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RIS citation export for MOPHA117: Big Data Archiving From Oracle to Hadoop

TY  - CONF
AU  - Prieto Barreiro, I.
AU  - Sobieszek, M.
ED  - White, Karen S.
ED  - Brown, Kevin A.
ED  - Dyer, Philip S.
ED  - Schaa, Volker RW
TI  - Big Data Archiving From Oracle to Hadoop
J2  - Proc. of ICALEPCS2019, New York, NY, USA, 05-11 October 2019
CY  - New York, NY, USA
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 17
LA  - english
AB  - The CERN Accelerator Logging Service (CALS) is used to persist data of around 2 million predefined signals coming from heterogeneous sources such as the electricity infrastructure, industrial controls like cryogenics and vacuum, or beam related data. This old Oracle based logging system will be phased out at the end of the LHC’s Long Shut-down 2 (LS2) and will be replaced by the Next CERN Accelerator Logging Service (NXCALS) which is based on Hadoop. As a consequence, the different data sources must be adapted to persist the data in the new logging system. This paper describes the solution implemented to archive into NXCALS the data produced by QPS (Quench Protection System) and SCADAR (Supervisory Control And Data Acquisition Relational database) systems, which generate a total of around 175, 000 values per second. To cope with such a volume of data the new service has to be extremely robust, scalable and fail-safe with guaranteed data delivery and no data loss. The paper also explains how to recover from different failure scenarios like e.g. network disruption and how to manage and monitor this highly distributed service.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 497
EP  - 501
KW  - database
KW  - network
KW  - monitoring
KW  - operation
KW  - SCADA
DA  - 2020/08
PY  - 2020
SN  - 2226-0358
SN  - 978-3-95450-209-7
DO  - doi:10.18429/JACoW-ICALEPCS2019-MOPHA117
UR  - https://jacow.org/icalepcs2019/papers/mopha117.pdf
ER  -