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I often use an analogy to describe parallel processing and why you need both a large task and sufficient free resources in the database. It goes like this: suppose you have two tasks to complete. The first is to write a one-page summary of a new product. The other is to write a ten-chapter comprehensive report, with each chapter being very much independent of the others. For example, consider this book: this chapter, Parallel Execution, is very much separate and distinct from the chapter titled Redo and Undo they did not have to be written sequentially. How do you approach each task Which one do you think would benefit from parallel processing

Now let s write an aspect that will introduce a crosscutting concern (such as authentication) to BusinessClass. As a part of the concern implementation, the before advice to the operations() pointcut calls a method concernLogic(), which throws a checked exception. As a first implementation, we let the exception thrown by concernLogic() propagate to callers and we declare that the advice may throw ConcernCheckedException. Listing 8.13 shows the abstract ConcernAspect.

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constraint_name, 9 max(decode( position, 1, column_name, null )) cname1, 10 max(decode( position, 2, column_name, null )) cname2, 11 max(decode( position, 3, column_name, null )) cname3, 12 max(decode( position, 4, column_name, null )) cname4, 13 max(decode( position, 5, column_name, null )) cname5, 14 max(decode( position, 6, column_name, null )) cname6, 15 max(decode( position, 7, column_name, null )) cname7, 16 max(decode( position, 8, column_name, null )) cname8, 17 count(*) col_cnt 18 from (select substr(table_name,1,30) table_name, 19 substr(constraint_name,1,30) constraint_name, 20 substr(column_name,1,30) column_name, 21 position 22 from user_cons_columns ) a, 23 user_constraints b 24 where aconstraint_name = bconstraint_name 25 and bconstraint_type = 'R' 26 group by btable_name, bconstraint_name 27 ) cons 28 where col_cnt > ALL 29 ( select count(*) 30 from user_ind_columns i 31 where itable_name = constable_name 32 and icolumn_name in (cname1, cname2, cname3, cname4, 33 cname5, cname6, cname7, cname8 ).

In this analogy, the one-page summary you have been assigned is not a large task. You would either do it yourself or assign it to a single individual. Why Because the amount of work required to parallelize this process would exceed the work needed just to write the paper yourself. You would have to sit down, figure out that there should be 12 paragraphs, determine that each paragraph is not dependent on the other paragraphs, hold a team meeting, pick 12 individuals, explain to them the problem and assign them each a paragraph, act as the coordinator and collect all of their paragraphs, sequence them into the right order, verify they are correct, and then print the report. This is all likely to take longer than it would to just write the paper yourself, serially. The overhead of managing a large group of people on a project of this scale will far outweigh any gains to be had from having the 12 paragraphs written in parallel. The exact same principle applies to parallel execution in the database. If you have a job that takes seconds or less to complete serially, then the introduction of parallel execution and its associated managerial overhead will likely make the entire thing take longer.

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