Hi Andy,
Broadcasting is really a computational concept rather than one related to
memory representation / data structures -- we haven't developed significant
computational libraries in Apache Arrow yet, but it is within scope for the
project.
In C++ I have anticipated adding an object model for
Numpy uses the concept of broadcasting to perform math operations on arrays
of different sizes:
https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html
A good example is multiplying an array by a single literal value or
comparing an array to a single value.
I'm in the process of converting
@Kou, automated commits / PRs to trigger Appveyor/Travis CI are most
likely part of the solution, but there are other issues.
We should start a Google document or something to enumerate all the
things we want to implement and identify the technical issues with
each thing. For example, at present,
Hi,
How about creating a pull request to apache/arrow-dist with
changes to use the latest apache/arrow? (A sample script
exists at the end.)
If the pull request is created, we can test packaging with
the latest apache/arrow on Travis CI. If we add the
following configuration to .travis.yml in apa
Hello all,
I strongly support Wes' points about having better automated feedback in our
build chain is essential, independent from the tool we use to make the builds.
As it sadly seems that our newly uploaded Arrow wheels for OSX are broken, I'm
going to start there and add them to the build ma
Uwe L. Korn created ARROW-2352:
--
Summary: [C++/Python] Test OSX packaging in Travis matrix
Key: ARROW-2352
URL: https://issues.apache.org/jira/browse/ARROW-2352
Project: Apache Arrow
Issue Type:
Also works for me
On Sat, Mar 24, 2018, at 1:34 AM, Bryan Cutler wrote:
> Sounds good to me
>
> On Fri, Mar 23, 2018, 11:10 AM Li Jin wrote:
>
> > Works for me. Thanks!
> >
> > On Fri, Mar 23, 2018 at 2:03 PM, Wes McKinney wrote:
> >
> > > hi folks,
> > >
> > > With the USA DST transition, the
