go-py-arrow-bridge
arrow-julia
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| go-py-arrow-bridge | arrow-julia | |
|---|---|---|
| 1 | 4 | |
| 18 | 277 | |
| - | 1.8% | |
| 0.0 | 6.2 | |
| almost 5 years ago | 17 days ago | |
| Go | Julia | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
go-py-arrow-bridge
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Apache Arrow 3.0.0 Release
Not only in between processes, but also in between languages in a single process. In this POC I spun up a Python interpreter in Go and can pass the Arrow data buffer between processes in constant time. https://github.com/nickpoorman/go-py-arrow-bridge
arrow-julia
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Julia 1.8 has been released
For some examples of people porting existing C++ Fortran libraries to julia, you should check out https://github.com/JuliaLinearAlgebra/Octavian.jl, https://github.com/dgleich/GenericArpack.jl, https://github.com/apache/arrow-julia (just off the top of my head). These are all ports of C++ or Fortran libraries that match (or exceed) performance of the original, and in the case of Arrow.jl is faster, more general, and 10x less code.
- How to adapt Arrow.Table columns (naturally per record batch basis) into CuArrays for GPU processing?
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Reading HDF5 Files
I guess current preferred format not feather, but arrow: https://github.com/JuliaData/Arrow.jl
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Apache Arrow 3.0.0 Release
Excited to see this release's official inclusion of the pure Julia Arrow implementation [1]!
It's so cool to be able mmap Arrow memory and natively manipulate it from within Julia with virtually no performance overhead. Since the Julia compiler can specialize on the layout of Arrow-backed types at runtime (just as it can with any other type), the notion of needing to build/work with a separate "compiler for fast UDFs" is rendered obsolete.
It feels pretty magical when two tools like this compose so well without either being designed with the other in mind - a testament to the thoughtful design of both :) mad props to Jacob Quinn for spearheading the effort to revive/restart Arrow.jl and get the package into this release.
[1] https://github.com/JuliaData/Arrow.jl
What are some alternatives?
arquero - Query processing and transformation of array-backed data tables.
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.