3 posts
This article follows the process of solving the concurrency problems in a like feature with database locks. It explains how pessimistic locking works and examines the performance degradation caused by next-key locks.
Suppose we are designing a first-come, first-served event system. The requirements are listed below. If 1,000 people request 100 available items at the same time, how can we ensure that exactly 100 people receive one? The solutions commonly proposed in this situation are listed below.
In Spring, @Transactional(readOnly = true) is commonly said to optimize performance by changing dirty checking to Manual mode. In practice, however, unnecessary JDBC calls can actually make it slower. Based on real call traces from Elastic APM, this post analyzes how read-only transactions affect performance and suggests a more practical alternative.