Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 04057 | |
Number of page(s) | 10 | |
Section | T4 - Data handling | |
DOI | https://doi.org/10.1051/epjconf/201921404057 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921404057
A prototype for the evolution of ATLAS EventIndex based on Apache Kudu storage
1
CERN,
Geneva,
Switzerland
2
Insitut de Fisica Corpuscular,
Valencia
Spain
3
University of Oxford,
Denys Wilkinson Bldg, Keble Rd, Oxford OX1 3RH,
United Kingdom
4
LAL, Université
Paris-Sud and CNRS/IN2P3,
Orsay,
France
5
Universidad Tecnica Federico Santa Maria,
Chile
6
Università di Genova and INFN, Genova, Italy
* e-mail: zbigniew.baranowski@cern.ch
** e-mail: luca.canali@cern.ch
*** e-mail: Alvaro.Fernandez@ific.uv.es
**** e-mail: elizabeth.gallas@physics.ox.ac.uk
† e-mail: carlos.garcia@ific.uv.es
‡ e-mail: sgonzale@ific.uv.es
§ e-mail: Julius.Hrivnac@cern.ch
¶ e-mail: Fedor.Prokoshin@cern.ch
‖ e-mail: Grigori.Rybkine@cern.ch
** e-mail: Jose.Salt@ific.uv.es
†† e-mail: Javier.Sanchez@ific.uv.es
‡‡ e-mail: Dario.Barberis@cern.ch
Published online: 17 September 2019
The ATLAS EventIndex has been in operation since the beginning of LHC Run 2 in 2015. Like all software projects, its components have been constantly evolving and improving in performance. The main data store in Hadoop, based on MapFiles and HBase, can work for the rest of Run 2 but new solutions are explored for the future. Kudu offers an interesting environment, with a mixture of BigData and relational database features, which look promising at the design level. This environment is used to build a prototype to measure the scaling capabilities as functions of data input rates, total data volumes and data query and retrieval rates. In this proceedings we report on the selected data schemas and on the current performance measurements with the Kudu prototype.
© The Authors, published by EDP Sciences, 2019
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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