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FitTextToWidth function earlier. But it turns out that GDI+ already includes a fea-
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Example 16-10 just feeds in strings from a fixed set of items at random. Calling this test function from just one thread produces the expected results: at the end, the Mos tRecentlyUsed object just returns the most recent items put into it by this test. However, the multithreaded test in Example 16-11 causes something quite different to happen.
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this.visibleLayer = (this.visibleLayer + 1) % 2;
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This is the most challenging task in the migration process and requires a good understanding of your application. The good news is that applications using DAOs don t have any impact on the business logic tier of the application, and the migration effort is limited only in the persistence tier. If you followed the DAO design pattern religiously, you most likely created value or transfer objects (similar to DTOs) that are used by the business tier to retrieve or update data from the database. A careful look reveals that these transfer objects resemble entities. A little
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LINQ includes eight standard aggregate functions, shown in Table 17-1. Each function accepts an expression that indicates what should be aggregated during the query.
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Vertical quote. This one looks like a male symbol ( ) in the console s IBM-emulating code page.
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Hypothetically, you could implement methods for each of these operations. For example, for your Fraction type, you might create an Add( ) method, which you would invoke like this:
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The transaction.factory_class property tells Hibernate that you ll be using JTA transactions. Currently, the only other option to JTA is JBDC transactions, which is the default. JTA transactions are retrieved from a JNDI URI, which is specified using the jta.UserTransaction property. If you don t know the URI for your specific application server, the default value is java:comp/UserTransaction. There is some confusion about another property related to JTA transactions: transaction.manager_lookup_class. You only need to specify the manager lookup class when you re using a transactional cache. (We discuss caches in the next section don t worry.) However, if you don t define the jta.UserTransaction property and transaction.manager_lookup_class is defined, the user transaction name in the lookup factory class is used. If neither of the properties are used, Hibernate falls back to java:comp/UserTransaction.
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... public class Shipment { ... @OneToOne @JoinColumn(table = "ITEM_SHIPMENT", name = "ITEM_ID") private Item auction; }
thirteen answers, but let me (your humble author) risk suggesting a couple of prime suspects:
A dirty read occurs if a one transaction reads changes made by another transaction that has not yet been committed. This is dangerous, because the changes made by the other transaction may later be rolled back, and invalid data may be written by the first transaction, see figure 10.3. An unrepeatable read occurs if a transaction reads a row twice and reads different state each time. For example, another transaction may have written to the row and committed between the two reads, as shown in figure 10.4. A special case of unrepeatable read is the second lost updates problem. Imagine that two concurrent transactions both read a row: One writes to it and commits, and then the second writes to it and commits. The changes made by the first writer are lost. This issue is especially relevant if you think about application
<url-pattern>/services/*</url-pattern> </servlet-mapping> <servlet-mapping> <servlet-name>AdminServlet</servlet-name> <url-pattern>/servlet/AdminServlet</url-pattern> </servlet-mapping>
Like in the remote configuration example, you need to get a reference to the RoleInstanceDiagnosticManagersForRole class. This reference will let you work with the configuration manager for each instance. In this example, you re going to be transferring the performance counter data over to an Azure table q. This transfer will include all counters you might have running from prior configuration changes. You use the OnDemandTransferOptions class to configure how the transfer should happen. This class has several parameters that you ll want to set. Set a time filter at w,
The fourth result was included here to help show the changes that have taken place. Notice how much the documents (D, F, and H) have shuffled; but not B. Even though the printout still shows the actual term frequency with (description:salesman)=2, the term frequency at I has changed from 2 to 1 as we expected from our overriding of the term frequency method. This changed the term frequency value from 1.4142125 to 1, reducing the overall score and dropping it lower in the results. We need to discuss one last thing about this explanation printout. Take a close look at the fieldNorm values B, E, G, and J. Hopefully you have noticed that the field normalization value has a huge impact on the final score. When the field you are searching is long (read that as has many terms ), the fieldNorm value can become quite small, reducing the score by a large amount. There are several ways around this normalization effect if you wish to eliminate it from your method of scoring:
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