Why do we recommend EXPLICIT LOCKING for PostgreSQL Tables in concurrent Transaction Processing Systems?

In PostgreSQL, if explicit locking is not enforced, duplicate records can be inserted when multiple concurrent transactions try to insert the same record simultaneously. This can occur when two or more transactions are executed concurrently and both attempt to insert the same record without proper locking mechanisms in place.

For example, consider the following scenario where two concurrent transactions are trying to insert the same record into a table:

— Transaction 1
BEGIN;
INSERT INTO my_table (id, name) VALUES (1, ‘John Doe’);
— Transaction 2
BEGIN;
INSERT INTO my_table (id, name) VALUES (1, ‘Jane Doe’);
— Commit both transactions
COMMIT;

In this example, both transactions are attempting to insert a record with the same ID value into the my_table table. If explicit locking is not enforced, both transactions may be executed concurrently and both may successfully insert the same record, resulting in a duplicate record.

To avoid this issue, it is recommended to use explicit locking mechanisms such as row-level locks, table-level locks, or advisory locks. For example, row-level locks can be used to prevent multiple transactions from inserting or updating the same record simultaneously. Here’s an example of how to use row-level locks to avoid duplicate records:

— Transaction 1
BEGIN;
LOCK TABLE my_table IN SHARE ROW EXCLUSIVE MODE;
INSERT INTO my_table (id, name) VALUES (1, ‘John Doe’);
— Transaction 2
BEGIN;
LOCK TABLE my_table IN SHARE ROW EXCLUSIVE MODE;
INSERT INTO my_table (id, name) VALUES (1, ‘Jane Doe’);
— Commit both transactions
COMMIT;

In this example, both transactions use the SHARE ROW EXCLUSIVE mode to lock the my_table table at the row level. This prevents both transactions from inserting the same record simultaneously, ensuring that only one transaction will be able to insert the record while the other transaction waits for the lock to be released.

Overall, it is recommended to use explicit locking mechanisms to avoid duplicate records in PostgreSQL. By using proper locking mechanisms, users can ensure that only one transaction can modify a record at a time, preventing the insertion of duplicate records.

About Shiv Iyer 443 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.