8 loop l_query := replace( l_query, lpad('@',10-i,'@'), '@' ); l_query := replace( l_query, lpad(' ',10-i,' '), ' ' ); end loop; return upper(l_query); end; / update t1 set sql_text_wo_constants = remove_constants(sql_text); select sql_text_wo_constants, count(*) from t1 group by sql_text_wo_constants having count(*) 100 order by 2 / The output of that last query will show you statements that are identical in the shared pool after all numbers and character string constants have been removed.
These statements -- and more importantly their counts -- are the potential bottlenecks.
Consider the following two tables: You have been tasked with updating the employee salaries in the EMPLOYEES table with the maximum salary for the same employee, based on EMPLOYEE_ID, in the NEW_SALARY_INFO table. There is no index on the NEW_SALARY_INFO table so the database will have to full scan a four million row table for each of the one million employee records to find the maximum salary.
As you can probably guess, there are situations where using PL/SQL can be the better option.
Such as in life, in technology the only guarantee is that there are no guarantees.
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