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So when the user gets back to us and says that he wants seat 7K, the application then has to go back to the database to see if that seat is in fact still free If it is, the application s optimism has been vindicated, and the booking can proceed If not, we just have to apologize to the user (or chastise him for his slowness, depending on the prevailing attitude to customer service in your organization), show him an updated seat map so that he can see which seats have been claimed while he was dithering, and ask him to make a new choice This will happen only a small fraction of the time, and so it turns out to be a reasonable solution to the problem certainly better than a system that is incapable of taking enough bookings to fill the plane in the time available.

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Sometimes optimistic concurrency is implemented in an application-specific way The example just described relies on an understanding of what the various entities involved mean, and would require us to write code that explicitly performs the check described But slightly more general solutions are available they are typically less efficient, but they can require less code The EF offers some of these ignorant-but-effective approaches to optimistic concurrency The default EF behavior seems, at a first glance, to be ignorant and broken not only does it optimistically assume that nothing will go wrong, but it doesn t even do anything to check that assumption We might call this blind optimism we don t even get to.

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discover when our optimism turned out to be unfounded. While that sounds bad, it s actually the right thing to do if you re using transactions transactions enforce isolation and so additional checks would be a waste of time. But if you re not using transactions, this default behavior is not good enough for code that wants to change or add data you ll risk compromising the integrity of your application s state. To get the EF to check that updates are likely to be sound, you can tell it to check that certain entity properties have not changed since the entity was populated from the database. For example, in the SalesOrderDetail entity, if you select the ModifiedDate property in the EDM designer, you could go to the Properties panel and set its Concurrency Mode to Fixed (its default being None). This will cause the EF to check that this particular column s value is the same as it was when the entity was fetched whenever you update it. And as long as all the code that modifies this particular table remembers to update the ModifiedDate, you ll be able to detect when things have changed.

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named is the actual name server of the BIND utilities. It is used to create and resolve domains and it uses the configuration file called named.conf, which is also generated by the rndc-confgen tool. You will use named extensively in the DNS section of this chapter. Additional tools are also included for testing forward and backward name resolution when performing lookups. These include nslookup, dig, and host, for example. Each of these tools will be discussed later when your name server is up and running.

While this example illustrates the concept, it s not entirely robust. Using a date and time to track when a row changes has a couple of problems. First, different computers in the system are likely to have slight differences between their clocks, which can lead to anomalies. And even if only one computer ever accesses the database, its clock may be adjusted from time to time. You d end up wanting to customize the SQL code used for updates so that everything uses the database server s clock for consistency. Such customizations are possible, but they are beyond the scope of this book. And even that might not be enough if the row is updated often, it s possible that two updates might have the same timestamp due to insufficient precision. A stricter approach based on GUIDs or sequential row version numbers is more robust. But this is the realm of database design, rather than Entity Framework usage ultimately you re going to be stuck with whatever your DBA gives you.

If any of the columns with a Concurrency Mode of Fixed change between reading an entity s value and attempting to update it, the EF will detect this when you call SaveChanges and will throw an OptimisticConcurrencyException, instead of completing the update.

The EF detects changes by making the SQL UPDATE conditional its WHERE clause will include checks for all of the Fixed columns. It inspects the updated row count that comes back from the database to see whether the update succeeded.

Before you can run named and rndc, you need to create their configuration files using the rndc-confgen tool. You will run rndc-confgen without any arguments and save the contents by redirecting them to a file. Do the following to create the configuration files.

How you deal with an optimistic concurrency failure is up to your application you might simply be able to retry the work, or you may have to get the user involved. It will depend on the nature of the data you re trying to update.

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