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Prevayler

Prevayler. Agenda. Introduction Object Prevalence Concepts Prevayler Concepts Transaction processing Performance Conclusion. Introduction. Persistence layer of business applications Typical: Usage of an RDBMS a nd O/R-Mapping Bridging between object model and relational model

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Prevayler

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  1. Prevayler

  2. Agenda • Introduction • Object Prevalence • Concepts • Prevayler • Concepts • Transaction processing • Performance • Conclusion

  3. Introduction • Persistence layer of business applications • Typical: Usage of an RDBMS and O/R-Mapping • Bridging between object model and relational model • Mapping mostly not transparent • Mapping expensive • Ideal: • Transparent persistency • Business objects... • having ACID semantics • implementation matchestransient implementation No mapping between data models rapid development quick prototyping possible

  4. Object Prevalence • Concept first published in 1987 by A. D. Birrell, M. B. Jones und E. P. Wobber in ‘A Simple and Efficient Implementation for Small Databases‘ • Pattern for keeping in-memory data structures durable • Later named‘Object Prevalence‘by Klaus Wuestefeld • Founder of the Prevayler project

  5. Object Prevalence • Core Concepts • All data organized in single data structure • Data structure held in memory • Premises: • System has plenty of memory to hold all data • Price of memory keeps dropping • No shortage of address space due to VM and 64 bit  Data available to owning process only • Contrary to RDBMS – RDBMS designed not to have all data in memory

  6. Object Prevalence • Core Concepts (2) • Periodicsnapshot of data structure • Saved on durable medium (hard disk) • Data structure accessed indirectly • Command-Pattern • Write Ahead Log for modifying accesses • Log documents all modifications since last snapshot • Saved on durable medium (hard disk) • Startup/Recovery • Read recent snapshot • Playback log

  7. Prevayler • Project Prevayler • Foundedby Klaus Wuestefeld • First public implementation of Object Prevalence • First universal implementation • Written in Java • Open Source (BSD Lizense) • First release in 2001 (LGPL) • Meanwhile, further Object Prevalence implementations exist • Gained publicity by performance claims • 9000 times faster than Oracle (über JDBC) • 3000 times faster than MySQL (über JDBC) • ... but no TPC-C available

  8. Prevayler – Concepts • Data structure • Tree of Java objects • Contains all business objects • All objects must be accessible by a single root • Root object named ‘Prevalent System‘ • All objects must be serializable • Implementation of java.io.Serializable or java.io.Externalizable  required for taking snaphots

  9. Prevayler – Concepts • Data access • Indirect access thru command objects • Readonly: Query-object • Modifications: Transaction-object • Only programmatic access • No Query Language • Commands are opaque to Prevayler • Prevayler cannot determineactual modifcations made • Synchronisation must be performedon Data structure level • Much more coarse-grained than RDBMS (page level)

  10. Prevayler – Concepts • Data access (2) • Query/Transaction execution • Before execution, lock on data structure must be aquired • No reader/writer lock distinction • Serial execution of all commands • Readonly Access • Implementation of Query-Interface • Commands not written to log  Query-objects must not perform any modifications public interface Query { public Object query( Object prevalentSystem, Date executionTime) throws Exception; }

  11. Prevayler – Concepts • Data access (3) • Modifying Access • Implementation of Transaction/TransactionWithQuery-Interface • Object must be serializable • Will be serialized to command log before execution • Deterministic behaviour • Replay during Startup/Recovery phase • External resources should not be used • (historic) Prevayler-time must be used instead of system time public interface Transaction extends java.io.Serializable { publicvoid executeOn( Object prevalentSystem, Date executionTime); }

  12. Prevayler – Data safety • Snapshots • Serialization of complete object tree • Standard: Java Object Serialization • All objects are serialized, not only ‚dirty‘ objects • Performed periodically • Process • Acquire lock on object tree • Serialize tree into file • Release lock • Mark snapshot file as complete • Truncate command log, delete old snapshot (optional) • Process may take several minutes  Downtime • Can be avoided by using a replica

  13. Prevayler – Data safety • Transaction processing • Process • Serializability-Test of command object • Approval by Censor • Adding entry to Transaction Log • Call Transaction.executeOn() • Execution of Transaction-Command considered atomic • But: Atomicity must be assured by developer • On error, all modifications must be rolled back manually  Complex for non-trivial commands • Transaction.executeOn may throw an exception • Result depends on Censor used

  14. Prevayler – Data safety • Transaction processing– Censors (2) • Censors • ‚Approve‘ Commands before their execution • Are optional • StrictTransactionCensor • Command executed twice • Execution on copy of data structure (‘Food Taster‘) • If successful: • Execution on main data strcture • If an error occured (Exception): • Transaction is aborted • Recovery of ‘Food Taster‘ •  Costly operation • Consequences • Failing commands may leave data structure in inconsistent state • Inconsistencies less likely though • Increased memory usage and execution time

  15. Prevayler – Data safety • ACID • Snapshots and logs ensure durability • Serial command execution implies Isolation • Developer is responsible of atomicity • Commands must be implememnted in atomic fashion • May be achived by using compensating actions • Developer has to ensure consistency of data structure • Object tree must be consistent before and after command execution, even if command failed  A flawed command implementation can lead to inconsistency

  16. Prevayler – Performance • Comparison to RDBMS problematic • RDBMS mostly run out-of-process • Usage of ODBC/JDBC/etc necessary • Published performance results taken on single-CPU machine • Synchonisation as bottleneck • Serial execution of Queries and Transactions • Can degrade performance on parallel systems • Can degrade performance on SMP sytemes  Commands still processed serially • Long running transaction may stall system • Waiting for lock on data structure

  17. Prevayler – Performance • Reading • No disk access neccessary • All required data already in memory  Quick access if data structure is organized well (using Hashtables etc)  Minimal overhead Can be siginificantly faster than RDBMS • Modifications • Disk access neccessary • WriteAhead-Logging • If StrictTransactionCensor is used: • Additional overhead • Rollbacks expensive • About same order of maginitude as RDBMS

  18. Conclusion • Prevayler can substitute RDBMS... • for moderate data volumes • if only local (in-process) access to data is required • If data accesses are mostly read-only • Benefits • No O/R-Mapping neccessary • Rapid development • High transparency for business objecs  but low transparency in data access (Query/Transaction-Modellis propriatary) • Performace • High performance for readonly access • Not designed for SMP systems • Data safety • Requires great care of developer • Prevayler does not reach reliability and robustness of modern RDBMS

  19. References • [RJW] Birrell , Andrew; Jones, Michael; Wobber, Edward: A Simple and Efficient Implementation for Small Databases, digital Systems Reseach Center, 1987 • [Carver] Carver, Frank: Thoughts about Prevayler and Databases http://radio.javaranch.com/frank/2004/12/27/1104152030000.html (11/10/2005) • [Evans] Evans, Huw: Why Object Serialization is Inappropriate for Providing Persistence in Java, Department of Computing Science, University of Glasgow • [Fowler] Fowler, Martin: Design Blikihttp://www.martinfowler.com/bliki/design.html (12 /19/2005) • [Melton] Melton, Hayden: An Evaluation of Object Prevalence, Dept. of Electrical and Electronic Engineering, University of Auckland • [ON] Obermayer, Nathanael: ACID gratis, iX Ausgabe 02/2004 • [Prevayler] Prevayler Homepage, http://www.prevayler.org • [Spille] Spille, Mike: Prevayler Revisitedhttp://www.pyrasun.com/mike/mt/archives/2004/12/25/15.02.00/index.html (11/10/2005) • [PT] Printezis, Tony: Garbage Collection in the Java HotSpot Virtual Machine, DevXhttp://www.devx.com/Java/Article/21977/0/ (01/10/2006) • [WE] Wolff, Eberhard: Die schnellste Datenbank der Welt, Java Magazin Ausgabe 06/2004

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