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The POOL Persistency Framework POOL Summary and Plans.

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Presentation on theme: "The POOL Persistency Framework POOL Summary and Plans."— Presentation transcript:

1 The POOL Persistency Framework POOL Summary and Plans

2 The POOL Persistency FrameworkD.Duellmann2 Storage Manager Plans Mainly performance and consolidation, but…Mainly performance and consolidation, but… Current dictionary loading creates deployment problemsCurrent dictionary loading creates deployment problems –All class dictionaries need to be loaded when ROOT file is opened –ROOT provides functionality to relax this constraint POOL will work with ROOT team to make lazy dictionary loading available for POOL clients Some Object Model support requestedSome Object Model support requested –Embedded pointer to non-polymorph type – POOL should store objects based on the pointer type Recent DataService Review gave some input on enhancements/consolidation requests in that areaRecent DataService Review gave some input on enhancements/consolidation requests in that area

3 The POOL Persistency FrameworkD.Duellmann3 POOL Performance - first cut.. Has not really been optimised systematicallyHas not really been optimised systematically –But first results look reasonable We won’t be faster than ROOT We won’t create smaller files than ROOT –But we want to control the overhead we put on top of ROOT – comparing to ROOT in areas where root offers similar functionality POOL collection performance show clearly that POOL insulation overhead can be kept minimal –But we provide more functionality and flexibility than ROOT so comparing raw IO speed is sometimes comparing apples with pears

4 The POOL Persistency FrameworkD.Duellmann4 File Catalog Plans Moving into production environmentMoving into production environment Extension to allow for typical the Meta Data evolution use casesExtension to allow for typical the Meta Data evolution use cases –Eg A new meta data element is introduced during production Composite CatalogsComposite Catalogs –Accessing eg a local writable together with a shared read-only catalog –Eg a job reads some user files in addition to any file from the large experiment production

5 The POOL Persistency FrameworkD.Duellmann5 POOL Collection Futures First implementation(s) exist and are being picked up byFirst implementation(s) exist and are being picked up by Integration in experiment frameworks just startingIntegration in experiment frameworks just starting –How does one find a collection? –Is there a Collection Catalog (like the File Catalog)? A central one? –Is a File just a special Collection to the end user? Role of collections in a grid environment not clear yet - ARDARole of collections in a grid environment not clear yet - ARDA Collection implementation in POOL is a first stepCollection implementation in POOL is a first step –But the real issue is not the implementation but rather conceptual –Need active experiment involvement in this area

6 The POOL Persistency FrameworkD.Duellmann6 RDBMS Independence POOL should not be directly be coupled to just one RDBMS implementationPOOL should not be directly be coupled to just one RDBMS implementation MySQL++ is a painMySQL++ is a pain –Need a replacement for many additional reasons Performance constraint on collections implementation Product does not evolve anymore Dependent on internals of the GCC compiler –Hard to port mysql++ based code to icc/ecc Did a short “market survey”Did a short “market survey” Outcome proposal to move to OTL Started evaluation by providing two prototype implementations of MySQL FileCatalog and Collections Prototypes are now part of V1.4 internal releases cyclesPrototypes are now part of V1.4 internal releases cycles

7 The POOL Persistency FrameworkD.Duellmann7 Infrastructure & Testing Move to QMtestMove to QMtest –To align with other LCG projects Will soon have to add several new platformsWill soon have to add several new platforms –icc ecc and VC for portability check of POOL code and also as additional development platform Fully Automate Data Format RegressionFully Automate Data Format Regression –Highest priority now as experiment data is produced Add traceability between bug reports and release contents and release validation testsAdd traceability between bug reports and release contents and release validation tests –In collaboration with SPI

8 The POOL Persistency FrameworkD.Duellmann8Summary POOL has delivered a functional persistency framework and has been integrated into frameworks of CMS, ATLAS and soon LHCbPOOL has delivered a functional persistency framework and has been integrated into frameworks of CMS, ATLAS and soon LHCb –Currently used for test productions in CMS –Possibly with more effort than integration teams expected POOL as a development team works well and would profit more from insuring stability than additional manpowerPOOL as a development team works well and would profit more from insuring stability than additional manpower –Some central positions inside POOL are more difficult to back up, but we remained productive even through vacation periods overlapping with experiment integrations POOL operates close to its release planPOOL operates close to its release plan –Following “release early, release often” strategy –Many experiment requirements have been clarified and agreed only during experiment integration phase rather than upfront Many thanks toMany thanks to –all developers working on the project for their commitment –all experiment integration teams for their patience and very constructive feedback!


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