| Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 7 | |
| Section | Offline Computing | |
| DOI | https://doi.org/10.1051/epjconf/202125103001 | |
| Published online | 23 August 2021 | |
https://doi.org/10.1051/epjconf/202125103001
Columnar data analysis with ATLAS analysis formats
1 Ludwig-Maximilians-Universität, München, Germany
2 Brookhaven National Laboratory, Upton, NY, USA
* e-mail: nihartma@cern.ch
Published online: 23 August 2021
Future analysis of ATLAS data will involve new small-sized analysis formats to cope with the increased storage needs. The smallest of these, named DAOD_PHYSLITE, has calibrations already applied to allow fast downstream analysis and avoid the need for further analysis-specific intermediate formats. This allows for application of the “columnar analysis” paradigm where operations are applied on a per-array instead of a per-event basis. We will present methods to read the data into memory, using Uproot, and also discuss I/O aspects of columnar data and alternatives to the ROOT data format. Furthermore, we will show a representation of the event data model using the Awkward Array package and present proof of concept for a simple analysis application.
© The Authors, published by EDP Sciences, 2021
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