The use case is to pass a Scalar created in Python to a kernel written in
C++ backend which supports arrow data types.
To support this I need to unwrap the Pyarrow Scalar to a C++ arrow Scalar.
With Regards,
Vibhatha Abeykoon
On Mon, Mar 22, 2021 at 11:15 PM Benjamin Kietzman
wrote:
> I'm not
Would MakeArray(array.data()) work for you?
On Mon, Mar 22, 2021, 23:00 Ying Zhou wrote:
> Hi,
>
> I know this is a very silly question here but I still prefer to see it
> resolved rather than working on it for a day:
>
> How shall I generate an std::shared_ptr from an Array&? Just taking
> the
I'm not sure what kind of unwrapping you are looking for, would
pyarrow.scalar and Scalar.as_py address your use case? For example,
pa.scalar(128) will wrap that integer into a Scalar
On Mon, Mar 22, 2021, 11:15 Vibhatha Abeykoon wrote:
> Hello,
>
> Is there a way to wrap and unwrap Scalars
Hi,
I know this is a very silly question here but I still prefer to see it resolved
rather than working on it for a day:
How shall I generate an std::shared_ptr from an Array&? Just taking the
address and constructing a shared_ptr from the pointer doesn’t work.
Ying
Le 22/03/2021 à 20:17, bobtins a écrit :
TL;DR: The Java implementation doesn't have generated flatbuffers code
under source control, and the code generation depends on an
unofficially-maintained Maven artifact. Other language implementations do
check in the generated code; would it make sense
TL;DR: The Java implementation doesn't have generated flatbuffers code
under source control, and the code generation depends on an
unofficially-maintained Maven artifact. Other language implementations do
check in the generated code; would it make sense for this to be done for
Java as well?
I'm
>
> Could you share the benchmark code/how the benchmark was run (does this
> account for JIT warm-up time)?
I just used the benchmark by the aircompressor project. They run the
benchmark for a lot of algorithms on a lot of datasets so I commented out
some to get faster results. You can find my
>
> I executed some of the benchmarks in the airlift/aircompressor project. I
> found that aircompressior achieves on average only about 72%
> throughput compared to the current version of the lz4-java JNI bindings
> when compressing. When decompressing the gap is even bigger with around 56%
>
Hello,
Is there a way to wrap and unwrap Scalars using the Cython API?
I am following the docs: https://arrow.apache.org/docs/python/extending.html
But I couldn't find an option. Not sure if I am following the correct docs.
With Regards,
Vibhatha Abeykoon,
PhD Candidate | Research Assistant,
Le 22/03/2021 à 15:29, Benjamin Wilhelm a écrit :
Also, I would like to resume the discussion about the Frame format vs the
Block format. There were 3 points for the Frame format by Antoine:
- it allows streaming compression and decompression (meaning you can
avoid loading a huge compressed
I executed some of the benchmarks in the airlift/aircompressor project. I
found that aircompressior achieves on average only about 72%
throughput compared to the current version of the lz4-java JNI bindings
when compressing. When decompressing the gap is even bigger with around 56%
throughout. See
+1
On Sun, Mar 21, 2021 at 7:08 PM paddy horan wrote:
> +1 (non-binding)
>
>
>
> From: Sutou Kouhei
> Sent: Sunday, March 21, 2021 4:34:43 PM
> To: dev@arrow.apache.org
> Subject: Re: [VOTE] Accept donation of Rust Ballista project
>
> +1 (binding)
>
> In
>
Arrow Build Report for Job nightly-2021-03-22-0
All tasks:
https://github.com/ursacomputing/crossbow/branches/all?query=nightly-2021-03-22-0
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