Introduction Have you ever wondered what the maximum number of database connections provided by a given RDBMS is? In this article, we are going to see what limits the number of database connections, no matter if you’re using Oracle, SQL Server, PostgreSQL, or MySQL.
Proxies FlexyPool monitors connection pool usage and so it needs to intercept the connection close method call. For simplicity sake, the first version was relying on dynamic proxies for this purpose: As straightforward as it may be, a proxy invocation is slower than a decorator, which calls the target method using a direct invocation. Because all connection pools use proxies anyway, adding another proxy layer only adds more call-time overhead and so now FlexyPool supports connection decorators as well.
Introduction Oracle Express Edition is the free version of Oracle Enterprise Edition and its smaller size makes it very convenient for testing various Oracle functionalities. According to Oracle documentation, the Express Edition can use at most one CPU and 1 GB of RAM, but in reality, there are other limitations that are not always obvious.
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.
Introduction I previously wrote about the benefits of connection pooling and why monitoring it is of crucial importance. This post will demonstrate how FlexyPool can assist you in finding the right size for your connection pools. Know your connection pool The first step is to know your connection pool settings. My current application uses XA transactions, therefore we use Bitronix transaction manager, which comes with its own connection pooling solution. Accord to the Bitronix connection pool documentation we need to use the following settings: minPoolSize: the initial connection pool size maxPoolSize: the… Read More
Introduction When I started working on enterprise projects we were using J2EE and the pooling data source was provided by the application server. Scaling up meant buying more powerful hardware to support the increasing request demand. The vertical scaling meant that for supporting more requests, we would have to increase the connection pool size accordingly. Horizontal scaling Our recent architectures shifted from scaling up to scaling out. So instead of having one big machine hosting all our enterprise services, we now have a distributed service network. This has numerous advantages: Each JVM… Read More
Introduction All projects I’ve been working on have used database connection pooling and that’s for very good reasons. Sometimes we might forget why we are employing one design pattern or a particular technology, so it’s worth stepping back and reason on it. Every technology or technological decision has both upsides and downsides, and if you can’t see any drawback you need to wonder what you are missing. The database connection life-cycle Every database read or write operation requires a connection. So let’s see how database connection flow looks like: The flow goes… Read More