The changes look good to me. Jenkins is somehow not responding. Will merge
once Jenkins comes back happy.
On Fri, Apr 24, 2015 at 2:38 AM, Olivier Girardot <
o.girar...@lateral-thoughts.com> wrote:
> done : https://github.com/apache/spark/pull/5683 and
> https://issues.apache.org/jira/browse/SPA
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.girar...@lateral-thoughts.com> a écrit :
> I'll try thanks
>
> Le ven. 24 avr. 2015 à 00:09, Reynold Xin a écrit :
>
>> You can do it simil
I'll try thanks
Le ven. 24 avr. 2015 à 00:09, Reynold Xin 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.girar...@
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.girar...@lateral-thoughts.com> wrote:
> I found another way setting a SPARK_HOME on a release
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 p
You need to first have the Spark assembly jar built with "sbt/sbt
assembly/assembly"
Then usually I go into python/run-tests and comment out the non-SQL tests:
#run_core_tests
run_sql_tests
#run_mllib_tests
#run_ml_tests
#run_streaming_tests
And then you can run "python/run-tests"
On Thu, Ap
What is the way of testing/building the pyspark part of Spark ?
Le jeu. 23 avr. 2015 à 22:06, Olivier Girardot <
o.girar...@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 a écrit :
>
>> Ah damn. We need t
yep :) I'll open the jira when I've got the time.
Thanks
Le jeu. 23 avr. 2015 à 19:31, Reynold Xin 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.girar...@lateral-thoughts.com> wrote:
>
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.girar...@lateral-thoughts.com> wrote:
> Yep no problem, but I can't seem to find the coalesce fonction in
> pyspark.sql.{*, functions, types or whatever :) }
>
>
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.girar...@lateral-thoughts.com> a écrit :
> a UDF might be a good idea no ?
>
> Le lun. 20 avr. 2015 à 11:17, Olivier Gir
It is actually different.
coalesce expression is to pick the first value that is not null:
https://msdn.microsoft.com/en-us/library/ms190349.aspx
Would be great to update the documentation for it (both Scala and Java) to
explain that it is different from coalesce function on a DataFrame/RDD. Do
y
I think I found the Coalesce you were talking about, but this is a catalyst
class that I think is not available from pyspark
Regards,
Olivier.
Le mer. 22 avr. 2015 à 11:56, Olivier Girardot <
o.girar...@lateral-thoughts.com> a écrit :
> Where should this *coalesce* come from ? Is it related to
Where should this *coalesce* come from ? Is it related to the partition
manipulation coalesce method ?
Thanks !
Le lun. 20 avr. 2015 à 22:48, Reynold Xin a écrit :
> Ah ic. You can do something like
>
>
> df.select(coalesce(df("a"), lit(0.0)))
>
> On Mon, Apr 20, 2015 at 1:44 PM, Olivier Girardo
Ah ic. You can do something like
df.select(coalesce(df("a"), lit(0.0)))
On Mon, Apr 20, 2015 at 1:44 PM, Olivier Girardot <
o.girar...@lateral-thoughts.com> wrote:
> From PySpark it seems to me that the fillna is relying on Java/Scala code,
> that's why I was wondering.
> Thank you for answerin
>From PySpark it seems to me that the fillna is relying on Java/Scala code,
that's why I was wondering.
Thank you for answering :)
Le lun. 20 avr. 2015 à 22:22, Reynold Xin a écrit :
> You can just create fillna function based on the 1.3.1 implementation of
> fillna, no?
>
>
> On Mon, Apr 20, 20
You can just create fillna function based on the 1.3.1 implementation of
fillna, no?
On Mon, Apr 20, 2015 at 2:48 AM, Olivier Girardot <
o.girar...@lateral-thoughts.com> wrote:
> a UDF might be a good idea no ?
>
> Le lun. 20 avr. 2015 à 11:17, Olivier Girardot <
> o.girar...@lateral-thoughts.co
a UDF might be a good idea no ?
Le lun. 20 avr. 2015 à 11:17, Olivier Girardot <
o.girar...@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 ?
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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