Ensuring Data Consistency: Non-Repeatable Reads and Phantom Reads in Oracle

Non-Repeatable Read:

1. Transaction A (yours) reads a piece of data.
2. Transaction B (another user) updates the same data. (This update gets committed)
3. Transaction A reads the same data again. This time, you'll see the updated value from transaction B, even though your transaction started before B's update. It's like reading something twice and getting different results because someone else changed it in between.

Phantom Read:

1. Transaction A (yours) reads data based on a specific criteria (e.g., all customers with a balance over $100).
2. Transaction B (another user) inserts new data that meets your criteria (e.g., a new customer with a balance of $120). (This insert gets committed)
3. Transaction A reads the data again using the same criteria. This time, you'll see the new data inserted by transaction B, even though it didn't exist when your transaction began. It's like seeing "phantom" data appear that wasn't there before.

Key Difference:

• Non-repeatable read: You see a change to the same data you already read.
• Phantom read: You see entirely new data that wasn't there before, based on your criteria.

Oracle Transaction Isolation Levels:

Oracle offers different transaction isolation levels that determine how transactions see each other's changes. The default level (READ COMMITTED) allows non-repeatable reads but not phantom reads. Higher isolation levels can prevent these issues but can also impact performance.

Avoiding these Issues:

• Increase isolation level: This can limit concurrency but ensures consistency.
• Use locking mechanisms: Explicitly lock data rows to prevent others from modifying them while your transaction is ongoing.
• Be aware of potential inconsistencies when working with concurrent transactions.

-- Transaction A (Your Session)
START TRANSACTION;

SELECT account_number, balance FROM accounts WHERE account_number = 123;

-- Assume balance is 100 initially

-- Transaction B (Another User) makes a withdrawal (committed)
UPDATE accounts SET balance = balance - 20 WHERE account_number = 123;
COMMIT;

-- Transaction A continues (reads again)
SELECT account_number, balance FROM accounts WHERE account_number = 123;

-- You might see balance as 80 now, even though your transaction started before the withdrawal
COMMIT;

-- Transaction A (Your Session)
START TRANSACTION;

SELECT customer_id, name FROM customers WHERE balance > 100;

-- Assume there are no customers with balance over 100 initially

-- Transaction B (Another User) adds a new high-balance customer (committed)
INSERT INTO customers (customer_id, name, balance) VALUES (456, 'New Customer', 120);
COMMIT;

-- Transaction A continues (reads again with the same criteria)
SELECT customer_id, name FROM customers WHERE balance > 100;

-- You might see the new customer record here, even though they weren't there before your transaction began
COMMIT;

Note:

• These are simplified examples. Real code would involve connecting to the database and using Oracle's specific SQL syntax.
• You cannot directly set isolation levels in Oracle with SQL statements, but you can achieve similar effects with techniques like SELECT ... FOR UPDATE for locking.

1. READ ONLY Transactions:

   • This isn't a true isolation level but acts like one.
   • You can set the transaction to READ ONLY mode, preventing any modifications within your transaction.
   • This ensures a consistent view of data but limits functionality.

   START TRANSACTION READ ONLY;
   
   -- Your read queries here
   
   COMMIT;  -- Technically a noop in READ ONLY mode
   

2. Locking Mechanisms:

   • Oracle offers explicit locking mechanisms to control access to data rows.
   • You can acquire locks before reading data, preventing other transactions from modifying it until your transaction releases the lock.
   • This provides strong consistency but can lead to performance overhead and potential deadlocks.

   -- Acquire a lock before reading
   SELECT * FROM accounts WHERE account_number = 123 FOR UPDATE; 
   
   -- Your read queries here (data is locked for others)
   
   COMMIT;  -- Releases the lock
   

3. Optimistic Locking:

   • This approach leverages a version column in your table.
   • When reading data, you also read the version number.
   • During updates, you include a WHERE clause with the old version number.
   • The update succeeds only if the version hasn't changed (meaning no other transaction modified it).
   • This allows for some concurrency but requires additional logic in your application.

   -- Read data with version
   SELECT * FROM accounts WHERE account_number = 123, version;
   
   -- Update with WHERE clause checking version
   UPDATE accounts SET balance = balance + 10 WHERE account_number = 123 AND version = <old_version>;
   

4. Application-Level Logic:

   • You can handle inconsistencies within your application code.
   • After a read operation, perform a quick validation check before using the data.
   • This requires careful design and might not be suitable for all scenarios.

Choosing the right approach depends on factors like:

• Required level of consistency
• Acceptable performance impact
• Complexity you're willing to manage in your application