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// Configure the receiver to listen to events // from the specified sender. receiver->SetUpToReceive(sender); EventArgs^ args = gcnew EventArgs(); sender->Fire(args); } Here is the output of Listing 7-19:

Do the following to make sure you have the Snooze option active: 1. 2. 3. 4. Open the Calendar application. Push the Menu key and glide down to Options. Click General Options. Look under the Actions subheading and set the field next to Snooze to something other than None.

It is possible that Oracle is using a form of the heapsort, which would start by loading data into a partly ordered tree structure known as a heap. (The word heap sometimes means something far more structured than the way teenagers store their belongings.) A heapsort then uses a shuffle-down mechanism to restructure the heap into a fully sorted structure. I have discounted the heapsort as Oracle s mechanism for sorting because even though the number of comparisons used is appropriate, the optimum implementation of the heapsort algorithm needs only one pointer per entry rather than the three which, given the amount of memory involved, Oracle seems to use. Interestingly, I have heard comments that the 10gR2 release is very much faster at sorting than previous releases so perhaps the Oracle developers have finally changed the algorithm and the code will have switched to a heapsort by the time you read this note.

It s possible you will want to increase the time until the Snooze alarm goes off. If so, follow these steps: 1. 2. Open and scroll down to the scheduled time and change that. Use the number keys on your BlackBerry to change the date or time. For example, typing 25 in the Minutes field would change the time to :25. Or, you can change the hours or days by highlighting them and pressing the Space key.

The final column in the table reports the total number of comparisons performed As you can see, this doesn t really change significantly, as the balance shifts from in-memory sorting to merge sorting But the previous table showed that we used increasing amounts of CPU as we shifted from the disk based to the memory-based sort How could this happen It seems a little unlikely that the CPU time of an actual comparison between data items is different in the two types of operation but it could take more CPU to walk up and down the tree to find something to compare with! When we did the full in-memory sort, we had a pretty tall tree to traverse (the height of the tree is log2(number of rows)).

The System::EventArgs class is itself not capable of passing custom event arguments. To define events that do contain additional data, you need to define a class derived from EventArgs that contains the required data. Listing 7-20 demonstrates how to use a class derived from EventArgs to send data about an event that can be used in the event handler to customize the response. You ll want to create a new event handler delegate type to match the custom EventArgs type. Listing 7-20. Providing Custom Event Data // eventargs.cpp using namespace System; ref class MyEventArgs : EventArgs { public: property String^ Info; MyEventArgs(String^ info) { Info = info; } }; delegate void MyEventHandler(Object^ sender, MyEventArgs^ args); // This class generates an event. ref class EventSender { public: event MyEventHandler^ MyEvent;

With your BlackBerry, you can invite people to meetings and reply to meeting invitations. If your BlackBerry is connected to a BlackBerry Enterprise Server (BES), you may also be able to check your invitees availability for specific times, as well.

But when we sorted a small fraction of the data (4% in our smallest test case earlier) before dumping it, each individual inmemory sort run produced a much shorter tree so the total CPU time spent traversing trees was a lot less And the final merge is only traversing a very short tree as well It s not the data comparisons that cost us CPU, it s traversing the pointers that make up the trees It is important to realize that if your bottleneck is CPU and your I/O subsystem is not under pressure, then you may be able to improve your performance on large sorts by switching from in-memory sorts to using the minimal amount of memory that can produce a onepass sort.