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Because both Singleton and SingleCall activation types create instances using the default constructor, the programmer cannot configure instances of the class by passing in arguments during construction. However, it is possible to publish an already created and configured instance of the class as a Singleton using the following call:
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than the specified date part; rather, it takes into consideration only lower ones . For example, when you calculate the following difference in years between two very close values, you get 1: DATEDIFF(year, 20091231 , 20100101 ) . DATEDIFF ignores those part of the values that have a higher level of granularity than year . (That is, it ignores the month, day, hour, and so on .)
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exManager.Process(() => method_name(param1, param2), "Exception Policy Name");
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public static void Main() { Int32 v = 5; Object o = v; v = 123; Console.WriteLine(v); v = (Int32) o; Console.WriteLine(v); }
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SELECT custid, empid, YEAR(orderdate) AS orderyear, MONTH(orderdate) AS ordermonth, SUM(qty) AS qty FROM dbo.Orders GROUP BY GROUPING SETS ( ( custid, empid, YEAR(orderdate), MONTH(orderdate) ), ( custid, empid, YEAR(orderdate) ), ( custid, YEAR(orderdate), MONTH(orderdate) ), ( custid, YEAR(orderdate) ), ( empid, YEAR(orderdate), MONTH(orderdate) ), ( empid, YEAR(orderdate) ) );
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As you can see from the previous section, Enterprise Library provides a comprehensive set of features that can help you to manage your crosscutting concerns though a reusable set of components and core functionality. Of course, like many developers, you may suffer from the well-known NIH (not invented here) syndrome. But, seriously, isn t it about time that every developer on your team stopped writing his or her own logging framework It s a commonly accepted fact that the use of standard and proven code libraries and components can save development time, minimize costs, reduce the use of precious test resources, and decrease the overall maintenance effort. In the words of the Librarian, These days you cannot afford not to reuse.
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Despite the simplicity of the Easy Gallery interface, the extension includes the following advanced features: It understands ZIP file archives, so multiple images can be added to the gallery at once. It allows server-side directories to be scanned for multi-image addition. It provides upload through FTP for image submission so that ownership and access problems can be avoided.
An index on the sort column (empid) happens to be the Sales table s clustered index. The table is rst fully scanned (as indicated by the Clustered Index Scan operator) to return all rows. For each row returned from the initial full scan, the Nested Loops operator invokes the activity that generates the row number by counting rows. Each row number calculation involves a seek operation within the clustered index, followed by a partial scan operation (from the head of the leaf level s linked list to the last point where S2.empid is smaller than or equal to S1.empid). Note that two different operators use the clustered index rst, a full scan to return all rows; second, a seek followed by a partial scan for each outer row to achieve the count. Remember that the primary factor affecting the performance of queries that do data manipulation is usually I/O. An estimate of the number of rows accessed here will show how inef cient this execution plan is. To calculate rownum for the rst row of the table, SQL Server needs to scan 1 row in the index. For the second row, it needs to scan 2 rows. For the third row, it needs to scan 3 rows, and so on, and for the nth row of the table, it needs to scan n rows. For a table with n rows, having an index based on the sort column in place, the total number of rows scanned (besides the initial scan of the data) is 1 + 2 + 3 + . . . + n. You may not grasp immediately the large number of rows that are going to be scanned. To give you a sense, for a table with 100,000 rows, you re looking at 100,000 + 5,000,050,000 rows that are going to be scanned in total.
Obviously, the WithCancellation method allows you to pass a CancellationToken so that the query processing can be stopped prematurely . The WithDegreeOfParallelism method specifies the maximum number of threads allowed to process the query; it does not force the threads to be created if not all of them are necessary . Usually you will not call this method, and, by default, the query will execute using one thread per core . However, you could call WIthDegreeOfParallelism, passing a number that is smaller than the number of available cores if you want to keep some cores available for doing other work . You could also pass a number that is greater than the number of cores if the query performs synchronous I/O operations because threads will be blocking during these operations . This wastes more threads but can produce the final result in less time . You might consider doing this in a client application, but I d highly recommend against performing synchronous I/O operations in a server application . Parallel LINQ analyzes a query and then decides how to best process it . Sometimes processing a query sequentially yields better performance . This is usually true when using any of these operations: Concat, ElementAt(OrDefault), First(OrDefault), Last(OrDefault), Skip( While), Take( While), or Zip . It is also true when using overloads of Select(Many) or Where that pass a position index into your selector or predicate delegate . However, you can force a query to be processed in parallel by calling WithExecutionMode, passing it one of the ParallelExecutionMode flags:
internal sealed class SomeType { private Int32 m_x = 5; }
This code calls Type s IsDefined method, effectively asking the system to look up the metadata for the enumerated type and see whether an instance of the FlagsAttribute class is associated with it . If IsDefined returns true, an instance of FlagsAttribute is associated with the enumerated type, and the Format method knows to treat the value as though it contained a set of bit flags . If IsDefined returns false, Format treats the value as a normal enumerated type .
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One longstanding piece of conventional wisdom that shouldn t be left unmentioned is the advice that when you run into a performance bottleneck, you should recode in assembler. Recoding in assembler tends to improve both speed and code size. Here is a typical approach to optimizing with assembler: 1. Write 100 percent of an application in a high-level language. 2. Fully test the application, and verify that it s correct.
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