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0.00 0.00 0 0 0 -------- ---------- ---------- ---------- ---------0.49 0.50 0 15439 948

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0 ---------9999

from their primary objective in order to handle the crosscutting concerns. Further, since different concern implementations may need different skill sets, either several people will have to collaborate on the implementation of a module or the developer implementing the module will need knowledge of each domain. The more concerns you implement together, the lower your probability of focusing on any one thing. Lower code reuse If a module is implementing multiple concerns, other systems requiring similar functionality may not be able to readily use the module due to a different set of concerns they might need to implement. Consider a database access module. One project may need one form of authentication to access the database, another project may need a different form, and still another may need no authentication at all. The variation of crosscutting requirements may render an otherwise useful module unusable. Poor quality Code tangling makes it more difficult to examine code and spot potential problems, and performing code reviews of such implementations is harder. For example, reviewing the code of a module that implements multiple concerns will require the participation of an expert in each of the concerns. Often not all of them are available at the same time, and the ones who are may not pay sufficient attention to the concerns that are outside their area of expertise. Difficult evolution An incomplete perspective and limited resources often result in a design that addresses only current concerns. When future requirements arise, they often require reworking the implementation. Because implementation is not modularized, this may mean modifying many modules. Modifying each subsystem for such changes can lead to inconsistencies. It also requires spending considerable testing effort to ensure that this implementation change does not introduce regression bugs.

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But with the index, it takes about 1.2 seconds: call count ------- -----Parse 1 Execute 1 Fetch 0 ------- -----total 2 cpu elapsed disk query current -------- ---------- ---------- ---------- ---------0.03 0.04 0 0 0 1.14 1.12 2 15650 7432 0.00 0.00 0 0 0 -------- ---------- ---------- ---------- ---------1.17 1.16 2 15650 7432 rows ---------0 9999 0 ---------9999

0 1 1

All of these problems lead to a search for better approaches to architecture, design, and implementation. Aspect-oriented programming offers one viable solution. In the next section, we introduce you to AOP and give you a little of its history.

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This was the overhead introduced in the management of the new index on the MY_SOUNDEX function both in the performance overhead of simply having an index (any type of index will affect insert performance) and the fact that this index had to call a stored procedure 9,999 times. Now, to test the query, we ll just rerun the query: ops$tkyte@ORA10G> REM reset our counter ops$tkyte@ORA10G> exec stats.cnt := 0 PL/SQL procedure successfully completed. ops$tkyte@ORA10G> set timing on ops$tkyte@ORA10G> set autotrace on explain ops$tkyte@ORA10G> select ename, hiredate 2 from emp 3 where substr(my_soundex(ename),1,6) = my_soundex('Kings') 4 / ENAME HIREDATE ---------- --------Ku$_Chunk_ 10-AUG-04 Ku$_Chunk_ 10-AUG-04 Elapsed: 00:00:00.02 Execution Plan ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=2 Card=1 Bytes=16) 1 0 TABLE ACCESS (BY INDEX ROWID) OF 'EMP' (TABLE) (Cost=2 Card=1 Bytes=16) 2 1 INDEX (RANGE SCAN) OF 'EMP_SOUNDEX_IDX' (INDEX) (Cost=1 Card=35) ops$tkyte@ORA10G> ops$tkyte@ORA10G> ops$tkyte@ORA10G> ops$tkyte@ORA10G> 2 set autotrace off set timing off set serveroutput on exec dbms_output.put_line( stats.cnt );

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If we compare the two examples (unindexed versus indexed), we find that the insert was affected by a little more than doubling the runtime However, the select went from over a second to effectively instantly The important things to note here are the following: The insertion of 9,999 records took approximately two times longer Indexing a userwritten function will necessarily affect the performance of inserts and some updates You should realize that any index will impact performance, of course For example, I did a simple test without the MY_SOUNDEX function, just indexing the ENAME column itself That caused the INSERT to take about one second to execute the PL/SQL function is not responsible for the entire overhead Since most applications insert and update singleton entries, and each row took less than 1/10,000 of a second to insert, you probably won t even notice this in a typical application.

AOP builds on top of existing methodologies such as OOP and procedural programming, augmenting them with concepts and constructs in order to modular, ize crosscutting concerns. With AOP you implement the core concerns using the chosen base methodology. For example, if OOP is the base methodology, you

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