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Phantom reads are still theoretically possible, but in reality are almost impossible to reproduce.

SERIALIZABLE: SERIALIZABLE eliminates phantom reads as well to offer the most secure isolation between transactions; it’s also the slowest.

Client A is adding a new account to a table containing bank account balances, while client B is executing a query to obtain the sum of all account balances.

A begins a transaction; while it is in progress, B attempts to view the changes being made by it before it has been committed.

What you’ve just seen is an example of the isolation property in action.

Therefore, in this concluding segment, I’ll be exploring the My SQL transactional model in a multi-user scenario, illustrating some of the data corruption problems that raise their ugly heads in this environment and showing you how you can use My SQL’s isolation levels to reduce their likelihood. While a transaction is in progress, open up a new client session and see if the changes made by the transaction are visible.

I’ll also show you how to leverage off the transaction model to build more robust SQL applications, with a sample Perl/DBI application, and – in case you’re still stuck using an older version of My SQL – illustrate how you can simulate transactions with non-transactional My ISAM tables. Consider the following example, which illustrates by using two clients, A and B.

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