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For simple transactions that expose a low risk of data corruption, a lower isolation can speed things up without any significant increase in risk; on the other hand, a high isolation level is necessary for mission-critical applications (like banking) even at the cost of some degradation in performance.
In order to understand the various isolation levels, it is necessary to first understand some of the problems that a low isolation level can cause.
Let’s assume we have two separate transactions, started by two different clients, A and B.
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.
Thus far, I’ve been explaining transactions under the assumption that the database is being accessed by a single user at a time.
This was done for purposes of simplicity in explanation; however, in the real world, such an assumption is unlikely to hold true.
READ COMMITTED: Offering more security than the READ UNCOMMITTED level, this level does not allow a transaction to see the uncommitted data of other transactions; however, it still allows unrepeatable and phantom reads.
REPEATABLE READ: The default isolation level in My SQL, this level eliminates dirty reads and unrepeatable reads.
The higher the isolation level, the more work My SQL has to do to keep users from seeing each other’s modifications and the slower things run.It occurs when a transaction sees a new row while it is in progress.Typically, this occurs due to new records INSERTed and committed by other transactions.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.