EPJ Web Conf.
Volume 245, 202024th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|Number of page(s)||6|
|Section||4 - Data Organisation, Management and Access|
|Published online||16 November 2020|
The ATLAS EventIndex for LHC Run 3
Physics Department of the University of Genoa and INFN Sezione di Genova, Via Dodecaneso 33, I-16146 Genova, Italy
2 Joint Institute for Nuclear Research, 6 Joliot-Curie St., Dubna, Moscow Region, 141980, Russia
3 CERN, 1211 Geneva 23, Switzerland
4 Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia CSIC, Valencia, Spain
5 Department of Physics, Oxford University, Oxford, United Kingdom
6 Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France
7 Department of Physics, University of Alberta, Edmonton AB, Canada
* Corresponding author: Dario.Barberis@cern.ch
© 2020 CERN for the benefit of the ATLAS Collaboration. CC-BY-4.0 license.
Published online: 16 November 2020
The ATLAS EventIndex was designed in 2012-2013 to provide a global event catalogue and limited event-level metadata for ATLAS analysis groups and users during the LHC Run 2 (2015-2018). It provides a good and reliable service for the initial use cases (mainly event picking) and several additional ones, such as production consistency checks, duplicate event detection and measurements of the overlaps of trigger chains and derivation datasets. The LHC Run 3, starting in 2021, will see increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. This proceeding describes the implementation of a new core storage service that will be able to provide at least the same functionality as the current one for increased data ingestion and search rates, and with increasing volumes of stored data. It is based on a set of HBase tables, with schemas derived from the current Oracle implementation, coupled to Apache Phoenix for data access; in this way we will add to the advantages of a BigData based storage system the possibility of SQL as well as NoSQL data access, allowing to re-use most of the existing code for metadata integration.
© 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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