As far as I understood, the idea is not to fully remove memory mapping,
just turn the current mmap=True default arguments to mmap=False
The goal is mostly to provide consistent behaviour for end users. At the
moment users might face very different performances when they read locally
or on a networ
Le 11/05/2022 à 10:19, Alessandro Molina a écrit :
As far as I understood, the idea is not to fully remove memory mapping,
just turn the current mmap=True default arguments to mmap=False
The goal is mostly to provide consistent behaviour for end users. At the
moment users might face very diff
Hi dev@arrow,
Recently I've created and published a Java binding[1] to datafusion[2],
as part of datafusion-contrib projects[3]. I've updated the README.md[4]
so people can pick it up via maven[5] or gradle.
Any feedback or contributions are welcome!
[1]: https://github.com/datafusion-contrib/da
Hi!
Can you elaborate how the binding transfers data between Datafusion and
Java Arrow? If I'm reading the code correctly, it seems to be writing
an IPC stream?
Le 11/05/2022 à 11:20, Jiayu Liu a écrit :
Hi dev@arrow,
Recently I've created and published a Java binding[1] to datafusion[2
On Wed, May 11, 2022 at 6:01 AM Sutou Kouhei wrote:
>
> Hi,
>
> In
> "Re: [DISC][Release] More control on Release Candidates commits" on Tue, 10
> May 2022 13:27:09 +0200,
> Raul Cumplido wrote:
>
> > I still think there is some value in standardising the "feature freeze" on
> > new release
Hi all,
Our biweekly sync call is today at 12:00 noon Eastern time.
The Zoom meeting URL for this and other biweekly Arrow sync calls is:
https://zoom.us/j/87649033008?pwd=SitsRHluQStlREM0TjJVYkRibVZsUT09
Alternatively, enter this information into the Zoom website or app to
join the call:
Meetin
I would like to propose that we move the Ballista project to a new
top-level *arrow-ballista* repository.
The rationale for this (copied from the GitHub issue [1]) is:
- Decouple release process for DataFusion and Ballista
- Allow each project to have top-level documentation and user guides
@Vibhatha
> Are these computations computationally intensive? To quantify it, in
general
> do these workloads occupy majority of the time compared to the overall
> dataflow problem's execution time?
It varies a lot and depending on what the user is doing and can vary
anywhere between 5%
(e.g., a
Thanks Weston. This resolved issue 1 for me.
As for issue 2, I am now running
"ninja format lint clang-tidy lint_cpp_cli"
and it seems to still take a while (over 30min now), and the console shows
"
[2/4] cd /home/icexelloss/workspace/arrow/cpp/build && /usr/bin/python3.10
/home/icexelloss/worksp
I talked about these problems with my colleague Michal Nowakiewicz who
has been developing some of the C++ engine implementation over the
last year and a half, and he wrote up this document with some ideas
about task scheduling and control flow in the query engine for
everyone to look at and commen
Attendees:
Joris Van den Bossche
Ian Cook
Nic Crane
Raul Cumplido
Ian Joiner
David Li
Rok Mihevc
Dragoș Moldovan-Grünfeld
Aldrin Montana
Weston Pace
Eduardo Ponce
Matthew Topol
Jacob Wujciak
Discussion:
Eduardo: Draft PR with a guide showing how to create a new Arrow C++
compute kernel [1]
- R
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