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Periods feature to compare the changes in key database metrics between two time intervals. As you know, an AWR snapshot captures information between two points in time. However, you can use the Time Periods Comparison feature to examine the difference in database metrics between two different time intervals or periods, by analyzing performance statistics captured by two sets of AWR snapshots. If your nightly batch job ran just fine on Tuesday but was slow on Wednesday, you can find out why, using the Compare Periods Report. To use the Compare Periods Report, use the following steps: 1. In the Database Control home page, click the Performance tab. 2. Under the Additional Monitoring Links group, click the Snapshots link. 3. In the drop-down list for Actions, select Compare Periods and click Go. 4. The Compare Periods: First Period End page appears. You must select the start time for the comparison analysis by selecting an ending snapshot ID for the first period. You may also choose a time period, if you wish, instead of the ending snapshot ID. Click Next. 5. The Compare Periods: Second Period Start page is next. You must select a snapshot ID to mark the beginning of the second period. Click Next. 6. The Compare Periods: Second Period End page is next. You select the ending snapshot for the second period on this page and click Next. 7. The Compare Periods: Review page is next, as shown in Figure 22-9. It shows the first period and second period beginning and ending snapshot IDs. After confirming that the first and second period ranges are correct, click Finish. 8. You ll now get the Compare Period: Results page, which summarizes the differences in key database metrics between the two periods.

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Figure 22-9. The Compare Periods: Review page Going through the differences in key database metrics between the two periods helps you identify the root causes of the performance slowdown in the latter period when compared to the earlier good period. You can also view the database configuration differences between the two periods as well.

To compare the two periods in detail and to drill down into various items such as SQL statements executed, SGA usage, and so on, click the Report link in the Compare Periods: Results page. You can see a nicely formatted report comparing the two periods on the basis of configuration, top five timed events, and Load Profile. By viewing the various statistics for the two periods, you can determine if there was excessive load or some such thing during the second period. At the bottom of the report, you ll find the Report Details section, with links for various items like wait events, I/O statistics, segment statistics, and SGA statistics. You can click any of these links to drill down into what exactly went on inside the database during the two periods. For example, by clicking the SQL Statistics link, you can get to the top ten SQL statements compared by execution time, CPU time, buffer gets, physical reads, and so on. For example, Figure 22-10 shows the top ten SQL statements compared on the basis of physical reads during each period.

Another received e-mail messages that contained system-setup parameters for numerous remote systems, such as the patch level or the names of installed applications Procmail would process these messages based on their subject lines and categorize the received information for later review It was a very convenient way of tracking system-configuration information The example I will demonstrate here is a simplified version of a procmail script I set up to deal with the lack of direct access to my home system from work, and the lack of convenient access to my work system from home My home system periodically dialed my ISP to gather e-mail From time to time I would want to get a file from my home system or find out a system setting on my work system while I was at home.

Figure 22-10. The Top 10 SQL Comparison report Instead of running myriad SQL scripts and manually examining various statistics, as is the tradition, you can use the Compare Periods feature to zoom in quickly on the reasons for deterioration in recent database performance compared to a past period of time.

The concept of automatic disposal is also applied if you define managed classes with implicitly dereferenced member variables. The following code defines a managed class FileDumper with two fields of type FileStream and StreamReader: public ref class FileDumper { FileStream fs; StreamReader sr; public: FileDumper(String^ name) : fs(name, FileMode::Open), sr(%fs) {} void Dump() { Console::WriteLine(sr.ReadToEnd()); } }; For these fields, the compiler generates a constructor that ensures construction of the member variables and an IDisposable implementation that calls the destructors for the member variables. Both construction and destruction of the sub-objects is done in an exception-safe way. The following pseudocode describes what the compiler generates for the FileDumper constructor: FileDumper::FileDumper(String^ name) // pseudocode { // instantiate the first sub-object FileStream^ fs = gcnew FileStream(name, FileMode::Open); // if successful ... try { // ... assign tracking handle of new object to member variable this->fs = fs; // initialize second sub-object StreamReader^ sr = gcnew StreamReader(fs);

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