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This article investigates whether the REPEATABLE‑READ isolation level in InnoDB fully prevents phantom reads by conducting a series of current‑read and snapshot‑read experiments, analyzing transaction behavior, MVCC mechanisms, and offering recommendations to avoid phantom anomalies.
This article examines whether the REPEATABLE‑READ isolation level in InnoDB fully prevents phantom reads by conducting systematic current‑read and snapshot‑read experiments, analyzing lock mechanisms, MVCC behavior, and presenting detailed SQL scripts, results, and recommendations for avoiding phantom reads.
This article explains MySQL's four transaction isolation levels—READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, and SERIALIZABLE—detailing their definitions, associated phenomena such as dirty reads, non‑repeatable reads, and phantom reads, and demonstrates how to query and set isolation levels with practical SQL examples.
This article explains MySQL's four transaction isolation levels, illustrating how concurrent transactions can cause dirty reads, non‑repeatable reads, and phantom reads through detailed examples of two transactions interacting via SELECT, UPDATE, and INSERT operations, and summarizes the consistency issues each scenario creates.
This article explains the concept of phantom reads, distinguishes them from non‑repeatable reads, critiques the ANSI SQL isolation‑level definitions, and shows how MySQL implements repeatable‑read using locks and MVCC to prevent both strict and loosely defined phantom anomalies.
This article explains the four transaction isolation levels, defines phantom reads, and details how MySQL's InnoDB engine uses MVCC snapshot reads and next‑key locking (including the next‑key principle and lock composition) to prevent phantom reads under the REPEATABLE READ isolation level.
This article explains MySQL’s transaction isolation levels, clarifies the differences between dirty reads, non‑repeatable reads and phantom reads, and demonstrates through experiments why the REPEATABLE READ level can prevent phantom reads, while also discussing its limitations, MVCC, and locking mechanisms.
This article examines why concurrent upsert operations in a high‑throughput MySQL service can cause deadlocks due to GAP locks and phantom reads, explains the underlying InnoDB locking mechanisms, and offers practical solutions such as adjusting isolation levels or redesigning data sharding logic.