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But what can we do to improve this situation Even with new storage options such as Exadata, which is already promising to meet the storage throughput requirements illustrated here, does it make sense to simply rely on sheer processing and storage power to save the day Or, can we push the requirements back down, reduce the requirements, to meet the state of the art as it improves to meet us Pushing the horizon of infinity further has to be accomplished step by step If the entire task is considered in its entirety only, it might well be impossible But if you take the big problem, break it down into chunks, and attack each chunk, you can achieve success in the face of the most extreme requirements You can reach 50TB a day In fact, it is already here.

mount operation will fail. Because we are passing the owners flag with a value of on,| we are ensuring that any ownership on the volume is preserved, which allows you to utilize normal file system permissions to secure data on mounted volumes. For more information on utilizing file system permissions, refer to 4. To unmount or detach the image, we simply use the detach verb and pass it the volume path:

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bool IsQueryCompleted() { return result->IsCompleted; } // This function gets called when the asynchronous call // completes. void ProcessResult(IAsyncResult^ result) { // Retrieve the delegate. QueryFunc^ caller = (QueryFunc^) result->AsyncState; // Get the data back (fill in DataSet parameter). caller->EndInvoke(result); Console::WriteLine(m_r->Value); } void UseData() { // Do something... } }; int main() { Document doc("Old Value"); doc.InitiateQuery("SELECT * FROM Plants WHERE Plant.Genus = 'Lycopersicon'"); // Do other work while the query executes. // Poll for completion. while (! doc.IsQueryCompleted() ) { Thread::Sleep(100); } // Do work with the data. doc.UseData(); } Here is the output of Listing 7-14: Old Value New Value

In mid-2009, I was contracted to begin implementation of a data warehouse that was expected to reach a size of 9PB after 12 months A little basic math shows that as loading approximately 25TB per day The scope of the project was later scaled way back, and the data volumes hacked to a fraction of that total, but the mission and the data to support it is still out there, waiting to be loaded and exploited The future is now And obscenely large Oracle databases are up and running right this minute, and more are being built Here is how they become feasible..

Caution Although software firewalls such as the one built into Linux offer a high level of protection, it s

Figure 1-15. Passing a DataSet between the Business and Data Access layers This approach has the maintenance and code-reuse flaws that I ve talked about, but the fact is that it gives pretty good performance in most cases. Also, it doesn t hurt that most programmers are pretty familiar with the idea of writing code to manipulate a DataSet, so the techniques involved are well understood, thus speeding up development. A decision to stick with an object-oriented approach should be undertaken carefully. It s all too easy to compromise the object-oriented design by taking the data out of the objects running on one machine, sending the raw data across the network, and allowing other objects to use that data outside the context of the objects and business logic. Such an approach would break the encapsulation provided by the logical Business layer.

namespace UsingStatement { class Program { static void Main( ) { // using statement using (TextWriter tw = File.CreateText("Lincoln.txt") ) { tw.WriteLine("Four score and seven years ago, ..."); } // using statement using (TextReader tr = File.OpenText("Lincoln.txt")) { string InputString; while (null != (InputString = tr.ReadLine())) Console.WriteLine(InputString); } } } } This code produces the following output: Four score and seven years ago, ...

DBTYPE_I8 DBTYPE_BYTES DBTYPE_BOOL DBTYPE_BSTR DBTYPE_STR DBTYPE_CY DBTYPE_DATE DBTYPE_DBDATE DBTYPE_DBTIME DBTYPE_DBTIMESTAMP DBTYPE_DECIMAL DBTYPE_R8 DBTYPE_ERROR DBTYPE_FILETIME DBTYPE_GUID DBTYPE_I4 DBTYPE_LONGVARCHAR DBTYPE_NUMERIC DBTYPE_R4 DBTYPE_I2 DBTYPE_I1 DBTYPE_UI8 DBTYPE_UI4 DBTYPE_UI2 DBTYPE_VARCHAR DBTYPE_VARIANT DBTYPE_WVARCHAR DBTYPE_WSRT

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