Business and System Transactions in Java

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Business and System Transactions
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What we've talked about so far, and most of what most people talk about, is what we call system transactions, or transactions supported by RDBMS systems and transaction monitors A database transaction is a group of SQL commands delimited by instructions to begin and end it If the fourth statement in the transaction results in an integrity constraint violation, the database must roll back the effects of the first three statements and notify the caller that the transaction has failed If all four statements had completed successfully all would have been made visible to other users at the same time rather than one at a time RDBMS systems and application server transaction managers are so commonplace that they can pretty much be taken for granted They work well and are well understood by application developers
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However, a system transaction has no meaning to the user of a business system To an online banking system user a transaction consists of logging in, selecting an account, setting up some bill payments, and finally clicking the OK button to pay the bills This is what we call a business transaction, and that displays the same ACID properties as a system transaction seems a reasonable expectation If the user cancels before paying the bills, any changes made on previous screens should be canceled Setting up payments shouldn't result in a system-visible balance change until the OK button is pressed
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The obvious answer to supporting the ACID properties of a business transaction is to execute the entire business transaction within a single system transaction Unfortunately business transactions often take multiple requests to complete, so using a single system transaction to implement one results in a long system transaction Most transaction systems don't work very efficiently with long transactions
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This doesn't mean that you should never use long transactions If your database has only modest concurrency needs, you may well be able to get away with it And if you can get away with it, we suggest you do it Using a long transaction means you avoid a lot of awkward problems However, the application won't be scalable because long transactions will turn the database into a major bottleneck In addition, the refactoring from long to short transactions is both complex and not well understood
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For this reason many enterprise applications can't risk long transactions In this case you have to break the business transaction down into a series of short transactions This means that you are left to your own devices to support the ACID properties of business transactions between system transactions a problem we call offline concurrency System transactions are still very much part of the picture Whenever the business transaction interacts with a transactional resource, such as a database, that interaction will execute within a system transaction in order to maintain the integrity of that resource However, as you'll read below it's not enough to string together a series of system transactions to properly support a business transaction The business application must provide a bit of glue between them
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Atomicity and durability are the ACID properties most easily supported for business transactions Both are supported by running the commit phase of the business transaction, when the user hits Save within a system transaction Before the session attempts to commit all its changes to the record set, it first opens a system transaction The system transaction guarantees that the changes will commit as a unit and will be made permanent The only potentially tricky part here is maintaining an accurate change set during the life of the business transaction If the application uses a Domain Model (116), a Unit of Work (184) can track changes accurately Placing business logic in a Transaction Script (110) requires a manual tracking of changes, but that's probably not much of a problem as the use of transaction scripts implies rather simple business transactions
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The tricky ACID property to enforce with business transactions is isolation Failures of isolation lead to failures of consistency Consistency dictates that a business transaction not leave the record set in an invalid state Within a single transaction the application's responsibility in supporting consistency is to enforce all available business rules Across multiple transactions the application's responsibility is to ensure that one session doesn't step all over another session's changes, leaving the record set in the invalid state of having lost a user's work
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As well as the obvious problems of clashing updates, there are the more subtle problems of inconsistent reads When data is read over several system transactions, there's no guarantee that it will be consistent The different reads can even introduce data in memory that's sufficiently inconsistent to cause application failures
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Business transactions are closely tied to sessions In the user's view each session is a sequence of business transactions (unless they're only reading data), so we usually make the assumption that all business transactions execute in a single client session While it's certainly possible to design a system that has multiple sessions for one business transaction, that's a very good way of getting yourself badly confused so we'll assume that you won't do that
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