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Reduce the amount of session logging on/off activity by users. This may reduce scalability due to the increased amount of overhead involved in authenticating the user, verifying privileges, and so on, leading to a waste of time and resources. Furthermore, the users may be spending more time trying to log into the system than executing their SQL statements. Frequent logging off and logging back on might also cause contention for the web server and other resources, and increase the time it takes to log into your system. To increase scalability, you must also ensure that applications share sessions. If you only have shared SQL, your hard parses will go down, but your soft parses might still be high. If an application program can maintain a persistent connection to the Oracle server, it doesn t have to perform repeated soft parsing to reuse code.

The best way to set the size of the shared pool in Oracle Database 11g is to let Oracle do all the work for you by using the MEMORY_TARGET initialization parameter, thus automating the management of SGA. You can initially set the SGA_TARGET parameter at something close to the total SGA you would have allocated under a manual management mode. Review the material in 17 for guidance on setting your initial MEMORY_TARGET value.

6,267,036 (319.00) 620,001 (2.80) 1,700,907 (3.69) 95,190 (1.10)

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As I have discussed, if code objects have to be repeatedly hard-parsed and executed, database performance will deteriorate eventually. Your goal should be to see that as much of the executed code remains in memory as possible so compiled code can be reexecuted. You can avoid repeated reloading of objects in your library cache by pinning objects using the DBMS_SHARED_POOL package. (The library cache is a component of the shared pool, as you ve seen earlier.) Listing 20-4 shows how you can determine the objects that should be pinned in your library cache (shared pool). Listing 20-4. Determining the Objects to Be Pinned in the Shared Pool SQL> 2 3 4 5 6* SELECT type, COUNT(*) OBJECTS, SUM(DECODE(KEPT,'YES',1,0)) KEPT, SUM(loads) - count(*) reloads FROM V$DB_OBJECT_CACHE GROUP BY type ORDER BY objects DESC;

TYPE OBJECTS KEPT RELOADS ---------------------------- ---------- ---------- ---------CURSOR 41143 0 136621 NOT LOADED 37522 0 54213 TABLE 758 24 133742 PUB_SUB 404 0 135 SYNONYM 381 0 7704 JAVA CLASS 297 296 317 VIEW 181 0 11586 INVALID TYPE 139 48 11 PACKAGE 137 0 8352 TRIGGER 136 0 8515 PACKAGE BODY 121 0 218 SEQUENCE 81 0 3015 INDEX 61 7 0 PROCEDURE 41 0 219

FUNCTION NON-EXISTENT TYPE CLUSTER TYPE BODY LIBRARY RSRC CONSUMER GROUP QUEUE JAVA SHARED DATA JAVA SOURCE 24 rows selected. SQL>

From Table 8-1, we can draw the following performance-related conclusions: In general, the relational tables based solution outperforms the other two solutions (in many cases by orders of magnitudes, both in terms of elapsed times and latches). The object views based solution performs rather poorly when compared to the nested tables based solution when it comes to inserts, deletes, and updates. This can be attributed to the overhead of the instead of triggers that do all the work behind the scenes. When it comes to selects, object views perform much better than the nested tables based solution. From the discussion we have had so far in this chapter, we can conclude the following about the code maintenance of all three approaches: In general, the code written on top of the relational schema is much more maintainable and also more open to be accessed from various tools that work using SQL as compared to schema that uses objects as storage mechanism. The code complexity increases tremendously for both object views and the nested tables based schema. On the whole, it is a good idea to always give preference to a pure relational tables based approach given the performance benefits and the other benefits, as discussed in the earlier sections. If you do have a good reason to choose otherwise, then the second choice, in general, may be the object views based solution, especially if the inserts, deletes, and updates are done directly on the underlying tables and only selects, when required, are done on the object view itself.

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