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You have just seen that PL/SQL bulk binding can be more effective than processing one row at a time However, the fact is that if an equivalent pure SQL solution exists, then there is a good chance that this solution will provide better performance still It s a good idea to use PL/SQL, as appropriate, in your applications, but don t use it to do the job of SQL In the following examples, you ll learn how, with good knowledge of SQL, you can improve performance even further Example 1: PL/SQL Bulk Bind vs SQL Multitable Insert We compare two approaches in this section: In the first approach, we use the bulk_bind method defined in the previous section (see the example in the previous section).

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In the second approach, we use a single multitable insert statement to accomplish the same goal (please see section INSERT of Oracle Database SQL Reference (10g Release 1) if you are not familiar with multitable insert syntax) As part of our SQL solution, we define a second procedure called single_sql_statement as follows: benchmark@ORA10G> create or replace procedure single_sql_statement 2 as 3 begin 4 insert all 5 when ( x > 0 ) then 6 into destination_table(x) values (x) 7 when ( x <= 0 ) then 8 into bad_records_table( x, error_message ) values ( x, error_message ) 9 select x, case 10 when x > 0 then null 11 when x <= 0 then 'invalid record: negative or zero number' 12 end error_message 13 from source_table; 14 commit; 15 end; 16 / Procedure created.

In my tests using JRunstats, on average, the SQL-based approach ran in 50% of the time and consumed 75% of the latches as compared to the PL/SQL bulk bind approach In general, you will find that a SQL-based solution, if available, will almost always outperform an equivalent PL/SQL procedural solution, often by a wide margin..

The first panel (Panel2) is essentially the header where the image to expand/collapse the panel is located. The majority of the actual content is in the second panel. In this case, the content is being generated by a method called GetContentFillerText. So notice that while the TargetContronID property of the CollapsiblePanelExtender is set to Panel1, the ExpandControlID and CollapseControlID properties are both set to Panel2, which is essentially the header panel. The small icon on the right portion of the header changes depending on the state of the panel as specified by the ExpandedImage and CollapsedImage properties. Figure 7-15 shows this panel in expanded mode.

In general, a SQL solution will outperform a PL/SQL solution. SQL is a very powerful language, and the Tip more you master it, the more you will be able to exploit it, thereby improving the performance and scalability of your code tremendously.

Example 2: Using the Power of Analytic Functions Let s end this section with another example that illustrates the power of SQL. We first implement a small specification in PL/SQL. Next, we improve upon our PL/SQL solution by using SQL. Finally, we further improve our SQL solution by using SQL analytic functions. If you are unfamiliar with SQL analytic functions, you have been missing out on one of the greatest innovations of the Oracle SQL engine. SQL analytic functions have been available since version 8.1.6, and they have improved in functionality and features with each subsequent release.

CHAPTER 7 USING THE ASP.NET AJAX CONTROL TOOLKIT (PART 1)

(10g Release 1). Don t be misled by the fact that they are documented in the Data Warehousing Guide document; they are very useful in any application that uses SQL on Oracle.

Now, on to our example. Suppose the requirement of our code is as follows: For each department, get all the employees who earn an above average or average salary for the department, and insert these records into a table called above_avg_emp. Insert the remaining employee records into the below_avg_emp table. Let s create the schema for this scenario. We first create a table called emp in our schema and populate it with 20,000 employees (dummy data) who work in three departments (department numbers 10, 20, and 30): benchmark@ORA10G> create table emp as 2 select 'name' ||rownum as ename, 3 (mod( rownum, 3 ) + 1)*10 as deptno, 4 trunc(dbms_random.value(1000, 6000)) as sal 5 from all_objects 6 where rownum <= 20000; Table created. benchmark@ORA10G> select count(*), count(distinct deptno) from emp; 20000 3

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