When multiple users try to access and modify the same data in a database at the same time, it can lead to concurrency issues. These issues can range from temporary data inconsistencies to permanent data corruption. In this blog post, we’ll explore the different types of concurrency issues that can occur in SQL databases, and we’ll discuss some strategies for controlling simultaneous access to data and ensuring data integrity.
Lost Updates
Lost updates occur when two or more transactions attempt to update the same row of data at the same time. If one of the transactions commits before the other, the changes made by the second transaction will be lost.
For example, consider the following scenario:
- Two users, Alice and Bob, are both trying to update the same customer record.
- Alice opens the record and sees that the customer’s balance is $100.
- Bob also opens the record and sees that the customer’s balance is $100.
- Alice withdraws $50 from the account and saves the record.
- Bob deposits $50 into the account and saves the record.
If Alice’s transaction commits before Bob’s, then Bob’s deposit will be lost. The customer’s balance will be $100 instead of $150.
Dirty Reads
A dirty read occurs when a transaction reads data that has been modified by another transaction that has not yet committed. This can lead to the transaction reading incorrect or inconsistent data.
For example, consider the following scenario:
- Two users, Alice and Bob, are both trying to update the same customer record.
- Alice opens the record and sees that the customer’s balance is $100.
- Bob also opens the record and sees that the customer’s balance is $100.
- Alice withdraws $50 from the account and saves the record.
- Bob reads the record and sees that the customer’s balance is $50.
Bob’s read is a dirty read because he is reading data that has been modified by Alice’s transaction, which has not yet committed. If Bob’s transaction then commits, his changes will overwrite Alice’s changes, and the customer’s balance will be $50 instead of $100.
Non-Repeatable Reads
A non-repeatable read occurs when a transaction reads the same row of data twice and gets different results because another transaction has modified the data in between the two reads.
For example, consider the following scenario:
- A user, Alice, is trying to transfer money from one account to another.
- Alice reads the balance of the first account and sees that it is $100.
- Alice reads the balance of the second account and sees that it is $50.
- Alice transfers $50 from the first account to the second account.
- Alice reads the balance of the first account again and sees that it is now $50.
Alice’s second read of the first account is a non-repeatable read because she got a different result than she did the first time she read the data. This is because Bob’s transaction, which transferred $50 from the first account to the second account, committed in between Alice’s two reads.
Phantom Reads
A phantom read occurs when a transaction reads data that was inserted or deleted by another transaction that has not yet committed. This can lead to the transaction seeing more or fewer rows of data than it should.
For example, consider the following scenario:
- Two users, Alice and Bob, are both trying to add new customers to the database.
- Alice opens the customer table and sees that there are 100 rows of data.
- Bob also opens the customer table and sees that there are 100 rows of data.
- Alice adds a new customer to the table and saves the record.
- Bob reads the customer table and sees that there are 101 rows of data.
Bob’s read is a phantom read because he saw a row of data that was inserted by Alice’s transaction, which has not yet committed. If Bob’s transaction then commits, his new customer record will be added to the table, and there will be 102 rows of data instead of 101.
Strategies for Controlling Simultaneous Access to Data
There are a number of strategies that can be used to control simultaneous access to data and ensure data integrity. These strategies include:
- Locking: Locking prevents other transactions from accessing data that is being modified by a transaction. There are two main types of locks: exclusive locks and shared locks. An exclusive lock prevents other transactions from reading or writing the data, while a shared lock allows other transactions to read the data but not write to it.
- Transactions: Transactions group a series of operations into a single unit of work. All of the operations in a transaction are either committed or rolled back atomically, which means that either all of the operations are completed successfully or none of them are.
- Isolation levels: Isolation levels control the degree to which transactions can see the changes made by other transactions. There are four main isolation levels: read uncommitted, read committed, repeatable read, and serializable.
- MVCC (Multi-Version Concurrency Control): MVCC is a concurrency control mechanism that allows multiple transactions to read and write data concurrently without causing conflicts. MVCC works by maintaining multiple versions of each row of data.
Conclusion
Concurrency issues can be a major problem in SQL databases, but they can be controlled using a variety of strategies. By understanding the different types of concurrency issues and the strategies for controlling them, you can help to ensure that your database data is always accurate and consistent.
FAQ
Q: What is the difference between a lock and a transaction?
A: A lock prevents other transactions from accessing data that is being modified by a transaction. A transaction groups a series of operations into a single unit of work. All of the operations in a transaction are either committed or rolled back atomically, which means that either all of the operations are completed successfully or none of them are.
Q: What is the difference between an exclusive lock and a shared lock?
A: An exclusive lock prevents other transactions from reading or writing the data, while a shared lock allows other transactions to read the data but not write to it.
Q: What is the difference between the four isolation levels?
A: The four isolation levels are:
- Read uncommitted: This isolation level allows transactions to see changes made by other transactions that have not yet committed.
- Read committed: This isolation level prevents transactions from seeing changes made by other transactions that have not yet committed.
- Repeatable read: This isolation level prevents transactions from seeing changes made by other transactions that have not yet committed, and it also prevents transactions from seeing changes made by other transactions that have already committed but have not yet been rolled back.
- Serializable: This isolation level prevents transactions from seeing any changes made by other transactions until those transactions have committed.
Q: What is MVCC?
A: MVCC (Multi-Version Concurrency Control) is a concurrency control mechanism that allows multiple transactions to read and write data concurrently without causing conflicts. MVCC works by maintaining multiple versions of each row of data.
