自动化 Hermitage 以查看 MySQL 和 MariaDB 中的事务差异
Automating Hermitage to see how transactions differ in MySQL and MariaDB

原始链接: https://theconsensus.dev/p/2026/05/02/automating-hermitage.html

本文探讨了SQL标准中事务隔离级别(如“未提交读”、“已提交读”等)定义的模糊性,以及数据库实际实现这些隔离级别的方式。虽然标准*允许*诸如“脏写”(覆盖未提交的数据)之类的行为,但大多数数据库会阻止它们。 核心问题通过一个“保龄球鞋”思想实验来演示,并针对名为Monastery的新开源工具进行了测试。该实验涉及并发事务尝试更新数据库中一双鞋的拥有者。目标是识别不一致性——“脏读”,即事务看到来自其他事务的未提交更改。 文章强调,即使在看似强大的隔离级别下,由于标准的灵活性,也可能出现意外行为。它强调了理解特定数据库如何处理并发的重要性,以及进行可靠测试以确保数据完整性的必要性。最终,文章提倡对事务隔离进行更深入的研究,超越理论定义。

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原文

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Transaction isolation levels (e.g. Read Uncommitted, Read Committed, Repeatable Read, Serializable) in the official SQL standard are defined in terms of transaction anomalies like Read Skew, Lost Updates, etc. But the SQL standard itself is ambiguous (yes, even the latest 2023 version) and allows some silly behavior.

Let's motivate this entire article by looking at the Dirty Writes. If a transaction can overwrite the writes of another concurrent (uncommitted) transaction, we might have Dirty Writes. If a transaction can see the writes of another concurrent (uncommitted) transaction, we might have Dirty Reads. No major database allows Dirty Writes, even though the SQL specification allows it. But Dirty Reads are allowed by databases with Read Uncommitted isolation levels (PostgreSQL doesn't have such a level).

Lorin Hochstein has a thought experiment for Dirty Writes. Roughly put, in a bowling alley, no one should be able to acquire a half a pair of shoes within concurrent transactions. We'll adapt this thought experiment to a format we’ll be able to execute on multiple databases at multiple isolation levels with a new open-source tool, Monastery.

DROP TABLE IF EXISTS shoes;
CREATE TABLE shoes (left_shoe TEXT, right_shoe TEXT, shoe_id INT PRIMARY KEY);
INSERT INTO shoes VALUES ('', '', 1);

---

t1: BEGIN;
t2: BEGIN;
t1: UPDATE shoes SET left_shoe = 'Lin' WHERE shoe_id = 1;
t2: UPDATE shoes SET left_shoe = 'Carlos' WHERE shoe_id = 1;
t2: UPDATE shoes SET right_shoe = 'Carlos' WHERE shoe_id = 1;
t1: UPDATE shoes SET right_shoe = 'Lin' WHERE shoe_id = 1;
t1: SELECT * FROM shoes; -- # Inconsistent results here would mean dirty reads not necessarily dirty writes.
t2: SELECT * FROM shoes; -- # Inconsistent results here would mean dirty reads not necessarily dirty writes.
t1: COMMIT;
t2: COMMIT;
t1: SELECT * FROM shoes; -- assert ({Lin, Lin, 1}) or ({Carlos, Carlos, 1})
t2: SELECT * FROM shoes; -- assert ({Lin, Lin, 1}) or ({Carlos, Carlos, 1})

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About the author

Phil is the founder of The Consensus. Before this, he contributed to Postgres products at EnterpriseDB, cofounded and led marketing at TigerBeetle, and was an engineering manager at Oracle. He runs the Software Internals Discord, the Software Internals Email Book Club, and co-runs NYC Systems. @eatonphil

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