Jacob Quinn

> As @kou refers, it would be good to read documents at https://www.apache.org/legal/release-policy.html#releases and https://www.apache.org/foundation/voting.html at first. Hi @kiszk, yes, I'm familiar with the apache release policies and tried to...

So the tricky thing here is that the arrow format is _columnar_; so rows have to be collected and columns have to be "built" at some point to write the...

I don't think it's entirely unexpected, I think it's just a matter of the fact that the "processing" work is going so much faster than the IO work, which isn't...

I'm pretty sure `@time Arrow.write(output Tables.partitioner(f, eachline(myfile)) |> collect) # 0.002 seconds, 43 kb arrow file` isn't generating the same output "table" you're expecting.

> We need a vote for each new release before we publish a new release. It requires the followings: > > 1. We need to create a source package such...

Yeah, I'd like for this to be defined. DataFrames has a pretty decent [definition](https://github.com/JuliaData/DataFrames.jl/blob/main/src/abstractdataframe/abstractdataframe.jl#L422) that I think we could copy.

Sorry for the slow response here, but here's one way we could convert between the awkward array and a Julia array: ```julia julia> off = Arrow.Offsets(UInt8[], arr.layout.offsets) 3-element Arrow.Offsets{Int64}: (1,...

In general though, it's going to be, IMO, practically impossible to try and re-use arrow memory at the individual column/array level. There are two many factors that would complicate things....

cc: @sa-, @Moelf

Oof, yeah, this is tricky. Sorry for the delay in responding btw. We've had the same issue w/ JSON3 serializing; it's just tricky to know what kind of Matrix you...