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In Figure 8-3, a user connects as SUE (password, SUE not an example of good security) and queries the EMPLOYEES table The statement fails because of a simple syntax error, correctly identified by SQL*Plus Note that SQL*Plus never attempts to correct such mistakes, even when it knows exactly what you meant to type Some third-party tools may be more helpful, offering automatic error correction The second attempt to run the statement fails with an error stating that the object does not exist This is because it does not exist in the current user s schema; it exists in the HR schema Having corrected that, the third run of the statement succeeds but only just The value passed in the WHERE clause is a string, 21-APR-2000 , but the column HIRE_DATE is not defined in the table as a string, it is defined as a date To execute the statement, the database had to work out what the user really meant and cast the string as a date In the last example, the typecasting fails This is because the string passed is formatted as a European-style date, but the database has been set up as American: the attempt to match 21 to a month fails The statement would have succeeded if the string had been 04/21/2007 If a statement is syntactically correct and has no errors with the objects to which it refers, it can still fail because of access permissions If the user attempting to execute the statement does not have the relevant permissions on the tables to which it refers, the database will return an error identical to that which would be returned if the object did not exist As far as the user is concerned, it does not exist Errors caused by access permissions are a case where SELECT and DML statements may return different results: it is possible for a user to have permission to see the rows in a table, but not to insert, update, or delete them Such an arrangement is not uncommon; it often makes business sense Perhaps more confusingly, permissions can be set up in such a manner that it is possible to insert rows that you are not allowed to see And, perhaps worst of all, it is possible to delete rows that you can neither see nor update However, such arrangements are not common A constraint violation can cause a DML statement to fail For example, an INSERT command can insert several rows into a table, and for every row the database will check whether a row already exists with the same primary key This occurs as each row is inserted It could be that the first few rows (or the first few million rows) go in without a problem, and then the statement hits a row with a duplicate value At this point it will return an error, and the statement will fail This failure will trigger a reversal of all the insertions that had already succeeded This is part of the SQL standard: a statement must succeed in total, or not at all The reversal of the work is a rollback The mechanisms of a rollback are described in the next section of this chapter, titled Control Transactions If a statement fails because of space problems, the effect is similar A part of the statement may have succeeded before the database ran out of space The part that did succeed will be automatically rolled back Rollback of a statement is a serious matter It forces the database to do a lot of extra work and will usually take at least as long as the statement has taken already (sometimes much longer).

The concepts behind a transaction are a part of the relational database paradigm A transaction consists of one or more DML statements, followed by either a ROLLBACK or a COMMIT command It is possible to use the SAVEPOINT command to give a degree of control within the transaction Before going into the syntax, it is necessary to review the concept of a transaction A related topic is read consistency; this is automatically implemented by the Oracle server, but to a certain extent programmers can manage it by the way they use the SELECT statement

Oracle s mechanism for assuring transactional integrity is the combination of undo segments and redo log files: this mechanism is undoubtedly the best of any database yet developed and conforms perfectly with the international standards for data processing Other database vendors comply with the same standards with their own mechanisms, but with varying levels of effectiveness In brief, any relational database must be able to pass the ACID test: it must guarantee atomicity, consistency, isolation, and durability

Figure 2-7