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A Prototype U.S. CMS analysis facility

Project description

Coffea-casa - A Prototype U.S. CMS analysis facility for Columnar Object Framework For Effective Analysis

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About Coffea-casa

The prototype analysis facility provides services for “low latency columnar analysis”, enabling rapid processing of data in a column-wise fashion. These services, based on Dask and Jupyter notebooks, aim to dramatically lower time for analysis and provide an easily-scalable and user-friendly computational environment that will simplify, facilitate, and accelerate the delivery of HEP results. The facility is built on top of a Kubernetes cluster and integrates dedicated resources with resources allocated via fairshare through the local HTCondor system. In addition to the user-facing interfaces such as Dask, the facility also manages access control through single-sign-on and authentication & authorization for data access. The notebooks in this repository and Coffea-casa tutorials include simple HEP analysis examples, managed interactively in a Jupyter notebook and scheduled on Dask workers and accessing both public and protected data.

Contact us

Interested? You can reach us in Github Discussions or in IRIS-HEP Slack channel.

Docker images used for Coffea-casa

Latest DockerHub Images:

Image Description Size Pulls Version Layers
coffea-casa Dask scheduler image for coffea-casa hub
coffea-casa-analysis Dask worker image for coffea-casa hub

Image tagging and "continuous building"

This repository uses GitHub Actions to build images, run tests, and push images to DockerHub (Docker image tags are syncronised with Coffea-casa releases).

  1. Tags pushed to GitHub represent "production" releases with corresponding tags on dockerhub coffeateam/coffea-casa:x.x.x and coffeateam/coffea-casa-analysis:x.x.x. The latest tag also corresponds to the most recent GitHub tag.

Please note we are using date-based versioning for Coffea-casa Docker images and Pypi module.

References

  • Coffea-casa: an analysis facility prototype, M. Adamec, G. Attebury, K. Bloom, B. Bockelman, C. Lundstedt, O. Shadura and J. Thiltges, arXiv 2103.01871 (02 Mar 2021).
  • PyHEP 2020 coffea-casa proceedings: DOI
  • The PyHEP 2020 introductory Youtube video is here.

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