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SOEN 6011 Software Engineering Processes. Section SS Fall 2007 Dr Greg Butler Week 10. Deliverable 3 Concurrency ACID UnitOfWork Identity Map Lazy Loading. Deliverable 3. Read Java threads tutorial (if necessary) - PowerPoint PPT Presentation

Text of SOEN 6011 Software Engineering Processes

  • SOEN 6011Software Engineering ProcessesSection SS Fall 2007Dr Greg Butler

  • Week 10Deliverable 3

    ConcurrencyACIDUnitOfWorkIdentity MapLazy Loading

  • Deliverable 3Read Java threads tutorial (if necessary)You need thread-safe Java code

    Do SOEN 344 Tutorials 3 and 4UnitOfWorkIdentity Map, Lazy Loading

  • Deliverable 3Everyone use same players, eitherAliceBobAllow your players to play multiple games at the same time from separate browsersStore statistics in DBDecide whether to store Game state in DB

  • Deliverable 3 Fowler Session State PatternsProblem: where to store session state

    Client session statestateless server stores state on the clientServer session stateKeep state on server in serialized formDatabase session stateStore state as committed data in DB

  • Client, Web server, Db server

  • Deliverable 3Should your code affect anyone elses? or their database content? or their serialized session state? or their client-side stored session state? or your other client-side stored session state?

  • Concurrency ProblemsEssential problems:Lost updatesInconsistent reads.Another point of view:CorrectnessLiveness

  • Offline concurrency the term we use is offline concurrency, that is, concurrency control for data thats manipulated during multiple database transactions.

  • Concurrency ControlTwo main approaches:Optimistic concurrency control.Pessimistic concurrency control.

    First let us examine the concept of transaction.

  • TransactionKey concept for handling concurrency issues.2 or more parties dialog / exchange messages.

    A transaction:Well defined start and end.Overall system and resources are in a consistent state at start and end of transaction.All or nothing

  • We want transactions to be A.C.I.D. Atomic.For a transaction to succeed all of its steps must succeed.All or nothingConsistentA systems resources must be in a consistent state at the start and the end of the transaction.IsolatedEffects of a trans. must be invisible to other open trans.s until it is committed successfully.Durable:Results of committed trans should be permanent.

  • Concurrency Control (Fowler Ch 16)Optimistic concurrency control:Prevents conflicts between concurrent business transactions by detecting a conflict and rolling back the transaction.Pessimistic concurrency controlPrevents conflicts between concurrent business transactions by allowing only one business transaction at a time to access the data.Eg, file locking on most OSs.

  • Optimistic Offline Lock

  • Pessimistic Offline Lock

  • Execution ContextsRequestSessionTransactionA transaction that spans multiple requests is terms a long transaction.

  • Some Basic Concepts related to WEA User Goalsperformsissueshas

  • Can you see an advantage in using the Front Controller pattern?

  • Client, Web server, Db server

  • Concurrency: StrategiesAvoid it if you can.Use reference implementations: e.g. DBMS.

    Understand the issues and limit:Number of threads.Data sharing (our focus)

  • Concurrent Data ManipulationWhere can this happen?In memory.In the database.Both of these places are subject to the problems ofInconsistent reads.Lost updates.



  • Database Management Systems (DBMS)Well developed (tried-and-true) technology.

    Hence we will try to push the concurrency down into the DBMS as much as possible.

    What does this suggest about your choice of Session State Pattern?

  • Design solutions regarding in memory data sharing Java: synchronize primitive can sometimes be used:E.g. a Singletons getUniqueInstance() is declared as synchronized. (What could happen if it wasnt?)Careful choice ofDeclaration and use of static fields.Object instantiation.Javas ThreadLocal.

  • Data Source PatternsFowler: Chapter 10.Data Mapper, TDG

    Fowler, Chapter 11UnitOfWorkIdentity MapLazy Loading

  • Unit of WorkMaintains a list of objects affected by a business transaction and coordinates the writing out of changes and the resolution of concurrency problems

    Caches DB access

    Minimizes (slow) DB calls

    After commit UoW alters DB

  • Client



    Unit of Work

    New Movie


    register clean

    change title

    register dirty




  • Identity MapEnsures that each object gets loaded only once by keeping every loaded object in a map. Looks up objects using the map when referring to them.

  • Example:Data Mapper & Identity MapProblem: Each person has many buddys (also Person objects) so may load many copies of the same object

    Solution: Identity Map




  • Identity Map (p.195): Ex. Find Alice

  • A Problem of O/R MappingsWhen are objects loaded, saved and changes committed?Load A first.Load B first, then ALoad B, then A, change B,

    O/R = object / relationalFowler calls this a behavioral problem.ABC*

  • A Solution: Lazy LoadingComes under various forms.Virtual Proxy

    This is particularly useful for large compound objects where only some of the data may be needed (for the request).

  • Lazy LoadingAn object that does not contain all the data you need buts knows how to get itEg, a customer with many orders, though generally you only want the customer name and address (for the request).Load orders only when required.

  • Virtual ProxyExtract an interface from Person.Result: IPerson.Create PersonProxyOne one field (the primary key): name.When another field value is requested, it fetches the real person from the DB and then returns the value by delegation.On subsequent calls, it simply delegates.

  • Proxy









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