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Not very much has changed, really, and this new version takes several more lines of code to implement than property list serialization, so you might be wondering if there really is an advantage to using archiving over just serializing property lists. For this application, the answer is simple: there really isn t. But, think back to the last example in 9 where we were letting the user edit a list of presidents, and each president had four different fields that could be edited. To handle archiving that list of presidents with a property list would involve iterating through the list of presidents, creating an NSDictionary instance for each president, copying the value from each of their fields over to the NSDictionary instance, and adding that instance to another array, which could then be written to a property list file. That is, of course, assuming that we restricted ourselves to using only serializable properties. If we didn t, using property list serialization wouldn t even be an option without doing a lot of conversion work. On the other hand, if we had an array of archivable objects, such as the FourLines class that we just built, we could archive the entire array by archiving the array instance itself. Collection classes like NSArray, when archived, archive all of the objects they contain. As long as every object you put into an array or dictionary conforms to NSCoding, you can archive the array or dictionary and restore it, and all the objects that were in it when you archived it will be in the restored array or dictionary. In other words, this approach scales beautifully (in

terms of code size, at least), because no matter how many objects you add, the work to write those objects to disk (assuming you re using single-file persistence) is exactly the same. With property lists, the amount of work increases with every object you add.

This is where a participant is notified by the depository that a trade has been settled; this includes the settlement details. public void SettleTrade ( Settlement settlement );

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The third persistence option we re going to discuss is the iPhone s embedded SQL database called SQLite3. SQLite3 is very efficient at storing and retrieving large amounts of data. It s also capable of doing complex aggregations on your data, with much faster results than you d get doing the same thing using objects. For example, if your application needed to calculate the sum of a particular field across all the objects in your application, or if you needed the sum from just the objects that meet certain criteria, SQLite3 would allow you to do that without loading every object into memory. Getting aggregations from SQLite3 is several orders of magnitude faster than loading all the objects into memory and summing up their values. Being a full-fledged embedded database, SQLite3 contains tools to make it even faster by, for example, creating table indexes that can speed up your queries.

Now that we have the data set up, we can load the aggregate assembly into the database. If you used the project from the last chapter, it will have both the Duration UDT and AvgDuration UDA, so be sure to load both. We can then create the UDA within SQL Server 2005 and test it out. CREATE ASSEMBLY DurationObjects FROM 'C:\Program Files\SQL Server Assemblies\Duration.dll' WITH PERMISSION_SET = SAFE GO CREATE AGGREGATE AvgDuration(@TimeValue Duration) RETURNS Duration EXTERNAL NAME DurationObjects.AvgDuration GO SELECT dbo.AvgDuration(TimeTaken) As AvgDuration FROM AvgTime GROUP BY TimeId

There are two schools of thought about the pronunciation of SQL and SQLite. Most official documentation says to pronounce SQL as Ess-Queue-Ell and SQLite as Ess-Queue-Ell-Light. Many people pronounce them, respectively, as Sequel and Sequel Light.

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