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xarray-beam
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Distributed Xarray with Apache Beam
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xarray-beam
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# 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
