>
> First of all I would like to ask why we use both type_codes and child_ids
> for Union types. It seems that we can already cover the logical types a
> union has using type_codes alone. What’s the point of using child_ids?
The two are inverses of each other:
The work of converting Arrow Arrays, ChunkedArrays, RecordBatches and Tables to
ORC files is about 50% done. Now I have two questions.
First of all I would like to ask why we use both type_codes and child_ids for
Union types. It seems that we can already cover the logical types a union has
I'm not opposed to installing headers that provide access to some of
the kernel implementation internals (with the caveat that changes
won't go through a deprecation cycle, so caveat emptor). It might be
more sustainable to think about what kind of stable-ish public API
could be exported to
Hi - I've been looking through the Arrow specification format to look for
ways to allow zero-copy creation of Pandas DataFrames (beyond
`split_blocks`). Am I right in thinking that if you created an Arrow file
(let's say of `m` rows and `n` columns of `float64`s for now) as a single
RecordBatch
Hi Niranda,
SumImpl is a subclass of KernelState. Given a SumAggregateKernel, one can
produce zeroed KernelState using the `init` member, then operate on data
using the `consume`, `merge`, and `finalize` members. You can look at
ScalarAggExecutor for an example of how to get from a compute
Hi Ben,
We are building a distributed table abstraction on top of Arrow dataframes
called Cylon (https://github.com/cylondata/cylon). Currently we have a
simple aggregation and group-by operation implementation. But we felt like
we can give more functionality if we can import arrow kernels and
Ni Niranda,
What is the context of your work? if you're working inside the arrow
repository you shouldn't need to install headers before using them, and we
welcome PRs for new kernels. Otherwise, could you provide some details
about how your work is using Arrow as a dependency?
Ben Kietzman
On
Hi,
I was wondering if I could use the arrow/compute/kernels/*internal.h
headers in my work? I would like to reuse some of the kernel
implementations and kernel states.
With -DARROW_COMPUTE=ON, those headers are not added into the include dir.
I see that the *internal.h headers are skipped from
Arrow Build Report for Job nightly-2020-11-08-0
All tasks:
https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-11-08-0
Failed Tasks:
- conda-win-vs2017-py36:
URL:
https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-11-08-0-azure-conda-win-vs2017-py36
-
