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2. You haven t changed the signature of any of the methods in the service, so there is no need to update the reference from within your consumer. You just need to recompile the application to ensure that this change is applied. Then you re ready to test the application again to see that this caching is working. Press F5 (the compile and debug shortcut) to do both. 3. Within the test application main page, enter the apress login and password, and then click the Refresh button. This will show all the requests for contact that this user has made so far. 4. Switch to the Friends Reunion web site, log in with a different user credentials, such as login vga and password vga, and make a new request for contact with Daniel Cazzulino (the one with the apress login and password), using the Search.aspx facility you created in 6. 5. Return to the consumer application and click the Refresh button again. If less than 10 minutes have passed since the last time you clicked the Refresh button (more precisely, since the server-side method was executed, and therefore, its output entered the cache), the test application s grid will show the cached version of the data again, so you won t see the new request for contact you just added via the web site. However, the speed boost with your GetContactRequests() method should be noticeable. After a 10-minute period, a fresh output will be generated, as the data in the cache will have expired, so the grid will include the new request for contact.
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10053 trace) and the parallel cost at full parallelism (the Resp figures in a 10053 trace), and then picks the point along the line from serial to parallel that represents your required percentage (The same interpolation mechanism applies to sorting and to some aspects of hash joins, but the simple tablescan is the best way to demonstrate the arithmetic) For example, from the table of 9i results, the cost of parallel degree 4 is 380, and the cost of a serial scan is 1519 If we set _optimizer_percent_parallel to 75, then the final cost would be calculated as 25% of 1519 plus 75% of 380, which comes to 66475 You might note from the table of results that running parallel 4 at 75% does not give you the same cost as running parallel 3 at 100%.
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Yet another consideration comes into play in 9i and 10g if you set the parameter parallel_adaptive_multi_user to true (and this is the default value for 10g) When this is set, only a limited number of users are allowed to run at the default degree of parallelism and on my test systems, this limit was one in 9i, and two in 10g So the optimizer is effectively costing parallel execution on the basis that no more than one or two parallel queries are going to be running at any one moment The limit is set by the hidden parameter _parallel_ adaptive_max_users, but don t fiddle with it as it s one of the parameter values used by Oracle at startup time to calculate the value of parallel_max_servers, so it will have side effects Other oddities occur with the costing of parallel tablescans.
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ll the data displayed in a report comes from the report parameters and report fields This data can be processed using the report variables and their expressions Some variables are initialized according to their reset type when the report starts, or when a page or column break is encountered, or when a group changes Furthermore, variables are evaluated every time new data is fetched from the data source (for every row) But simple variable expressions cannot always implement complex functionality This is where scriptlets come in Scriptlets are sequences of Java code that are executed every time a report event occurs Through scriptlets, users can affect the values stored by the report variables Since scriptlets work mainly with report variables, it is important to have full control over the exact moment the scriptlet is executed.
We ve just covered how to lower the processing overhead using caching, but this still leaves the time taken to request data and retrieve results This part of the overall round-trip time is governed by two factors: the amount of data and the speed at which it can be transmitted There is little that you can do to improve transmission speed without paying for faster Internet connections, leaving you with the option of reducing the amount of data transferred When you re making simple calls, such as to the GetAttendees() method, not much can be done to decrease the amount of data, since there is very little data there to start with However, in the case of retrieving a list of contact requests, you can apply optimizations, ranging from better serialization of the DataSet itself to completely replacing it with more efficient and resource-conservative representations.
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