扩展Nextdoor的数据库：第4部分

In this part of the Scaling Nextdoor’s Datastores blog series, we will see how the Core-Services team at Nextdoor keeps its cache consistent with database updates and avoids stale writes to the cache.

在 Scaling Nextdoor 的 Datastores 博客系列的这一部分中，我们将看到 Nextdoor 的核心服务团队如何保持其缓存与数据库更新的一致性，并避免对缓存的过时写入。

In this post, we’ll focus specifically on inconsistencies caused by racing writes and our solution. We’ll discuss other causes and our full solution for consistent caching in the next installment of our blog: Part 5: A time-bounded eventually-consistent cache.

在这篇文章中，我们将特别关注由竞争写入引起的不一致性及我们的解决方案。我们将在下一期博客中讨论其他原因及我们一致缓存的完整解决方案：第5部分：一个时间限制的最终一致缓存。

Inconsistent Cache

不一致的缓存

Caches can become inconsistent with the database for several reasons, such as:

缓存可能因多种原因与数据库不一致，例如：

• Racing Writes / Concurrent Updates: Multiple writes occurring simultaneously can result in a stale cache.
• 竞争写入 / 并发更新：多个写入同时发生可能导致缓存过时。
• Missed Writes / Failing to Update the Cache: Failure to update or set cache correctly after a database write.
• 遗漏写入 / 未能更新缓存：在数据库写入后未能正确更新或设置缓存。
• Delayed Cache Updates or Deletes: Slow propagation of updates or invalidation can leave the cache out of sync.
• 延迟的缓存更新或删除： 更新或失效的缓慢传播可能导致缓存不同步。
• Application-Level Bugs: Bugs in application side caching logic.
• 应用层错误：应用程序侧缓存逻辑中的错误。

Maintaining cache consistency with the database is crucial for data accuracy, especially in distributed systems with concurrent web requests. Consistent caching ensures reliable read-after-write behavior, improving performance and user experience. Without it, applications may face unpredictable behavior and user frustration. A well-designed caching system boosts performance, ensures consistency, and delivers up-to-date data even under high concurrency.

维护缓存与数据库的一致性对于数据准确性至关重要，特别是在具有并发 web 请求的分布式系统中。一致的缓存确保可靠的读后写行为，提高性能和用户体验。如果没有它，应用程序可能会面临不可预测的行为和用户挫败感。一个设计良好的缓存系统提升性能，确保一致性，并在高并发下提供最新数据。

Racing Writes

竞争写入

Let’s look at the scenario where two writers, A and B, update the same user in the database but write to the cache in a different order, causing the cac...