Retrospective January In the beginning of 2014, I took the initial version of my time series MongoDB aggregation example and pass it through a multistage optimization process, from indexing to advanced data-modelling: MongoDB time series: Introducing the aggregation framework A beginner’s guide to MongoDB performance turbocharging MongoDB and the fine art of data modelling February In February, I starting developing FlexyPool, the ultimate connection pool sizing utility. This was a great opportunity to dig into Queuing Theory and the following articles capture some of my findings: The anatomy of Connection Pooling FlexyPool,… Read More
Introduction A relational database strong consistency model is based on ACID transaction properties. In this post we are going to unravel the reasons behind using different transaction isolation levels and various configuration patterns for both resource local and JTA transactions. Isolation and consistency In a relational database system, atomicity and durability are strict properties, while consistency and isolation are more or less configurable. We cannot even separate consistency from isolation as these two properties are always related. The lower the isolation level, the less consistent the system will get. From the least… Read More
Introduction Hibernate fetching strategies can really make a difference between an application that barely crawls and a highly responsive one. In this post, I’ll explain why you should prefer query-based fetching instead of global fetch plans. Fetching 101 Hibernate defines four association retrieving strategies: Fetching Strategy Description Join The association is OUTER JOINED in the original SELECT statement Select An additional SELECT statement is used to retrieve the associated entity(entities) Subselect An additional SELECT statement is used to retrieve the whole associated collection. This mode is meant for to-many associations Batch An… Read More
Introduction In my previous post I demonstrated how you can scale optimistic locking through write-concerns splitting. Version-less optimistic locking is one lesser-known Hibernate feature. In this post, I’ll explain both the good and the bad parts of this approach. Version-less optimistic locking Optimistic locking is commonly associated with a logical or physical clocking sequence, for both performance and consistency reasons. The clocking sequence points to an absolute entity state version for all entity state transitions. To support legacy database schema optimistic locking, Hibernate added a version-less concurrency control mechanism. To enable this… Read More
Introduction Memoization is a method-level caching technique for speeding-up consecutive invocations. This post will demonstrate how you can achieve request-level repeatable reads for any data source, using Spring AOP only. Spring Caching Spring offers a very useful caching abstracting, allowing you do decouple the application logic from the caching implementation details. Spring Caching uses an application-level scope, so for a request-only memoization we need to take a DIY approach.