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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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Lenguaje: | eng |
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2014
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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 |
record_format | invenio |
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 |