What is phantom read?

A phantom read is a phenomenon that occurs in database transactions when, within a single transaction, two identical read queries are executed, but the second query returns a different set of rows (either more or fewer rows) due to concurrent insertions or deletions made by another committed transaction.

Understanding Phantom Read

A phantom read is a specific type of anomaly related to transaction isolation levels. It differs from a non-repeatable read, where the *values* of existing rows change, and from a dirty read, where uncommitted data from another transaction is read. A phantom read specifically refers to changes in the *number* of rows returned by a query when the same query is executed multiple times within the same transaction.

This anomaly arises when one transaction (T1) queries a range of rows, and then another transaction (T2) inserts or deletes rows within that range, and commits its changes. If T1 then re-executes its original query, it will find a different set of rows (a 'phantom' row appearing or disappearing), even if T1 is operating at an isolation level like REPEATABLE READ which is designed to prevent non-repeatable reads.

Example of a Phantom Read

Consider a scenario with a products table. Transaction 1 (T1) wants to count all products with a price greater than $100. While T1 is still active, Transaction 2 (T2) inserts a new product that also meets this criteria and commits its changes. When T1 re-runs the same count query, it finds an additional row, a 'phantom' row.

CREATE TABLE products (
    id INT PRIMARY KEY,
    name VARCHAR(100),
    price DECIMAL(10, 2)
);

INSERT INTO products (id, name, price) VALUES (1, 'Laptop', 1200.00);
INSERT INTO products (id, name, price) VALUES (2, 'Mouse', 25.00);

-- Transaction 1 (T1) starts
SET TRANSACTION ISOLATION LEVEL REPEATABLE READ; -- Or READ COMMITTED
START TRANSACTION;

-- T1 reads the count of expensive products
SELECT COUNT(*) FROM products WHERE price > 1000;
-- Expected result: 1 (only 'Laptop')

-- Transaction 2 (T2) starts concurrently
START TRANSACTION;

-- T2 inserts a new product that matches T1's criteria
INSERT INTO products (id, name, price) VALUES (3, 'Monitor', 1500.00);

-- T2 commits its changes
COMMIT;

-- T1 reads the count of expensive products again
SELECT COUNT(*) FROM products WHERE price > 1000;
-- Expected result: 2 (now includes 'Monitor')
-- This is a phantom read: the number of rows changed for the same query within T1.

-- T1 commits
COMMIT;

Transaction Isolation Levels and Phantom Reads

Phantom reads can occur at READ COMMITTED and REPEATABLE READ isolation levels. Although REPEATABLE READ prevents non-repeatable reads (where the data in *existing* rows changes), it typically does not prevent phantom reads because it usually only locks individual rows that have been read, not the 'gaps' or ranges where new rows could be inserted or existing rows deleted.

The highest isolation level, SERIALIZABLE, is designed to prevent phantom reads. It achieves this by using techniques like range locks (or 'predicate locks'), which lock not just the individual rows but also the potential space where new rows matching the query criteria could be inserted or deleted, thereby ensuring that no other transaction can modify the data set relevant to the serializable transaction's queries.

Preventing Phantom Reads

• Use SERIALIZABLE Isolation Level: This is the most straightforward way to prevent phantom reads. However, it can significantly reduce concurrency and impact performance due to extensive locking.
• Application-Level Logic: In some cases, if lower isolation levels are used for performance, the application might need to implement logic to detect or handle phantom reads, though this is often complex and error-prone.
• Explicit Locking (Database-specific): Some databases offer explicit locking mechanisms, such as SELECT ... FOR UPDATE or SELECT ... FOR SHARE, which can be used to lock selected rows and sometimes ranges, but their behavior regarding phantom reads can vary depending on the database system and specific implementation.