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The SAMGrid Data Handling System Outline:  What Is SAMGrid?  Use Cases for SAMGrid in Run II Experiments  Current Operational Load  Stress Testing.

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Presentation on theme: "The SAMGrid Data Handling System Outline:  What Is SAMGrid?  Use Cases for SAMGrid in Run II Experiments  Current Operational Load  Stress Testing."— Presentation transcript:

1 The SAMGrid Data Handling System Outline:  What Is SAMGrid?  Use Cases for SAMGrid in Run II Experiments  Current Operational Load  Stress Testing  Future Project Plans Wyatt Merritt (FNAL/CD/DØ) for the SAMGrid Team (Talk created by Adam Lyon)

2 2 What is SAMGrid?  Data handling system for Run II DØ and CDF  SAMGrid manages file storage (replica catalogs)  Data files are stored in tape systems at FNAL and elsewhere (most use ENSTORE at FNAL)  Files are cached around the world for fast access  SAMGrid manages file delivery  Users at FNAL and remote sites retrieve files out of file storage. SAMGrid handles caching for efficiency  You don't care about file locations  SAMGrid manages file meta-data cataloging  SAMGrid DB holds meta-data for each file. You don't need to know the file names to get data  SAMGrid manages analysis bookkeeping  SAMGrid remembers what files you ran over, what files you processed successfully, what applications you ran, when you ran them and wher

3 3 SAMGrid Terms and Concepts  A project runs on a station and requests delivery of a dataset to one or more consumers on that station.  Station : Processing power + disk cache + (connection to tape storage) + network access to SAMGrid catalog and other station caches Example: a linux analysis cluster at D0  Dataset : metadata description which is resolved through a catalog query to a list of files. Datasets are named. Examples: (syntax not exact)  data_type physics and run_number 78904 and data_tier raw  request_id 5879 and data_tier thumbnail  Consumer : User application (one or many exe instances) Examples: script to copy files; reconstruction job

4 4 Physics Analysis Use Cases I.Process Simulated Data II.Process Unskimmed Collider Data III.Process Skimmed Collider Data IV.Process Missed/New Data V.Analyze Sets of Individual Events ("Pick Events")  Note that there are more use cases for production of simulated data and reconstruction not covered here

5 5 I. Process Simulated Data  Look up simulation request with parameters of interest  e.g. Request 5874 has using Pythia with m t = 174 GeV/ c 2  Define dataset (via command-line or GUI):  request_id 5874 and data_tier thumbnail  Submit project to SAMGrid station and submit executable instance(s) to batch system (our tools to make that easy)  Consumer is started  Station delivers files to executable instance(s)  Station marks which files were delivered and consumed successfully and which had errors

6 6 II. Process Unskimmed Collider Data  Define dataset by describing files of interest (not listing file names) using command-line or GUI  data_tier thumbnail and version p14.06.01 and run_type physics and run_qual_group MUO and run_quality GOOD  Submit project to SAMGrid station and submit executable instance(s) to batch system (our tools to make that easy)  Consumer is started  Station delivers files to executable instance(s)  Station marks which files were delivered and consumed successfully and which had errors

7 7 III. Process Skimmed Collider Data  Someone (a Physics group, the Common Skimming Group, or an individual) has produced skimmed files  They created a dataset that describes these files  You can...  Submit project/jobs using their dataset name OR  Create a new dataset based on theirs and adding additional constraints __set__ DiElectronSkim and run_number 168339  Submission is same as before

8 8 IV. Process Missed/New Data  The set of files that satisfy the dataset query at a given time is a snapshot and is remembered with the SAMGrid project information  One can make new datasets with:  Files that satisfy a dataset but are newer than the snapshot (new since the project ran)  Files that should have been processed by the original project but were not delivered or not consumed __set__ myDataSet minus (project_name myProject and consumed_status consumed and consumer lyon)

9 9 V. Analyze Individual Events (Pick Events)  Users want to analyze individual events with lower level data tiers (e.g. raw)  Event displays  Special investigations  The SAMGrid catalog keeps information on each raw event (run#, event#, trigger bits, file)  Users run a pick events tool that creates a dataset and submits an executable to extract and process these events

10 10 Current SAMGrid Production Configurations  Large SMP  A 10 TB central cache with 128 attached processors  Mostly used for Pick Events  Local job submission (not Grid)  Linux production farms  Reconstruction, Monte Carlo Production, Reprocessing  Various cache arrangements: distributed on worker nodes, NFS- mounted from a central head node, routed through a central head node and then distributed  Local or Grid (Condor) job submission  Linux analysis clusters  Analysis jobs  Various cache arrangements: distributed on worker nodes, routed through a central head node and then distributed; cached on central node only  Local job submission or remote submission (with experiment-specific tools, not Condor)

11 11 SAMGrid Statistics (DØ) Files delivered by month 19992000200120022003 Run II Begins

12 12 SAMGrid Statistics - Usage Data 9000 Projects!233 Different Users! Data from early January 6 until February 24 at DØ

13 13 SAMGrid Statistics - Usage Data ~500K Files! ~1%

14 14 SAMGrid Statistics - Usage Data Raw Thumbnails + … 256 TB! 8.3 Billion Events! Data from early January 6 until February 24 at DØ

15 15 SAMGrid Statistics - Operations Data

16 16 SAMGrid Statistics - Operations Data  Time between Request Next File and Open File  For CAB and CABSRV1 analysis farms stations  50% of enstore (tape) transfers occur within 10 minutes.  75% within 20 minutes  95% within 1 hour  For CENTRAL-ANALYSIS (SMP station) and CLUED0 (desktop cluster station)  95% of enstore (tape) transfers within 10 minutes

17 17 SAMGrid Statistics - Operations Data

18 18 Stress Testing  There are many station parameters to tune  Maximum parallel transfers  Maximum concurrent enstore requests  Configuration of cache disks  …  We're moving away from d0mino to Linux  How robust are these linux machines?  How many projects can they run?  How many concurrent file transfers can they handle?  Running test harness on a small cluster to explore SAMGrid parameter space

19 19 SAMGrid Stress Testing max transfers =5max transfers =1

20 20 SAMGrid Stress Testing max transfers =5max transfers =1

21 21 SAMGrid Stress Testing max transfers =5max transfers =1

22 22 SAMGrid Projects  Recently Completed:  Python & C++ Client API  Improved DB Schema  Batch system adapters  1 st generation monitoring  Active & Future:  DB-Middleware improvements  2 nd generation monitoring  Improved query language  Grid submission  Conversion to SRM interface for cache functions

23 23 Summary  SAMGrid has been successfully used at DØ for all data handling  Over the past year 44 stations consumed (remote = outside fermilab) 3.6 million files (0.46 million files remote) 40 billion events (3 billion events remote) 1.6 Petabytes of data (137 TB of data remote)  ~25 million MC events produced remotely with SAMGrid  ~90 million events reprocessed remotely with SAMGrid  SAMGrid will soon become the data handling system for CDF and later MINOS  SAMGrid deployment on grids is contributing improvements to Grid tools & interfaces

24 24 EXTRA SLIDES FOLLOW

25 25 ENSTORE Statistics  0.6 Petabytes in tape storage! Only 5 files unrecoverable (5 GB total; 8ppm loss) !!! One of them was RAW file

26 26 Some SAMGrid buzzwords  Dataset Definition  A set of requirements to obtain a particular set of files  e.g. data_tier thumbnail and run_number 181933  Datasets can change over time More files that satisfy the dataset may be added to SAMGrid  Snapshot  The files that satisfy a dataset at a particular time (e.g. when you start an analysis job)  Snapshots are static  Project  The running of an executable over files in SAMGrid  Consists of the dataset definition, the snapshot from that dataset definition, and application information  Bookkeeping data is kept - how many files did you successfully process, where did your job run, how long did it take


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