Hi Jörn,
I agree with your concerns about NaN. There was a discussion about this in
https://github.com/apache/arrow/pull/7193
I will try and make time this weekend to look at the current implementation
and your suggestions around DictionaryArray.
Hopefully, other contributors that are more
Hi Antoine
> Yes, that is our plan. Since this is going to be done on the storage-,
> > server-side, this would be transparent to the client. So our main concern
> > is whether this be OK from the design perspective, and could this
> > eventually be merged upstream?
>
> Arrow datasets have no
CRAN has finally accepted the R package release, so I think that closes the
post-release tasks for 1.0.1
Neal
On Mon, Aug 24, 2020 at 1:58 PM Krisztián Szűcs
wrote:
> Thank you Neal!
>
> The conda packages have been updated as well.
>
> 2. [done] upload source
> 3. [done] upload binaries
>
I ran into a few issues with the rust sort kernels and would like to
discuss possible solutions.
1. When sorting by multiple columns (lexsort_to_indices) the Float32
and Float64 data types are not supported because the implementation
relies on the OrdArray trait. This trait is not implemented
Arrow Build Report for Job nightly-2020-08-28-0
All tasks:
https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-08-28-0
Failed Tasks:
- conda-osx-clang-py36:
URL:
https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-08-28-0-azure-conda-osx-clang-py36
-
Le 27/08/2020 à 21:55, Ivo Jimenez a écrit :
> Hi Antoine,
>
>> Our main concern is that this new arrow::dataset::RadosFormat class will
>> be
>>> deriving from the arrow::dataset::FileFormat class, which seems to raise
>> a
>>> conceptual mismatch as there isn’t really a RADOS format but
Hi François,
Thank you very much for your response with very helpful information.
I realized that this command is launched as follows at
https://ci.ursalabs.org/#/builders/73/builds/100/steps/3/logs/stdio
$ archery benchmark diff --output=diff.json
--suite-filter=parquet-encoding-benchmark