How to monitor a Java EE DataSource
Introduction FlexyPool is an open-source framework that can monitor a DataSource connection usage. This tool come out of necessity, since we previously lacked support for provisioning connection pools. FlexyPool was initially designed for stand-alone environments and the DataSource proxy configuration was done programmatically. Using Spring bean aliases, we could even substitute an already configured DataSource with the FlexyPool Metrics-aware proxy alternative.
How does Hibernate Query Cache work
Introduction Now that I covered both Entity and Collection caching, it’s time to investigate how Query Caching works. The Query Cache is strictly related to Entities, and it draws an association between a search criterion and the Entities fulfilling that specific query filter. Like other Hibernate features, the Query Cache is not as trivial as one might think.
How does Hibernate TRANSACTIONAL CacheConcurrencyStrategy work
Introduction In my previous post, I introduced the READ_WRITE second-level cache concurrency mechanism. In this article, I am going to continue this topic with the TRANSACTIONAL strategy.
How does Hibernate READ_WRITE CacheConcurrencyStrategy work
Introduction In my previous post, I introduced the NONSTRICT_READ_WRITE second-level cache concurrency mechanism. In this article, I am going to continue this topic with the READ_WRITE strategy.
How does Hibernate NONSTRICT_READ_WRITE CacheConcurrencyStrategy work
Introduction In my previous post, I introduced the READ_ONLY CacheConcurrencyStrategy, which is the obvious choice for immutable entity graphs. When cached data is changeable, we need to use a read-write caching strategy and this post will describe how NONSTRICT_READ_WRITE second-level cache works.
How does Hibernate Collection Cache work
Introduction Previously, I described the second-level cache entry structure, Hibernate uses for storing entities. Besides entities, Hibernate can also store entity associations and this article will unravel the inner workings of collection caching.
How does Hibernate READ_ONLY CacheConcurrencyStrategy work
Introduction As I previously explained, enterprise caching requires diligence. Because data is duplicated between the database (system of record) and the caching layer, we need to make sure the two separate data sources don’t drift apart. If the cached data is immutable (neither the database nor the cache is able to modify it), we can safely cache it without worrying about any consistency issues. Read-only data is always a good candidate for application-level caching, improving read performance without having to relax consistency guarantees.
A beginner’s guide to Cache synchronization strategies
Introduction A system of record is the authoritative data source when information is scattered among various data providers. When we introduce a caching solution, we automatically duplicate our data. To avoid inconsistent reads and data integrity issues, it’s very important to synchronize the database and the cache (whenever a change occurs in the system). There are various ways to keep the cache and the underlying database in sync and this article will present some of the most common cache synchronization strategies.
Things to consider before jumping to application-level caching
Introduction Relational database transactions are ACID and the strong consistency model simplifies application development. Because enabling Hibernate caching is one configuration away, it’s very appealing to turn to caching whenever the data access layer starts showing performance issues. Adding a caching layer can indeed improve application performance, but it has its price and you need to be aware of it.
