ATLAS Distributed Computing Tutorial Tags: What, Why, When, Where and How? Mike Kenyon University of Glasgow.

Slides:



Advertisements
Similar presentations
Metadata Progress GridPP18 20 March 2007 Mike Kenyon.
Advertisements

Metadata (data about data) GridPP-15, Paul Millar.
31/03/00 CMS(UK)Glenn Patrick What is the CMS(UK) Data Model? Assume that CMS software is available at every UK institute connected by some infrastructure.
1 Databases in ALICE L.Betev LCG Database Deployment and Persistency Workshop Geneva, October 17, 2005.
David Adams ATLAS DIAL Distributed Interactive Analysis of Large datasets David Adams BNL March 25, 2003 CHEP 2003 Data Analysis Environment and Visualization.
ATLAS Analysis Model. Introduction On Feb 11, 2008 the Analysis Model Forum published a report (D. Costanzo, I. Hinchliffe, S. Menke, ATL- GEN-INT )
29 July 2008Elizabeth Gallas1 An introduction to “TAG”s for ATLAS analysis Elizabeth Gallas Oxford Oxford ATLAS Physics Meeting Tuesday 29 July 2008.
David Adams ATLAS DIAL Distributed Interactive Analysis of Large datasets David Adams BNL June 23, 2003 GAE workshop Caltech.
L3 Filtering: status and plans D  Computing Review Meeting: 9 th May 2002 Terry Wyatt, on behalf of the L3 Algorithms group. For more details of current.
ATLAS Analysis Overview Eric Torrence University of Oregon/CERN 10 February 2010 Atlas Offline Software Tutorial.
December 17th 2008RAL PPD Computing Christmas Lectures 11 ATLAS Distributed Computing Stephen Burke RAL.
Event Metadata Records as a Testbed for Scalable Data Mining David Malon, Peter van Gemmeren (Argonne National Laboratory) At a data rate of 200 hertz,
ATLAS : File and Dataset Metadata Collection and Use S Albrand 1, J Fulachier 1, E J Gallas 2, F Lambert 1 1. Introduction The ATLAS dataset search catalogs.
Conditions DB in LHCb LCG Conditions DB Workshop 8-9 December 2003 P. Mato / CERN.
Alignment Strategy for ATLAS: Detector Description and Database Issues
LHC: ATLAS Experiment meeting “Conditions” data challenge Elizabeth Gallas - Oxford - August 29, 2009 XLDB3.
30 Jan 2009Elizabeth Gallas1 Introduction to TAGs Elizabeth Gallas Oxford ATLAS-UK Distributed Computing Tutorial January 2009.
The first year of LHC physics analysis using the GRID: Prospects from ATLAS Davide Costanzo University of Sheffield
Your university or experiment logo here Caitriana Nicholson University of Glasgow Dynamic Data Replication in LCG 2008.
ATLAS and GridPP GridPP Collaboration Meeting, Edinburgh, 5 th November 2001 RWL Jones, Lancaster University.
Databases E. Leonardi, P. Valente. Conditions DB Conditions=Dynamic parameters non-event time-varying Conditions database (CondDB) General definition:
Datasets on the GRID David Adams PPDG All Hands Meeting Catalogs and Datasets session June 11, 2003 BNL.
Introduction Advantages/ disadvantages Code examples Speed Summary Running on the AOD Analysis Platforms 1/11/2007 Andrew Mehta.
ATLAS Detector Description Database Vakho Tsulaia University of Pittsburgh 3D workshop, CERN 14-Dec-2004.
INFSO-RI Enabling Grids for E-sciencE ATLAS Distributed Analysis A. Zalite / PNPI.
DPDs and Trigger Plans for Derived Physics Data Follow up and trigger specific issues Ricardo Gonçalo and Fabrizio Salvatore RHUL.
1 Database mini workshop: reconstressing athena RECONSTRESSing: stress testing COOL reading of athena reconstruction clients Database mini workshop, CERN.
DDM Monitoring David Cameron Pedro Salgado Ricardo Rocha.
3rd November Richard Hawkings Luminosity, detector status and trigger - conditions database and meta-data issues  How we might apply the conditions.
Full Dress Rehearsal (FDR1) studies Sarah Allwood-Spiers 11/3/2008.
17 December 1998Silvia Resconi ATLFast++ into LHC++: a first exercise The aim of the exercise: from generation to analysis using ATLFast++ algorithms into.
David Adams ATLAS Virtual Data in ATLAS David Adams BNL May 5, 2002 US ATLAS core/grid software meeting.
Conditions Metadata for TAGs Elizabeth Gallas, (Ryan Buckingham, Jeff Tseng) - Oxford ATLAS Software & Computing Workshop CERN – April 19-23, 2010.
LHC Physics Analysis and Databases or: “How to discover the Higgs Boson inside a database” Maaike Limper.
David Adams ATLAS DIAL: Distributed Interactive Analysis of Large datasets David Adams BNL August 5, 2002 BNL OMEGA talk.
A New Tool For Measuring Detector Performance in ATLAS ● Arno Straessner – TU Dresden Matthias Schott – CERN on behalf of the ATLAS Collaboration Computing.
Integration of the ATLAS Tag Database with Data Management and Analysis Components Caitriana Nicholson University of Glasgow 3 rd September 2007 CHEP,
Kyle Cranmer (BNL)HCP, Isola d’Elba, March 23, The ATLAS Analysis Architecture Kyle Cranmer Brookhaven National Lab.
A Flexible Distributed Event-level Metadata System for ATLAS David Malon*, Jack Cranshaw, Kristo Karr (Argonne), Julius Hrivnac, Arthur Schaffer (LAL Orsay)
LCG Distributed Databases Deployment – Kickoff Workshop Dec Database Lookup Service Kuba Zajączkowski Chi-Wei Wang.
The ATLAS TAGs Database - Experiences and further developments Elisabeth Vinek, CERN & University of Vienna on behalf of the TAGs developers group.
M. Oldenburg GridPP Metadata Workshop — July 4–7 2006, Oxford University 1 Markus Oldenburg GridPP Metadata Workshop July 4–7 2006, Oxford University ALICE.
The “Comparator” Atlfast vs. Full Reco Automated Comparison Chris Collins-Tooth 19 th February 2006.
Pavel Nevski DDM Workshop BNL, September 27, 2006 JOB DEFINITION as a part of Production.
TAGS in the Analysis Model Jack Cranshaw, Argonne National Lab September 10, 2009.
INFSO-RI Enabling Grids for E-sciencE Using of GANGA interface for Athena applications A. Zalite / PNPI.
Summary of User Requirements for Calibration and Alignment Database Magali Gruwé CERN PH/AIP ALICE Offline Week Alignment and Calibration Workshop February.
Victoria, Sept WLCG Collaboration Workshop1 ATLAS Dress Rehersals Kors Bos NIKHEF, Amsterdam.
1 A Scalable Distributed Data Management System for ATLAS David Cameron CERN CHEP 2006 Mumbai, India.
ELSSISuite Services QIZHI ZHANG Argonne National Laboratory on behalf of the TAG developers group ATLAS Software and Computing Week, 4~8 April, 2011.
Distributed Analysis Tutorial Dietrich Liko. Overview  Three grid flavors in ATLAS EGEE OSG Nordugrid  Distributed Analysis Activities GANGA/LCG PANDA/OSG.
David Adams ATLAS ATLAS Distributed Analysis (ADA) David Adams BNL December 5, 2003 ATLAS software workshop CERN.
Tim Christiansen (CERN), Claudio Campagnari (UCSB), and Benedikt Hegner (CERN) for the Top-Physics Group AOD/PAT-tuples: Top-PAG Plans and Needs for the.
Finding Data in ATLAS. May 22, 2009Jack Cranshaw (ANL)2 Starting Point Questions What is the latest reprocessing of cosmics? Are there are any AOD produced.
Dynamic Data Placement: the ATLAS model Simone Campana (IT-SDC)
Comments on #3: “Motivation for Regional Analysis Centers and Use Cases” Chip Brock 3/13/2.
ATLAS Physics Analysis Framework James R. Catmore Lancaster University.
ATLAS TAGs: Tools from the ELSSI Suite Elizabeth Gallas - Oxford ATLAS-UK Distributed Computing Tutorial Edinburgh, UK – March 21-22, 2011.
Joe Foster 1 Two questions about datasets: –How do you find datasets with the processes, cuts, conditions you need for your analysis? –How do.
Metadata and Supporting Tools on Day One David Malon Argonne National Laboratory Argonne ATLAS Analysis Jamboree Chicago, Illinois 22 May 2009.
Peter van Gemmeren (ANL) Persistent Layout Studies Updates.
ATLAS TAG Services Jack Cranshaw with support from Thomas Doherty, Julius Hrivnac, Marcin Nowak.
Monitoring of L1Calo EM Efficiencies
Database Replication and Monitoring
Developments of the PWG3 muon analysis code
LHCb Computing Model and Data Handling Angelo Carbone 5° workshop italiano sulla fisica p-p ad LHC 31st January 2008.
Readiness of ATLAS Computing - A personal view
Grid Data Integration In the CMS Experiment
ATLAS TAGs: Tools from the ELSSI Suite
ATLAS DC2 & Continuous production
Presentation transcript:

ATLAS Distributed Computing Tutorial Tags: What, Why, When, Where and How? Mike Kenyon University of Glasgow

Tags What are tags? Why have them? When are they produced? Where are they? How can they be used?

What are Event Tags? Event-level metadata: summary information about events, with a “pointer” to the corresponding AOD/ESD/RDO format –Useful for selecting events for physics analysis –Should be no bigger than 1KB per event (~ 1% AOD size)

Why have Event Tags? To make Physicist’s life easier and analysis faster –Allows you to exclude uninteresting events from data sample used for analysis without searching through AOD/ESD files –Samples of specific interest to an analysis can be extracted into a smaller set of files for repeated running –Provides a global view of the data, useful for data mining Not to do analysis on directly

Tag Use Cases Some Physicist use cases: –Using official Tags with query in job options –Using local Tag “database” for preliminary analysis –Using global Tag database to look for events –Using global Tag database to build input list for Athena jobs

What do they look like? The LCG POOL infrastructure is used to store Tags –Hence use of “collection” terminology They exist in 2 forms: –ROOT files –Relational database (MySQL and Oracle) Why keep 2 forms? –ROOT files useful for local work –DB useful for queries, global view of data Tag content: collection information + event information

Tag Content Collection Information –Collection ID, AOD/ESD/RDO references Global Event Quantities –Event no., run no., no. of tracks, missing E T etc Trigger Decisions Electrons, Photons, Muons –Number, P T,  etc Jets, Taus –Number, P T, , etc

When are Tags produced? Written to ROOT files at Tier 0 during AOD production – “Explicit collections” Data then imported into central relational database (Oracle at CERN) Database replicated to Tier 1 and lower –Oracle where available; MySQL otherwise Users can create their own tag files

Sample Queries General Collection Information –How many events in collection A? –What are the names and types of Tag attributes? –What production task(s) produced these Tags? Content Queries –Give me all events with at least 2 electrons and missing ET > 10 GeV which are ‘good for physics’ Summary Queries –Give me the number of events for some content query –Give me sum of the luminosity for some content query

How can Tags be used? Collection tools Athena Tag Navigator Tool (TNT)

Collection Tools To use Tags in Athena, you need to know what the attributes are POOL Collection tools can be used for this –Can copy collections, append collections, print list of files used, etc –Allows queries on the input collections See Tutorial Exercises, part 1

Tags in Athena Both ROOT and Relational Tags can be read directly from Athena Need file catalogue to find the AOD files, and Athena version which matches that used by the Tags One can also produce private ROOT Tags from AOD Focus here is on reading, rather than building, Tags

Local Tag Files with Athena jobOptions for event selection look like:

Remote Tag Database with Athena Not many Tags available in central database yet –This constrains the exercises somewhat, but we can at least illustrate the principles jobOptions must include lines like: EventSelector.InputCollections = ['rome_4312_merge_H12_140_gamgam_AOD_tags’] EventSelector.Connection = 'oracle://atlas_tags/atlas_tags_rome’ EventSelector.CollectionType = 'ExplicitRAL'

Tag Navigator Tool (TNT) A utility which aims to allow ATLAS physicists to use the Tag database for analysis Runs a query on the database and outputs a local ROOT collection Divides this into a number of sub-collections Submits user jobs to LCG, one per sub-collection Output files can be registered as new DQ2 dataset

What’s there now? There is still a lot of work to be done to get an efficient Tag system running –Currently running performance / scalability tests on central database Need Tags to be produced and loaded into database as a matter of course Tag database from Rome workshop is still there, now awaiting Tags from Streaming Tests

And finally… Tags will become ever more useful as real data appears Infrastructure is still being developed Wednesday’s exercises aimed at familiarisation with ideas and methods