To solve this problem, in my opinion, the pool should be self tunning. Just like the Evictor thread (which is just a trigger), another thread would wakeup at regular intervals and gather statistical data and analyse it. As a result action would be taken (like changing the values of the pool settings) to adapt the pool to the usage pattern.
How you you go about monitoring the usage pattern of a pool?
The only ideas I have right now is using a moving average of the active connections and may be remembering this average throught the day so that the pool that anticipate usage. Imagine an automatic process that uses the pool once a day at 1:00 and borrows 1000 objects from the pool in a few seconds: The pool could anticipate this regular usage and create more objects in the pool.
I'm not very good at statistics and I hope that some of you are and could explain how statistics could help in this task.
This self tuning thing could be a more general problem and find other applications in other pagakges.
Interesting idea. A "resource manager" component that could support different heuristics for monitoring and controlling resource levels. An object pool could be a managed resource. Configuration metadata could abstract resource mgt interfaces (so the pool itself, for example would not have to change). In many cases, very simple reactive growth / shrinkage (growth and shrinkage triggered by resource availability thresholds) would work fine. Predictive modelling would require you to quantify and measure lots of things -- cost of starvation / overload, cost to create/activate, destroy/passivate, cost to maintain idle resources, resource request arrival rate, service time (at different load levels), etc. Really more operations research than statistics. Could be worthwhile in some cases. There are lots of different heuristics that could be applied. Defining the interfaces to support a wide range of heuristics could be interesting.
One more note on this. Web applications, which probably dominate [pool]'s user base, often present "bursty" and irregular load profiles. This presents some special problems for both modelling and adaptive heuristics. Growing a pool on demand, for example, can fail if rampup takes too long when a "flash crowd" has shown up. Here is an interesting article describing some of the things that come up:
http://lass.cs.umass.edu/~lass/papers/pdf/TR03-37.pdf
Phil
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