Database Administration for Beginners/

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Isolation Levels

Isolation Levels

Learn about transaction isolation, common concurrency issues, and how to manage isolation levels in MySQL.

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Imagine our OnlineStore is having a massive flash sale. Two enthusiastic customers, let’s call them Alex and Ben, are both eyeing the very last unit of the brand-new SuperFast Laptop. Alex adds it to his cart, and the system notes that one unit is available. Just moments later, before Alex can complete his checkout, Ben also sees the laptop, notes 1 in stock, and adds it to his cart. If our database isn’t careful about how it handles these simultaneous actions, both Alex and Ben might believe they’ve successfully purchased the laptop. This could lead to an oversold item, an unhappy customer (or two!), and a logistical headache for the store. This is precisely the kind of situation where understanding and correctly using transaction isolation levels becomes incredibly important. They are the rules of the road that ensure multiple users can access and modify data concurrently without tripping over each other or corrupting the data.

In this lesson, we’re going to dive into the world of transaction isolation. By the end of our journey, we’ll be able to:

  • Understand what transaction isolation is and why it’s a cornerstone for maintaining data integrity when many transactions are happening at once.

  • Identify and clearly explain common issues that can arise with concurrent transactions, such as dirty reads, non-repeatable reads, and phantom reads.

  • Describe the four standard ANSI SQL isolation levels: READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, and SERIALIZABLE.

  • Grasp how each of these isolation levels helps prevent (or allows) those concurrency issues.

  • Learn the practical steps to check and set transaction isolation levels in MySQL.

Let’s get started and unravel the secrets of keeping our database operations smooth and reliable!

What is transaction isolation?

When we have multiple transactions trying to read and write data in our database at the same time (which is very common in any busy application like our OnlineStore), things can get complicated. Transaction isolation is one of the key properties (the I in ACID) that determines how much a transaction is affected by other concurrently running transactions.

Think of it like this: if two people are editing the same document simultaneously, isolation rules decide whether one person sees the other’s changes as they type, only when they save, or perhaps not until they reopen the document.

Proper isolation is crucial for maintaining data consistency and integrity. Without it, one transaction might read incomplete or incorrect data written by another transaction that hasn’t finished yet (or might even be rolled back). This could lead to errors in reports, incorrect business decisions, or, like in our flash sale example, selling a product that’s no longer in stock. Isolation levels allow us to balance the need for data accuracy with the need for many users to access the system at the same time (concurrency). A higher isolation level provides more data accuracy but can reduce concurrency, while a lower level allows more concurrency but with a higher risk of data anomalies.

Essentially, isolation levels define the degree to which one transaction must be shielded from the data modifications made by other transactions. MySQL, like other relational database systems, provides several isolation levels that we can choose from based on the specific needs of our applications.

Concurrency phenomena

When multiple transactions run concurrently without perfect isolation, several undesirable phenomena can occur. Understanding these is key to appreciating why different isolation levels exist.

Dirty read

A dirty read means a transaction reads data that has been modified by another transaction but not yet committed. If the modifying transaction then rolls back its changes, the first transaction has read data that technically never existed in the database, which can lead to incorrect calculations or decisions.

Transaction T1 modifies a data item. Another transaction, T2, reads that modified data item before T1 commits. If T1 then performs a ROLLBACK, T2 has read dirty data.

Sample scenario: Incorrect stock check

Imagine in our OnlineStore, a new shipment of Wireless Earbuds (ProductID 3) arrives, and an employee starts a transaction to update the stock.

  • Connection 1 (employee updating stock):

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-- Let's assume ProductID 3 (Wireless Earbuds) initially has 100 stock.
START TRANSACTION;
UPDATE Products SET Stock = Stock + 50 WHERE ProductID = 3;
-- Stock is now 150 in this transaction, but not yet committed.
-- Now, imagine the employee gets distracted before committing.

  • Connection 2 (reporting system, operating at a very low isolation level):

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-- This transaction reads the stock level.
-- If allowed to perform a DIRTY READ:
SELECT ProductName, Stock FROM Products WHERE ProductID = 3;
-- It might see Stock = 150.

  • Connection 1 (employee realizes a mistake or system error):

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ROLLBACK; -- The stock update is undone. Stock for ProductID 3 reverts to 100.

  • If Connection 2 read the stock as 150 (a dirty read) and made business decisions based on that, those decisions would be flawed because the actual committed stock remained 100.

Non-repeatable read

A non-repeatable read occurs when a transaction reads the same row multiple times and gets different data values each time because another transaction has modified that row and committed the changes in between the reads. ...