The PHysics Analysis SERver Project (PHASER) CHEP 2000 Padova, Italy February 7-11, 2000 M. Bowen, G. Landsberg, and R. Partridge* Brown University

Richard Partridge2 What is the PHASER project? u Effort to substantially increase productivity of physicists analyzing multi-TB summary data sets u Our immediate focus is on the DØ experiment »600 million data events/year starting in early 2001 »Summary data set expected to grow at rate of 3TB/year u Concentrate on event selection and “ntuple” creation stage »transition in data handling from monolithic reconstruction processing to the much more chaotic processing of summary data by many physicisits »IO and CPU intensive due to need to apply latest calibration, particle ID, and event selection algorithms to several hundred million events

Richard Partridge3 PHASER Architecture u Physics Object Database (POD) stores meta-data used by most physics analyses for their initial event selection u Physics Object and Particle ID tables in POD store calibrated 4-vectors, object quality variables, and results of particle ID algorithms  DVD storage of full summary (  DST) data set and useful subsets of larger DST and STA data sets

Richard Partridge4 PHASER is PHast u New calibrations and particle ID algorithms can be quickly incorporated »Only the changes need to be importd »Regenerating the large  DST data set will only be done infrequently u Storage of up-to-date calibrations and particle ID algorihtms avoids the need to re-apply these alogorithms for each event selection pass u Particle ID tables are small, making it possible to quickly eliminate events not having the desired set of physics objects  Direct access to full  DST sample on DVD allows a  DST subset to be quickly generated for advanced analyses developing new algorithms not yet in the database

Richard Partridge5 The Physics Object Database (POD) u Stores fully calibrated meta-data associated with the various physics objects »leptons, photons, jets, missing ET, secondary vertices, triggers, etc. »for example, an electron object would have the energy, direction, and various quantities used in the electron ID algorithms stored u Each physics object associated with a table in a relational database u Primary key uniquely identifies each physics object and provides information needed to correlate physics objects from a single event »Currently use Run, Event, Instance (where appropriate) and row number from ntuple used to load database »Alternative: data source index, sequence number, and instance

Richard Partridge6 Why use a Relational Database? u Physics objects typically have a fixed set of attributes used for event selection and analysis u Independence of tables aids loading, updating database »Data can be “bulk loaded” as long as primary key is provided in input data stream u Several vendors with quite capable products, large commercial market

Richard Partridge7 Prototype POD u Use DØ Run 1 data ( running period) u 62 million events loaded into the database u Entire “All-Stream” data set loaded »Data set used by almost all DØ physics analyses »Only files with special processing or trigger conditions excluded u Column-wise ntuple format used for importing/exporting data

Richard Partridge8 DØ Run 1 POD u Including indexes, Run 1 POD occupies ~100 GB »58% physics object data »18% indexes on object E T »12% primary keys »12% database overhead

Richard Partridge9 POD Benchmarks u Z  e + e - candidate event selection: »7 seconds to identify ~6k events  W  e  candidate event selection: »18 seconds to identify ~86k events u Both benchmarks times make use of particle ID tables u Event selection times compare very favorably with ~1000 CPU hours required to generate ntuples used in this study Benchmark Hardware/Software u 450 MHz dual-processor Pentium II with 256 MB RAM u Database stored on (6) 36 GB disks in Raid 0 stripe set u MS SQL Server running on Windows NT 4.0

Richard Partridge10 DVD Storage u Provide access to additional event information not included in POD u DVD-RAM has a number of unique capabilities »Less expensive than disk storage, doesn’t require backup »Access to individual events is much faster than tape storage u Current disk capacity is 2.6 GB, 4.7 GB expected soon u Commercial DVD libraries hold up to 600 DVD disks »2.8 TB capacity using 4.7 GB DVD-RAM disks »Average disk load time of 4.5 s, <1 hour to cycle through 600 disks »Up to 6 DVD-RAM drives gives ~10 MB/s IO rate

Richard Partridge11 Web Interface u Plan to develop web-based user interface u Interface modelled on “3-tier” architecture widely used in commercial applications u Physicist will enter event selection requirements using a Java applet u Applet communicates request to “Physics Intelligence” middleware running on PHASER system (via CORBA) »Translate request to SQL for event selection »Verify that request can be accommodated within resource constraints »Produce the requested output files

Richard Partridge12 PHASER Output u Several output options: »List of run and event numbers satisfying the request »Ntuple created from POD information »  DST stream containing requested events from DVD library u Output files will generally be small enough to transfer over the network u Larger output files can be written to DVD and physically sent to physicist for further analysis

Richard Partridge13 Conclusions u PHASER offers a way for both experts, novices, and “dinosaurs” to quickly extract information about a particular class of events u Feasibility of loading “Run 1” size physics object info into a relational database has been demonstrated u Significant improvements in event selection time has been observed for W/Z benchmarks u Expect these results will scale up to Run 2 data load u Database technology is also potentially useful for helping manage complex analyses and storing intermediate results