https://github.com/google/xarray-beam

Distributed Xarray with Apache Beam
https://github.com/google/xarray-beam

beam dask xarray zarr

Last synced: 28 days ago
JSON representation

Distributed Xarray with Apache Beam

• Host: GitHub
• URL: https://github.com/google/xarray-beam
• Owner: google
• License: apache-2.0
• Created: 2021-05-11T20:48:07.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-10-23T18:12:08.000Z (about 2 months ago)
• Last Synced: 2024-10-24T01:35:46.912Z (about 2 months ago)
• Topics: beam, dask, xarray, zarr
• Language: Python
• Homepage: https://xarray-beam.readthedocs.io
• Size: 271 KB
• Stars: 135
• Watchers: 7
• Forks: 7
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

• Awesome-Earth-Artificial-Intelligence - Xarray-Beam - Python library for building Apache Beam pipelines with Xarray datasets. (Tools)

README

        
# Xarray-Beam

Xarray-Beam is a Python library for building

[Apache Beam](https://beam.apache.org/) pipelines with

[Xarray](http://xarray.pydata.org/en/stable/) datasets.

The project aims to facilitate data transformations and analysis on large-scale

multi-dimensional labeled arrays, such as:

-   Ad-hoc computation on Xarray data, by dividing a `xarray.Dataset` into many

    smaller pieces ("chunks").

-   Adjusting array chunks, using the

    [Rechunker algorithm](https://rechunker.readthedocs.io/en/latest/algorithm.html).

-   Ingesting large, multi-dimensional array datasets into an analysis-ready,

    cloud-optimized format, namely [Zarr](https://zarr.readthedocs.io/) (see

    also [Pangeo Forge](https://github.com/pangeo-forge/pangeo-forge-recipes)).

-   Calculating statistics (e.g., "climatology") across distributed datasets

    with arbitrary groups.

For more about our approach and how to get started,

**[read the documentation](https://xarray-beam.readthedocs.io/)**!

**Warning: Xarray-Beam is a sharp tool 🔪**

Xarray-Beam is relatively new, and focused on expert users:

-   We use it extensively at Google for processing large-scale weather datasets,

    but there is not yet a vibrant external community.

-   It provides low-level abstractions that facilitate writing very large

    scale data pipelines (e.g., 100+ TB), but by design it requires explicitly

    thinking about how every operation is parallelized.

## Installation

Xarray-Beam requires recent versions of immutabledict, Xarray, Dask, Rechunker,

Zarr, and Apache Beam. For best performance when writing Zarr files, use Xarray

0.19.0 or later.

## Disclaimer

Xarray-Beam is an experiment that we are sharing with the outside world in the

hope that it will be useful. It is not a supported Google product. We welcome

feedback, bug reports and code contributions, but cannot guarantee they will be

addressed.

See the "Contribution guidelines" for more.

## Credits

Contributors:

-   Stephan Hoyer

-   Jason Hickey

-   Cenk Gazen

-   Alex Merose