11th November 2008 1Richard Hawkings Richard Hawkings (CERN) ATLAS reconstruction jobs & conditions DB access  Conditions database basic concepts  Types.

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Presentation transcript:

11th November Richard Hawkings Richard Hawkings (CERN) ATLAS reconstruction jobs & conditions DB access  Conditions database basic concepts  Types of data …  Access in Athena  Athena reconstruction jobs  Conditions data access  Scaling and problems  Possible improvements Distributed database operations workshop, CERN, 11/11/08

11th November Richard Hawkings Conditions DB - basic concepts  COOL-based database architecture - data with an interval of validity (IOV) Online, Tier 0/1 COOL Relational Abstraction Layer (CORAL) Oracle DB MySQL DB Recon(athena) (Small DB Replicas) SQLite File Frontier web File-based subsets http-based Proxy/cache SQL-like C++ API C++, python APIs, specific data model IOV start IOV stop channel1(tag1)payload1 IOV start IOV stop channel2(tag2)payload2  COOL IOV (63 bit) can be interpreted as:  Absolute timestamp range (e.g. for DCS)  Run/Lumiblock range (1 LB ~ 1 minute)  COOL payload defined per ‘folder’  Ttuple of simple types  1 DB table row  Can also be a reference to external data  Use channels for multiple instances of data in 1 folder (e.g HV channels)  COOL tags allow multiple data versions  COOL folders organised in a hierarchy  Tags in the hierarchy referenced from a global ‘top-level’ tag Indexed

11th November Richard Hawkings Overview - types of conditions data  Detector calibration, configuration and status data stored directly in COOL  Volume dominated by large CLOB objects ~O(20 MB) for muon calibration  Also many smaller objects  Typically valid for at least one run - update frequency ~ 1 per day or less  Detector control system (DCS/’Slow controls’) data stored directly in COOL  Expect O(1-2 GB/day) DCS data, distributed over <50 COOL folders  IOV valid from a few seconds to a few hours - depends on stability, filtering etc  Data is a subset of that available in PVSS Oracle - what is needed for Athena recon  Fit 1-2 GB/day size constraints (set by Tier-1 and Oracle streams bandwidth)  This dominates the data volume in Oracle  Calibration data stored in referenced POOL files (COOL+POOL)  Volume in COOL is small (only references to POOL files via GUID/offset)  All data volumes are approximate  Data volume is still ramping up as subdetectors increase storage of conditions data and use in reconstruction jobs  Requested space for 1 TB new data (table+index) in 2009, includes safety factor

11th November Richard Hawkings Athena reconstruction job - what is it?  Takes a RAW data file written by online, reconstructs to ESD and AOD files used by physics analysis  Characteristics depend on type of data taking (cosmics, colliding beams)  1 RAW file is O(few 100 MB)-O(few GB) - takes a few hours CPU to reconstruct  E.g. file with MB events, ~15 seconds/event - 4 hour job  Trade-off between file length (storage likes few big files) and recon job wall-time  File contains event data with a timespan of ~30 seconds to several minutes  DAQ system divides data into ‘data streams’, which fill at rates from a few Hz to 50 Hz  Hope for ‘balanced’ streams in collision data taking  One ‘run’ can last several hours (divided into ~1 min lumiblocks), 1000s files/run  What conditions data is required by reconstruction job?  Detector calibration and configuration data, indexed by run/LB  But typically changes only once per run - only one set required per job  DCS data, indexed by timestamp  Potentially changes every second … many sets of data per job  Athena can bulk-read a 10-minute ‘chunk’ of data in one go, cache it for later use - avoid recontacting database every few events

11th November Richard Hawkings Athena job database access  Configuration for October 2008 cosmics data processing  Data from around 70 COOL folders read, < 10 with DCS-type data (more coming)  Data organised in about 12 COOL schema (one per detector)  In COOL, each schema requires a separate Oracle session to read it  Phases of data access within Athena  Job starts… reading configuraton, loading shared libraries etc  After ~1 minute: IOVDbSvc initialise  Go through configured list of COOL folders, check existence, read meta-data, tags  Sessions opened ‘on demand’, not ordered by schema, so gradual open of more sessions up to max of 12; then all are closed at end of initialise  Athena intialisation continues, then start first event processing  For each folder, read the actual data requested (COOL browseObjects calls)  Again happens ‘on demand’ (on callbacks and explicit data requests) - not ordered by schema, gradual increase of sessions up to max of 12, over a few minutes  All sessions/connections closed at end of first event  Can take ~ 10 minutes wall-clock time from job start to end of first event  Two ‘bursts’ of connections/sessions up to maximum of ~12, only one active at a time  Normally, no more database activity for rest of job… but Athena will transparently reopen connections if required (e.g. a file with a long timespan, multi-run file)

11th November Richard Hawkings Scaling and problems  Expect O(2000) jobs running in parallel at Tier-0, O(1000) at Tier-1s  Critical parameter is ‘job start’ rate, not nunber of parallel jobs  E.g. Tier-0 throttles to jobs launched/minute (8/min required for hour jobs)  Harder to do in Tier-1 production environment - want to fill an empty farm, fluctuating load due to other production work - can we introduce load-based throttling?  Indirect measurements indicate reading O(40 MB) from database for each job  Problems with current Athena access scheme  Originally designed for ‘on-demand’ access, connection kept throughout job  Various ‘sticking plaster’ improvements (close connections at end of initialise and event 1)  Trade off between open-close cycles and having idle connections open  Possible improvements  Rewrite Athena IOVDbSvc to order and group data requests by schema  Keep only one connection open at a time, grab all needed data ‘speculatively’ and cache it locally on client - major reimplementation of IOVDbSvc needed  Take opportunity to also ‘align’ query IOVs, to improve performance with Frontier  Stuck with 12 connections per job unless COOL can share sessions across schema  Timescale for implementation with OracleAccess? / or wait for CORAL server?