Friday, May 20, 2011

Object Pool pattern


  • Object pooling can offer a significant performance boost; it is most effective in situations where the cost of initializing a class instance is high, the rate of instantiation of a class is high, and the number of instantiations in use at any one time is low.


  • Object pools (otherwise known as resource pools) are used to manage the object caching. A client with access to a Object pool can avoid creating a new Objects by simply asking the pool for one that has already been instantiated instead. Generally the pool will be a growing pool, i.e. the pool itself will create new objects if the pool is empty, or we can have a pool, which restricts the number of objects created.
  • It is desirable to keep all Reusable objects that are not currently in use in the same object pool so that they can be managed by one coherent policy. To achieve this, the Reusable Pool class is designed to be a singleton class.
Object pooling in java is often seen as an anti pattern and/or wasted effort - but there are still valid reasons to think about pooling for certain kind of applications.
The JVM allocates objects much faster from managed heap (young generation; contiguous and defragmented) as you could ever recycle objects from a self written pool running on top of a VM. A good configured garbage collector is also able to delete unused objects fast. GCs in fact don't delete objects explicitly, they rather evacuate all surviving objects and sweep whole memory regions in a very efficient manner and only when its necessary to reduce runtime overhead.
Object allocation (of small objects) on modern JVMs is even so fast that making a copy of immutable objects sometimes outperforms modification of mutable (and often old) objects. JVM languages like scala or clojure make heavy use of this observation. One of the reasons for that anomaly is that generational JVMs are designed to be able to deal with loads of short living objects which makes them inexpensive compared to long living objects in old generations.

Performance does not always mean Throughput

Rendering a game with 60fps might be optimal throughput for a renderer but the performance might be still unacceptable when all frames are rendered in the first half of the second with the second half spent on GC ;). Even if Object Pools may not increase system throughput they can still increase determinism of your application. Here are some observations and tips which might help:

When should I consider Object Pools?

  • GC tuning did not help - you want to try something else
  • The application creates a lot of objects which die in the old generation
  • Your Objects are expansive to create but easy to recycle
  • Determinism, e.g response time (soft real time requirements) is more important for you than throughput

Pro Pooling:

  • pools reduce GC activity in peak times (worst case scenarios)
  • are easy to implement and test (its basically an array ;))
  • are easy to disable (inject a fake pool which returns only new Objects)

Con Pooling:

  • more (old) objects are referenced when a GC kicks in (increases gc overhead)
  • memory leaks (don't forget to reclaim your objects!)
  • cause additional problems in a multi-threaded scenario (new Object() is thread safe!)
  • may decrease throughput
  • cumbersome, repetitive client code
When you decided to use pools you have to make sure to reclaim all objects as soon they are no longer used. One way of doing this is by applying the static factory method pattern for object allocation and a per object dispose method for deallocation.


to be added soon

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