method that takes of
>>> list of columns as arguments" considering they will be varargs based (and
>>> therefore needs an Array[Column] instead of just a list of arguments)
>>>
>>> But this seems very specific and very prone to future mistakes.
>>> Is there any way in Py4j to know before calling it the signature of a
>>> method ?
>>>
>>>
>>> Le jeu. 23 avr. 2015 à 22:17, Olivier Girardot <
>>> o.girardot@lateral-thoughts.com> a écrit :
>>>
>>>> What is the way of testing/building the pyspark part of Spark ?
>>>>
>>>> Le jeu. 23 avr. 2015 à 22:06, Olivier Girardot <
>>>> o.girardot@lateral-thoughts.com> a écrit :
>>>>
>>>>> yep :) I'll open the jira when I've got the time.
>>>>> Thanks
>>>>>
>>>>> Le jeu. 23 avr. 2015 à 19:31, Reynold Xin <rxin@databricks.com>
a
>>>>> écrit :
>>>>>
>>>>>> Ah damn. We need to add it to the Python list. Would you like to
give
>>>>>> it a shot?
>>>>>>
>>>>>>
>>>>>> On Thu, Apr 23, 2015 at 4:31 AM, Olivier Girardot <
>>>>>> o.girardot@lateral-thoughts.com> wrote:
>>>>>>
>>>>>>> Yep no problem, but I can't seem to find the coalesce fonction
in
>>>>>>> pyspark.sql.{*, functions, types or whatever :) }
>>>>>>>
>>>>>>> Olivier.
>>>>>>>
>>>>>>> Le lun. 20 avr. 2015 à 11:48, Olivier Girardot <
>>>>>>> o.girardot@lateral-thoughts.com> a écrit :
>>>>>>>
>>>>>>> > a UDF might be a good idea no ?
>>>>>>> >
>>>>>>> > Le lun. 20 avr. 2015 à 11:17, Olivier Girardot <
>>>>>>> > o.girardot@lateral-thoughts.com> a écrit :
>>>>>>> >
>>>>>>> >> Hi everyone,
>>>>>>> >> let's assume I'm stuck in 1.3.0, how can I benefit from
the
>>>>>>> *fillna* API
>>>>>>> >> in PySpark, is there any efficient alternative to mapping
the
>>>>>>> records
>>>>>>> >> myself ?
>>>>>>> >>
>>>>>>> >> Regards,
>>>>>>> >>
>>>>>>> >> Olivier.
>>>>>>> >>
>>>>>>> >
>>>>>>>
>>>>>>
>>>>>>
>>

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