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What is Phantom Read?
Phantom Read, in the context of databases, refers to a phenomenon where a transaction in a database system retrieves a set of records based on a certain condition, but then, when the same transaction is performed again, it retrieves a different set of records, even though no records were inserted, updated, or deleted in the meantime. This unexpected change in the results is known as a phantom read.
Understanding Phantom Read
To better understand phantom reads, let’s take an example. Suppose we have a database with a table called “Students” that stores information about students in a particular school. We have a transaction that retrieves all students whose age is greater than 18.
Now, consider the following scenario:
1. Transaction A starts and retrieves all students who are over 18. Let’s say it retrieves three records.
2. While Transaction A is still in progress, Transaction B performs an insert operation and adds a new record to the “Students” table. This new record represents a student who just turned 18.
3. Transaction A continues and retrieves the remaining students who are over 18. However, since a new record has been inserted, it retrieves four records this time.
This unexpected change in the results, where the number of records retrieved by Transaction A changed between two identical queries, is the essence of a phantom read.
Causes of Phantom Read
Phantom reads occur due to the way database systems handle concurrent transactions. When transactions are executed concurrently, they can interfere with each other, leading to phenomena like phantom reads.
In the example above, Transaction A initially retrieves a set of records based on a certain condition. However, while this transaction is in progress, Transaction B performs an insert operation, modifying the set of records that Transaction A is supposed to retrieve. As a result, when Transaction A queries the database again, it encounters the new record inserted by Transaction B, leading to a phantom read.
Preventing Phantom Read
Database systems employ various techniques to prevent phantom reads and ensure the consistency of the data. One common approach is to use locking mechanisms or isolation levels.
Locking mechanisms allow transactions to acquire locks on database objects, preventing other transactions from modifying the data until the locks are released. Isolation levels, on the other hand, define the visibility rules for transactions. By using a stricter isolation level, such as serializable, databases can avoid phenomena like phantom reads.
However, it’s important to consider the trade-offs between data consistency and performance. Stricter isolation levels impose a higher level of locking and concurrency control, which can degrade performance in highly concurrent systems. Database administrators need to carefully choose the appropriate isolation level based on the requirements of the application.
Conclusion
In summary, phantom reads are phenomena that occur in databases when a transaction retrieves a set of records based on certain conditions, and then, when the same transaction is repeated, retrieves a different set of records due to concurrent modifications. Understanding and addressing phantom reads is crucial for maintaining data consistency and ensuring reliable results in database systems. By employing suitable locking mechanisms and isolation levels, database administrators can mitigate the chances of phantom reads occurring in their systems.
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