| Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
|---|---|---|
| Article Number | 02016 | |
| Number of page(s) | 7 | |
| Section | 2 - Offline Computing | |
| DOI | https://doi.org/10.1051/epjconf/202024502016 | |
| Published online | 16 November 2020 | |
https://doi.org/10.1051/epjconf/202024502016
Prompt calibration automation at Belle II
School of Physics (David Caro Building), The University of Melbourne, VIC 3010, Australia
* e-mail: david.dosssett@unimelb.edu.au
† e-mail: martines@unimelb.edu.au
Published online: 16 November 2020
The Belle II detector began collecting data from e+e− collisions at the SuperKEKB electron-positron collider in March 2019. Belle II aims to collect a data sample 50 times larger than the previous generation of B-factories. For Belle II analyses to be competitive it is crucial that calibration payloads for this data are calculated promptly prior to data reconstruction. To accomplish this goal a Python plugin package has been developed based on the open-source Apache Airflow package; using Directed Acyclic Graphs (DAGs) to describe the ordering of processes and Flask to provide administration and job submission web pages. DAGs for calibration process submission, monitoring of incoming data files, and validation of calibration payloads have all been created to help automate the calibration procedure. Flask plugin classes have been developed to extend the built-in Airflow administration and monitoring web pages. Authentication was included through the use of the pre-existing X.509 grid certificates of Belle II users.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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