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What is a Phantom Read Anomaly?

Introduction

A phantom read is a scenario that occurs in a database when a transaction re-executes a query and finds that another committed transaction has added or removed rows that weren’t there previously. This anomaly can lead to inconsistencies in the data.

Consider the following example:

  1. Transaction 1 (T1) reads all rows in a table that satisfy some condition, let’s say SELECT * FROM accounts WHERE balance > 5000, and gets 100 rows as a result.
  2. Then Transaction 2 (T2) inserts a new row into the accounts table where the balance is 7000 and commits.
  3. Transaction 1 (T1) re-executes the same query, SELECT * FROM accounts WHERE balance > 5000, but this time it gets 101 rows instead of the initial 100 rows.

The extra row read by T1 during the second execution is known as a phantom read.

Avoiding a Phantom Read

There are several ways to handle phantom reads:

1. Serializable Isolation Level: In most databases, you can set the transaction isolation level to ‘SERIALIZABLE’. This is the highest level of isolation and guarantees safety from all concurrency issues, including phantom reads. But it comes at the cost of reduced concurrency.

2. Use a ‘SELECT FOR UPDATE’ Statement: In some cases, you can use a ‘SELECT FOR UPDATE’ statement. This locks the selected rows from being updated or selected by other transactions until the current transaction is complete. However, this won’t prevent new rows from being inserted, so it doesn’t completely solve the phantom read problem.

3. Locking the Table: Another way is to explicitly lock the entire table. This could prevent any other transaction from making changes while the first transaction is ongoing. However, this significantly reduces concurrency and could lead to performance issues.

4. Using Optimistic Locking: Optimistic locking is a strategy where records are versioned. Any transaction that attempts to modify a record must provide the version that it expects the record to have. If the actual record’s version does not match the expected version, the transaction fails.

It’s important to note that different databases may provide different mechanisms and syntax for handling concurrency issues like phantom reads. The developer should be aware of these features and decide the right strategy based on the specific requirements of the application.