The ATLAS DAQ System Online Configurations Database Service Challenge J. Almeida, M. Dobson, A. Kazarov, G. Lehmann-Miotto, J.E. Sloper, I. Soloviev and.

Slides:



Advertisements
Similar presentations
Peter Berrisford RAL – Data Management Group SRB Services.
Advertisements

Chapter 10: Designing Databases
March 24-28, 2003Computing for High-Energy Physics Configuration Database for BaBar On-line Rainer Bartoldus, Gregory Dubois-Felsmann, Yury Kolomensky,
GNAM and OHP: Monitoring Tools for the ATLAS Experiment at LHC GNAM and OHP: Monitoring Tools for the ATLAS Experiment at LHC M. Della Pietra, P. Adragna,
1 Databases in ALICE L.Betev LCG Database Deployment and Persistency Workshop Geneva, October 17, 2005.
ATLAS DAQ Configuration Databases CHEP 2001September 3 - 7, 2001 Beijing, P.R.China I.Alexandrov 1, A.Amorim 2, E.Badescu 3, D.Burckhart-Chromek 4, M.Caprini.
Workload Management Workpackage Massimo Sgaravatto INFN Padova.
Software Frameworks for Acquisition and Control European PhD – 2009 Horácio Fernandes.
A Database Visualization Tool for ATLAS Monitoring Objects A Database Visualization Tool for ATLAS Monitoring Objects J. Batista, A. Amorim, M. Brandão,
March 2003 CHEP Online Monitoring Software Framework in the ATLAS Experiment Serguei Kolos CERN/PNPI On behalf of the ATLAS Trigger/DAQ Online Software.
F Fermilab Database Experience in Run II Fermilab Run II Database Requirements Online databases are maintained at each experiment and are critical for.
Data Warehousing: Defined and Its Applications Pete Johnson April 2002.
Slide 1 of 9 Presenting 24x7 Scheduler The art of computer automation Press PageDown key or click to advance.
First year experience with the ATLAS online monitoring framework Alina Corso-Radu University of California Irvine on behalf of ATLAS TDAQ Collaboration.
70-293: MCSE Guide to Planning a Microsoft Windows Server 2003 Network, Enhanced Chapter 14: Problem Recovery.
Linux Operations and Administration
2/10/2000 CHEP2000 Padova Italy The BaBar Online Databases George Zioulas SLAC For the BaBar Computing Group.
15 Copyright © 2005, Oracle. All rights reserved. Performing Database Backups.
+ discussion in Software WG: Monte Carlo production on the Grid + discussion in TDAQ WG: Dedicated server for online services + experts meeting (Thusday.
Science Archive for Sky Surveys Data Providers and the VO - NeSC 2003 March Wide Field Astronomy Unit Institute for Astronomy.
HPS Online Software Discussion Jeremy McCormick, SLAC Status and Plans.
Service Computation 2010November 21-26, Lisbon.
1 Alice DAQ Configuration DB
The Network Performance Advisor J. W. Ferguson NLANR/DAST & NCSA.
Databases E. Leonardi, P. Valente. Conditions DB Conditions=Dynamic parameters non-event time-varying Conditions database (CondDB) General definition:
Control in ATLAS TDAQ Dietrich Liko on behalf of the ATLAS TDAQ Group.
Gnam Monitoring Overview M. Della Pietra, D. della Volpe (Napoli), A. Di Girolamo (Roma1), R. Ferrari, G. Gaudio, W. Vandelli (Pavia) D. Salvatore, P.
ALICE, ATLAS, CMS & LHCb joint workshop on
Elizabeth Gallas August 9, 2005 CD Support for D0 Database Projects 1 Elizabeth Gallas Fermilab Computing Division Fermilab CD Grid and Data Management.
Introduction CMS database workshop 23 rd to 25 th of February 2004 Frank Glege.
Databases in CMS Conditions DB workshop 8 th /9 th December 2003 Frank Glege.
Online Software 8-July-98 Commissioning Working Group DØ Workshop S. Fuess Objective: Define for you, the customers of the Online system, the products.
Overview of DAQ at CERN experiments E.Radicioni, INFN MICE Daq and Controls Workshop.
Database Server Concepts and Possibilities Lee Lueking D0 Data Browser Workshop April 8, 2002.
The Process Manager in the ATLAS DAQ System G. Avolio, M. Dobson, G. Lehmann Miotto, M. Wiesmann (CERN)
Peter Chochula ALICE Offline Week, October 04,2005 External access to the ALICE DCS archives.
5-Oct-051 Tango collaboration status ICALEPCS 2005 Geneva (October 2005)
U.S. ATLAS Executive Committee August 3, 2005 U.S. ATLAS TDAQ FY06 M&O Planning A.J. Lankford UC Irvine.
September 2007CHEP 07 Conference 1 A software framework for Data Quality Monitoring in ATLAS S.Kolos, A.Corso-Radu University of California, Irvine, M.Hauschild.
CHEP March 2003 Sarah Wheeler 1 Supervision of the ATLAS High Level Triggers Sarah Wheeler on behalf of the ATLAS Trigger/DAQ High Level Trigger.
INFSO-RI Enabling Grids for E-sciencE Ganga 4 – The Ganga Evolution Andrew Maier.
Jan 28, 2005Elizabeth_Gallas D0_Trigger_Database 1 D0 Trigger Database Status Elizabeth Gallas Fermilab CD/D0CA Margherita Vittone, Vijay Murthi, and Steve.
PPDG February 2002 Iosif Legrand Monitoring systems requirements, Prototype tools and integration with other services Iosif Legrand California Institute.
TDAQ Experience in the BNL Liquid Argon Calorimeter Test Facility Denis Oliveira Damazio (BNL), George Redlinger (BNL).
The Lisbon Team - 8 December 2003The Lisbon team - 25 November 2003 ConditionsDB – Lisbon API Wide access to CondDB data and schema LCG Conditions DB Workshop.
Kostas KORDAS INFN – Frascati 10th Topical Seminar on Innovative Particle & Radiation Detectors (IPRD06) Siena, 1-5 Oct The ATLAS Data Acquisition.
Correlator GUI Sonja Vrcic Socorro, April 3, 2006.
November 1, 2004 ElizabethGallas -- D0 Luminosity Db 1 D0 Luminosity Database: Checklist for Production Elizabeth Gallas Fermilab Computing Division /
The DCS Databases Peter Chochula. 31/05/2005Peter Chochula 2 Outline PVSS basics (boring topic but useful if one wants to understand the DCS data flow)
1 A Scalable Distributed Data Management System for ATLAS David Cameron CERN CHEP 2006 Mumbai, India.
Event Management. EMU Graham Heyes April Overview Background Requirements Solution Status.
INFSO-RI Enabling Grids for E-sciencE Ganga 4 Technical Overview Jakub T. Moscicki, CERN.
A Validation System for the Complex Event Processing Directives of the ATLAS Shifter Assistant Tool G. Anders (CERN), G. Avolio (CERN), A. Kazarov (PNPI),
The ALICE data quality monitoring Barthélémy von Haller CERN PH/AID For the ALICE Collaboration.
Online DBs in run Frank Glege on behalf of several contributors of the LHC experiments.
M. Caprini IFIN-HH Bucharest DAQ Control and Monitoring - A Software Component Model.
1 Copyright © 2008, Oracle. All rights reserved. Repository Basics.
Cofax Scalability Document Version Scaling Cofax in General The scalability of Cofax is directly related to the system software, hardware and network.
Distribution of ATLAS Software and configuration data Costin Caramarcu on behalf of ATLAS TDAQ SysAdmins.
Computing in High Energy and Nuclear Physics 2012 May 21-25, 2012 New York United States The version control service for ATLAS data acquisition configuration.
L1Calo DBs: Status and Plans ● Overview of L1Calo databases ● Present status ● Plans Murrough Landon 20 November 2006.
Database Replication and Monitoring
Open Source distributed document DB for an enterprise
The Improvement of PaaS Platform ZENG Shu-Qing, Xu Jie-Bin 2010 First International Conference on Networking and Distributed Computing SQUARE.
The Performance and Scalability of the back-end DAQ sub-system
Production Manager Tools (New Architecture)
Mark Quirk Head of Technology Developer & Platform Group
Offline framework for conditions data
Presentation transcript:

The ATLAS DAQ System Online Configurations Database Service Challenge J. Almeida, M. Dobson, A. Kazarov, G. Lehmann-Miotto, J.E. Sloper, I. Soloviev and R. Torres

The Configuration Service Is a part of the ATLAS DAQ/HLT Provides configurations prepared by many DAQ, trigger and detector groups for: –overall DAQ system description (control, monitoring, data-flow) –partial trigger and detectors descriptions The configurations are accessed by huge number of online processes (up to 25K) during boot and config phases of run Once used, the configurations are archived by the service for offline access and analysis by experts CALO MUONS TRACKING RODs ROB ROSs LVL2 & EB network SFIs EF farm SFOs mass storage EF farm L2 farm LVL1 RoIB L2SVs DFM ROLs Front-end pipeline memories 2 Igor Soloviev - CHEP 2007 … … RoIs

3 Igor Soloviev - CHEP 2007

4

5

The Implementation We evaluated many DBMS and persistent managers as candidates for the service implementation, but no one satisfying all requirements were found As a prototype, we started to use own OKS persistent object manager and later made it capable of fulfilling DAQ configuration service needs –from beginning the OKS is based on object data model, uses XML files as persistent storage of the schema and data, and provides GUI tools for schema design and data modifications (see next slide for examples) –later we added: remote access (RDB – remote DB server using CORBA) archiving into relational database abstract API layer with plug-ins for different implementations and DAL generation tools 6 Igor Soloviev - CHEP 2007

The OKS GUI Editors The OKS Schema editor allows to design schema using UML syntax The OKS Data editor allows to create and to modify data using customized appearance of user- defined views graphically presenting relations between objects 7 Igor Soloviev - CHEP 2007

Remote Access Performance & Scalability The distant access to OKS is implemented by RDB server on top of CORBA RDB preloads configuration from master copy of configuration data All programs running on a Point-1 require similar configuration data and are accessing the same RDB server running on rack’s local file server RDB caches results of queries During last technical run 500 L2 applications got full config from single RDB server in ~5” Repository of OKS XML files Rack 1 LFS RDB … N1N1 P 11 P 1M … N2N2 P 21 P 2M … NLNL P L1 P LM … Rack X LFS RDB … N1N1 P 11 P 1M … N2N2 P 21 P 2M … NLNL P L1 P LM … 8 Igor Soloviev - CHEP 2007

Archiving At start of each new run the configuration service automatically archives the used configuration into OKS relational archive The data can be read from the archive using OKS API and can be extracted as XML files The Web GUI allows to select archived data by release name, time interval, user, host and partition masks, to compare, and to save The OKS supports incremental archiving, when only differences between given and base versions are really stored 9 Igor Soloviev - CHEP 2007

Programming Interfaces The code of ATLAS software never uses OKS programming interfaces directly. There are two layers available to hide them: 10 Igor Soloviev - CHEP 2007 –the config layer defines abstract interface to work with arbitrary databases and configuration objects implements caching of results on client side exists for C++, Java and Python implementations are available for XML, RDB and archive –the DAL layer is using above config layer config OKS RDB archive DAL plug-ins user code

Configuration Service: Interfaces and Users Repository of OKS XML files OKS RDB OKS Archive (RDBMS) user OKS data editor text editor Web GUI DAL config oksconfig rdbconfig roksconfig genconfig Partition Maker Partition Maker developer online process 11 Igor Soloviev - CHEP 2007

The Current Status The present implementation is used several years and has been tested during: –ATLAS combined test beams –ATLAS TDAQ technical and detector commissioning runs –TDAQ large scale performance and scalability tests Each time an important feedback was received, we had modified the configuration service software to address user’s needs –full code is under our control from the very base levels For the moment there are no any major design, reliability and performance problems The configuration service is mostly ready for ATLAS 12 Igor Soloviev - CHEP 2007

Should We Use Anything Else? An object database can be a better choice (at least requires less development from our side), but we failed to find scalable and reliable one  Relational database are often used for similar purposes: –prevalence and maturity in database world –commercial and freeware solutions –promising area for specialists (not only in science sectors) But relational technology itself does not address any challenging requirement we have –the installation and support at collaborating institutes is difficult –pure relational data model does not support inheritance we need and some useful data types, like arrays which we are using –one has to write the DALs; automatic generation is difficult because of gap between required data model and the limited relational one –to deal with simultaneous requests from thousands of clients one has to provide tools to cache at some level results of queries (similar to RDB) –archiving of relational data is not trivial; to prepare next configuration one cannot simply modify existing data since the historical data can be overwritten; versioning of relational data is not trivial, since a copying of single data can be not enough because of relations from other data 13 Igor Soloviev - CHEP 2007

Conclusions The huge size and complex organization of the ATLAS system puts challenging requirements on the DAQ system configuration service There is no any third-party solution satisfying all of them is found Current implementation is based on the software designed and developed by the DAQ group and addresses all requirements The configuration service is mostly ready for ATLAS run in the beginning of 2008 Igor Soloviev - CHEP