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https://issues.apache.org/jira/browse/ARROW-11?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney resolved ARROW-11.
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Resolution: Done
Resolved by INFRA-11370
> Mirror JIRA activity to dev@arrow.apache.org
> -
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https://issues.apache.org/jira/browse/ARROW-23?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15179232#comment-15179232
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Wes McKinney commented on ARROW-23:
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See patch https://github.com/apache/arrow/pull/15
>
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https://issues.apache.org/jira/browse/ARROW-23?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney reassigned ARROW-23:
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Assignee: Wes McKinney
> C++: Add logical "Column" container for chunked data
> ---
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https://issues.apache.org/jira/browse/ARROW-26?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney resolved ARROW-26.
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Resolution: Fixed
Resolved by https://github.com/apache/arrow/pull/12
> C++: Add developer instructions
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https://issues.apache.org/jira/browse/ARROW-10?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney resolved ARROW-10.
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Resolution: Fixed
Issue resolved by pull request 3
[https://github.com/apache/arrow/pull/3]
> Fix misma
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https://issues.apache.org/jira/browse/ARROW-15?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney resolved ARROW-15.
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Resolution: Fixed
Issue resolved by pull request 4
[https://github.com/apache/arrow/pull/4]
> Fix a nam
It's not like you are going to break an existing release.
On Thu, Mar 3, 2016 at 3:11 PM, Julien Le Dem wrote:
> sounds good.
>
> On Thu, Mar 3, 2016 at 1:17 PM, Jason Altekruse
> wrote:
>
> > +1
> >
> > On Thu, Mar 3, 2016 at 12:58 PM, Jacques Nadeau
> > wrote:
> >
> > > +1. Sounds good to
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https://issues.apache.org/jira/browse/ARROW-21?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wes McKinney resolved ARROW-21.
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Resolution: Fixed
Issue resolved by pull request 10
[https://github.com/apache/arrow/pull/10]
> C++: Ad
Returning to this discussion. I did some C++ prototyping
https://github.com/apache/arrow/pull/9
https://github.com/apache/arrow/pull/10
A handful of thoughts:
1) It is most useful for compatibility with other systems (e.g. Parquet --
see ARROW-22) to have required/optional in the type metadata,
sounds good.
On Thu, Mar 3, 2016 at 1:17 PM, Jason Altekruse
wrote:
> +1
>
> On Thu, Mar 3, 2016 at 12:58 PM, Jacques Nadeau
> wrote:
>
> > +1. Sounds good to me.
> >
> > On Thu, Mar 3, 2016 at 12:35 PM, P. Taylor Goetz
> > wrote:
> >
> > > +1
> > >
> > > I think CTR makes sense at this stage.
+1
On Thu, Mar 3, 2016 at 12:58 PM, Jacques Nadeau wrote:
> +1. Sounds good to me.
>
> On Thu, Mar 3, 2016 at 12:35 PM, P. Taylor Goetz
> wrote:
>
> > +1
> >
> > I think CTR makes sense at this stage. RTC would slow things down
> > considerably.
> >
> > -Taylor
> >
> > > On Mar 3, 2016, at 3:00
+1. Sounds good to me.
On Thu, Mar 3, 2016 at 12:35 PM, P. Taylor Goetz wrote:
> +1
>
> I think CTR makes sense at this stage. RTC would slow things down
> considerably.
>
> -Taylor
>
> > On Mar 3, 2016, at 3:00 PM, Julian Hyde wrote:
> >
> > +1
> >
> > Thanks for asking.
> >
> >
> >> On Mar 3,
+1
I think CTR makes sense at this stage. RTC would slow things down considerably.
-Taylor
> On Mar 3, 2016, at 3:00 PM, Julian Hyde wrote:
>
> +1
>
> Thanks for asking.
>
>
>> On Mar 3, 2016, at 11:22 AM, Wes McKinney wrote:
>>
>> hi folks,
>>
>> I'm going to have many C++ and Python pa
+1
Thanks for asking.
> On Mar 3, 2016, at 11:22 AM, Wes McKinney wrote:
>
> hi folks,
>
> I'm going to have many C++ and Python patches the next few weeks, any
> objections to proceeding in commit-then-review mode (particularly on the
> Python side) for the time being in the interest of expe
Serializing Spark DataFrame in either Java or Scala would suffice for the
use case, but there may be follow-on JIRAs to make the Arrow adapters more
accessible. pandas only needs access to flat schemas for now, for example,
so nested Spark SQL schemas could be handled in follow-up work.
Note: this
hi folks,
I'm going to have many C++ and Python patches the next few weeks, any
objections to proceeding in commit-then-review mode (particularly on the
Python side) for the time being in the interest of expediency? I will be
more than happy to collect feedback from merged patches into new JIRAs a
Hi Wes,
Thanks for raising the ticket. So it seems like Spark 2.0 will not have
support for Arrow.
Also does SPARK-13534 cover Arrow serialization for Spark's JAVA API, or do
we need to raise a separate ticket for that?
As of now, I only have a high-level understanding of Arrow and it's data
stru
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