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For the first part of this discussion, we ll assume that constraints are in IMMEDIATE mode, which is the norm. In this case, the integrity constraints are checked immediately after the entire SQL statement has been processed. Note that I used the term SQL statement, not just statement. If I have many SQL statements in a PL/SQL stored procedure, each SQL statement will have its integrity constraints validated immediately after its individual execution, not after the stored procedure completes. So, why are constraints validated after the SQL statement executes Why not during This is because it is very natural for a single statement to make individual rows in a table momentarily inconsistent. Taking a look at the partial work by a statement would result in Oracle rejecting the results, even if the end result would be OK. For example, suppose we have a table like this: ops$tkyte%ORA11GR2> create table t ( x int unique ); Table created. ops$tkyte%ORA11GR2> insert into t values ( 1 ); 1 row created. ops$tkyte%ORA11GR2> insert into t values ( 2 ); 1 row created. ops$tkyte%ORA11GR2> commit; Commit complete. And we want to execute a multiple-row UPDATE: ops$tkyte%ORA11GR2> update t set x=x-1; 2 rows updated. If Oracle checked the constraint after each row was updated, on any given day we would stand a 5050 chance of having the UPDATE fail. The rows in T are accessed in some order, and if Oracle updated the X=1 row first, we would momentarily have a duplicate value for X and it would reject the UPDATE. Since Oracle waits patiently until the end of the statement, the statement succeeds because by the time it is done, there are no duplicates.

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Starting with Oracle 8.0, we also have the ability to defer constraint checking, which can be quite advantageous for various operations. The one that immediately jumps to mind is the requirement to cascade an UPDATE of a primary key to the child keys. Many people claim you should never need to do this that primary keys are immutable (I am one of those people), but many others persist in their desire to have a cascading UPDATE. Deferrable constraints make this possible.

Storing data in various files, reading them into memory, and querying and manipulating the resulting in-memory data collection is a sufficient approach for many applications working with data, but there comes a point where a more persistent data handling is required For example, consider a business that has two applications that need to access the same set of data about employees One way to do this is to store data in a text file and work with this data file from both applications But this approach is quite vulnerable; you would quickly realize how redundant text files can get when adding new pieces of data (say you wanted to add an address next to the name, department, and age of each employee) or if you wanted to group your employee data by introducing various relationships (say, multiple addresses per employee).

Note It is considered an extremely bad practice to perform update cascades to modify a primary key. It violates

the intent of the primary key. If you have to do it once to correct bad information, that s one thing, but if you find you are constantly doing it as part of your application, you will want to go back and rethink that process you have chosen the wrong attributes to be the key!

Even if you did manage to find a good storage alternative, you would still have to modify both applications to read and write this new data format Databases make scenarios like these much easier to cope with by enforcing centralized control of persistent data (data that is more persistent than what appears in a single application) and by giving you the freedom to define, manipulate, and query this data in an application-neutral way Databases give you many benefits; some of the more important ones are listed here: Data security: Having a centralized control of data, it becomes possible to erect a full security system around your data, giving specific access rules for each type of access or parts of the database.