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Listing 10-2. Using the Properties of the Exception Class // exception_properties.cpp using namespace System; int main() { try { bool error = true; // other code if (error) { throw gcnew Exception("XYZ"); } } catch( Exception^ exception) { Console::WriteLine("Exception Source property {0}", exception->Source); Console::WriteLine("Exception StackTrace property {0}", exception->StackTrace); Console::WriteLine("Exception Message property {0}", exception->Message); } } The output of Listing 10-2 is as follows: Exception Source property exception_properties Exception StackTrace property at main() Exception Message property XYZ When an unhandled exception occurs in a console application, the Message and StackTrace data are printed to the standard error stream, like this: Unhandled Exception: System.Exception: XYZ at main() There s also a property of the Exception class called InnerException, which may reference an exception that gives rise to the exception we re looking at. In this way, a cascading series of exceptions may be nested one within the other. This could be useful if an exception occurs deep down in low-level code, but there are several layers of libraries between the problem and the code that knows how to handle such situations. As a designer of one of the intermediate libraries, you could choose to wrap that lower exception as an inner exception and throw a higher exception of a type that is more intelligible to your clients. By passing the inner exception,

The cost of a tablescan is largely the cost of assumed multiblock reads To calculate the cost, the optimizer divides the number of used blocks in the table (below the high water mark) by a number representing the assumed size of the multiblock read (It was only when I wrote this line for the summary that I thought how nice it would be if the parameter included the word size instead of count and was expressed in KB) In 8i, this calculated count of the required number of multiblock reads is the cost In 9i, the introduction of system statistics allows the result to be adjusted by factors representing typical sizes and relative speeds of multiblock reads, and adding in the CPU cost of visiting the blocks and acquiring data from every row in the blocks.

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And 10g holds some clues that at some future date the optimizer will also factor in recent cache history, which is likely to result in a reduced value for the cost For index fast full scans, the number of leaf blocks in the index, rather than the number of blocks below the high water mark, seems to be the driving value used in the calculation In many cases, this will give a reasonable result There are a couple of scenarios, though, where the number of leaf blocks can be much smaller than the number of blocks below the high water mark, and this would result in the cost of an index fast full scan being seriously underestimated Partitioned tables are likely to be a problem The optimizer can use the statistics from a single partition if the partition can be identified at parse time; otherwise it uses the table-level statistics.

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the inner exception information can be used by the error-handling code to respond more appropriately to the real cause of the error.

And the same type of strategy appears with subpartitions of a single partition In many cases, you may find that the only way to get the optimizer to produce sensible plans is to refresh the table-level statistics as you do partition maintenance This may prove to be a resourceintensive approach..

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plan_run81.sql plan_run92.sql tablescan_01.sql calc_mbrc.sql tablescan_01a.sql tablescan_01b.sql set_system_stats.sql tablescan_02.sql tablescan_03.sql tablescan_04.sql cpu_costing.sql parallel.sql parallel_2.sql index_ffs.sql hack_stats.sql partition.sql setenv.sql

Adjust Zoom: Glide the Trackpad up/down or use the Volume keys on the right side to adjust the Zoom level (see Figure 22-2).