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nullSafeSet(133) | binding '0' to parameter: 5 .. * 2 logEntryDaosave(le2); DEBUG [main] AbstractBatcherlog(401) | update t_log_entry set version= , name_= , date_= where id= and version= DEBUG [main] NullableTypenullSafeSet(133) | binding '1' to parameter: 1 DEBUG [main] NullableTypenullSafeSet(133) | binding 'Z' to parameter: 2 DEBUG [main] NullableTypenullSafeSet(133) | binding '2007-10-12 10:35:06' to.

parameter: 3 DEBUG [main] NullableType.nullSafeSet(133) | binding '1160' to parameter: 4 DEBUG [main] NullableType.nullSafeSet(133) | binding '0' to parameter: 5 ... ERROR [main] AbstractFlushingEventListener.performExecutions(301) | Could not synchronize database state with session org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect): [com.apress.prospring2.ch11.domain.LogEntry#1160] at org.hibernate.persister.entity.AbstractEntityPersister. check(AbstractEntityPersister.java:1765) ... at com.apress.prospring2.ch11.dataaccess.VersioningDemo. main(VersioningDemo.java:34) The line marked * 1 in the output shows the point where we call logEntryDao.save(le1). The update operation includes both the primary key (id) and the version. The version gets increased on update, and Hibernate checks that exactly one row has been modified. We try to run logEntryDao.save(le2) at the line marked * 2. We see a similar update statement, but the version in the database is now set to 1. Therefore, the update affects zero rows, and at that point, Hibernate throws the StaleObjectStateException.

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The more I dived into it, the more I started thinking of how I best could evaluate an organization to implement VSTS at their site I wanted to take the assessment concept I had and make an ALM assessment out of it, because ALM started to get my attention I realized very quickly that ALM was an important part of an organization s ability to improve their software development cycle, and if I could find a way to help them with this, the market potential (for me as a consultant) was great Fortunately, Microsoft released their ALM assessments on the web (wwwmicrosoftcom/almassessment), including the Application Platform Optimization (APO) assessment Microsoft has provided its APO model to help IT organizations understand and adopt a more flexible and agile application platform.

Now that we can safely prevent stale data updates, we need to consider another important limitation. When we persist collections in Hibernate, we are likely to use some kind of Collection. When we are modeling a 1-to-n relationship, we are most likely to use a Set. A Set is a collection that does not guarantee order of elements and does not allow duplicate elements; this is precisely what a 1-to-n relationship in a database represents. We will be adding our domain objects to the Sets, so we need to consider their equality. We can implement natural equality or database equality. Natural equality means that two objects are equal if they contain the same data from the application logic point of view. Consider the domain object in Listing 11-21. Listing 11-21. The Customer Domain Object public class Customer { private Long id; private String title; private String firstName; private String lastName; private String address; // getters and setters } When should we consider two Customer objects equal Is it when their IDs are equal or when their title, firstName, lastName, and address fields are equal, regardless of the value of id When it comes to data persistence, we favor the first approach. The database does not care if it contains two rows with all other columns set to the same value as long as the rows primary keys are unique and the rows do not violate any other constraints. If you need to enforce natural equality, consider using a unique index. With this in mind, we can take a look at the implementation of the equals and hashCode methods in our LogEntry class; see Listing 11-22.

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