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Real-time statistic analytics for the WLCG Transfers Dashboard with Espe

The WLCG Data Transfer Dashboard is monitoring the data movement, which are generated by the LHC experiments, between sites and scientists around the world. Currently all the transfer information data are recorded inside an Oracle database and the statistics are computed on a regular basis using PL/...

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Autor principal: Georgiou, Maria Varvara
Lenguaje:eng
Publicado: 2014
Materias:
Acceso en línea:http://cds.cern.ch/record/1753831
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author Georgiou, Maria Varvara
author_facet Georgiou, Maria Varvara
author_sort Georgiou, Maria Varvara
collection CERN
description The WLCG Data Transfer Dashboard is monitoring the data movement, which are generated by the LHC experiments, between sites and scientists around the world. Currently all the transfer information data are recorded inside an Oracle database and the statistics are computed on a regular basis using PL/SQL procedures. This is a solid and reliable solution, but it can be improved because the PL/SQL procedures are not scaling with the increasing data volume and also the statistics re-computation may take days/weeks. This project aims to integrate Esper, an open-source in-memory processing engine, to the existing work flow to allow a real-time computation and visualization on fresh data and to speed-up all the statistics generation. This project is part of the WLCG monitoring analytics framework evolution.
id cern-1753831
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2014
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spelling cern-17538312019-09-30T06:29:59Zhttp://cds.cern.ch/record/1753831engGeorgiou, Maria VarvaraReal-time statistic analytics for the WLCG Transfers Dashboard with EspeComputing and ComputersThe WLCG Data Transfer Dashboard is monitoring the data movement, which are generated by the LHC experiments, between sites and scientists around the world. Currently all the transfer information data are recorded inside an Oracle database and the statistics are computed on a regular basis using PL/SQL procedures. This is a solid and reliable solution, but it can be improved because the PL/SQL procedures are not scaling with the increasing data volume and also the statistics re-computation may take days/weeks. This project aims to integrate Esper, an open-source in-memory processing engine, to the existing work flow to allow a real-time computation and visualization on fresh data and to speed-up all the statistics generation. This project is part of the WLCG monitoring analytics framework evolution.CERN-STUDENTS-Note-2014-180oai:cds.cern.ch:17538312014-09-05
spellingShingle Computing and Computers
Georgiou, Maria Varvara
Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title_full Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title_fullStr Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title_full_unstemmed Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title_short Real-time statistic analytics for the WLCG Transfers Dashboard with Espe
title_sort real-time statistic analytics for the wlcg transfers dashboard with espe
topic Computing and Computers
url http://cds.cern.ch/record/1753831
work_keys_str_mv AT georgioumariavarvara realtimestatisticanalyticsforthewlcgtransfersdashboardwithespe