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Nonrepeatable Reads The next phenomenon that can occur when concurrent transactions are initiated is the nonrepeatable read. The nonrepeatable read can occur when one transaction reads data from a table, another transaction then updates that data, and the first transaction rereads the data, only to discover that the data has changed. As a result, the first read is not repeatable. Let s take a look at Figure 16-3 to better understand this concept. When Transaction 1 is initiated, it reads the data in the table. At that point, the transaction might be involved in other processes or is waiting for a response from a user. For example, the user might receive a call from a manager who is trying to find out how many copies of a particular CD are in stock. The user checks for that information. The manager then puts the user on hold for a short time, so the user must wait to complete the transaction. During that time, Transaction 2 is initiated and it updates the table. After the update, Transaction 1 again reads the data (the manager returns to the phone) and finds different information from the first read, resulting in a nonrepeatable read. Phantom Reads The last phenomenon that we ll look at is the phantom read. Although similar to the nonrepeatable read, the phantom read has some subtle differences, which are factors when trying to determine an isolation level. A phantom read can occur when a transaction reads a table based on some sort of search condition, then a second transaction updates the data in the table, and then the first transaction attempts to reread the data, only this time different rows are returned because of how the search condition is defined. To clarify this, let s take a look at Figure 16-4.

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16:

Several third-party vendors offer backup services. Many of these operate over the Internet or a WAN connection. There are several benefits to this type of service. First, all backups are performed from a remote location. This fact alone means that your data is protected offsite. Second, the costs associated with implementing and managing your backups is offloaded to a company that specializes in such services. Finally, the hardware, software, and storage requirement costs are offloaded to another organization.

CD_NAME Transaction 1 reads values different from first read Famous Blue Raincoat Court and Spark Past Light

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A transaction is a discrete series of actions that must be either completely processed or not processed at all. Some call a transaction a unit of work as a way of further emphasizing its all-or-nothing nature. Transactions have properties that can be easily remembered using the acronym ACID (Atomicity, Consistency, Isolation, Durability): Atomicity A transaction must remain whole. That is, it must completely succeed or completely fail. When it succeeds, all changes that were made by the transaction must be preserved by the system. Should a transaction fail, all changes that were made by it must be completely undone. In database systems, we use the term rollback for the process that backs out any changes made by a failed transaction, and we use the term commit for the process that makes transaction changes permanent. Consistency A transaction should transform the database from one consistent state to another. For example, a transaction that creates an invoice for an order transforms the order from a shipped order to an invoiced order, including all the appropriate database changes. Isolation Each transaction should carry out its work independent of any other transaction that might occur at the same time. Durability Changes made by completed transactions should remain permanent, even after a subsequent shutdown or failure of the database or other critical system component. In object terminology, the term persistence is used for permanently stored data. The concept of permanent here can be confusing, because nothing seems to ever stand still for long in an OLTP (online transaction processing) database. Just keep in mind that permanent means the change will not disappear when the database is shut down or fails it does not mean that the data is in a permanent state that can never be changed again.

Figure 16-3

Figure 2-3.

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