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Development of noSQL data storage for the ATLAS PanDA Monitoring System

For several years the PanDA Workload Management System has been the basis for distributed production and analysis for the ATLAS experiment at the LHC. Since the start of data taking PanDA usage has ramped up steadily, typically exceeding 500k completed jobs/day by June 2011. The associated monitorin...

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Autor principal: Potekhin, Maxim
Lenguaje:eng
Publicado: 2011
Materias:
Acceso en línea:http://cds.cern.ch/record/1397816
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author Potekhin, Maxim
author_facet Potekhin, Maxim
author_sort Potekhin, Maxim
collection CERN
description For several years the PanDA Workload Management System has been the basis for distributed production and analysis for the ATLAS experiment at the LHC. Since the start of data taking PanDA usage has ramped up steadily, typically exceeding 500k completed jobs/day by June 2011. The associated monitoring data volume has been rising as well, to levels that present a new set of challenges in the areas of database scalability and monitoring system performance and efficiency. These challenges are being met with a R&D effort aimed at implementing a scalable and efficient monitoring data storage based on a noSQL solution (Cassandra). We present our motivations for using this technology, as well as data design and the techniques used for efficient indexing of the data. We also discuss the hardware requirements as they were determined by testing with actual data and realistic loads.
id cern-1397816
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2011
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spelling cern-13978162019-09-30T06:29:59Zhttp://cds.cern.ch/record/1397816engPotekhin, MaximDevelopment of noSQL data storage for the ATLAS PanDA Monitoring SystemDetectors and Experimental TechniquesFor several years the PanDA Workload Management System has been the basis for distributed production and analysis for the ATLAS experiment at the LHC. Since the start of data taking PanDA usage has ramped up steadily, typically exceeding 500k completed jobs/day by June 2011. The associated monitoring data volume has been rising as well, to levels that present a new set of challenges in the areas of database scalability and monitoring system performance and efficiency. These challenges are being met with a R&D effort aimed at implementing a scalable and efficient monitoring data storage based on a noSQL solution (Cassandra). We present our motivations for using this technology, as well as data design and the techniques used for efficient indexing of the data. We also discuss the hardware requirements as they were determined by testing with actual data and realistic loads.ATL-SOFT-PROC-2011-044oai:cds.cern.ch:13978162011-11-10
spellingShingle Detectors and Experimental Techniques
Potekhin, Maxim
Development of noSQL data storage for the ATLAS PanDA Monitoring System
title Development of noSQL data storage for the ATLAS PanDA Monitoring System
title_full Development of noSQL data storage for the ATLAS PanDA Monitoring System
title_fullStr Development of noSQL data storage for the ATLAS PanDA Monitoring System
title_full_unstemmed Development of noSQL data storage for the ATLAS PanDA Monitoring System
title_short Development of noSQL data storage for the ATLAS PanDA Monitoring System
title_sort development of nosql data storage for the atlas panda monitoring system
topic Detectors and Experimental Techniques
url http://cds.cern.ch/record/1397816
work_keys_str_mv AT potekhinmaxim developmentofnosqldatastoragefortheatlaspandamonitoringsystem