A worker pool is a very common pattern, and they exist in the standard libraries for many languages. The idea is simple: submit some sort of closure to a service which commits to running the closure in the future in some thread. Normally the work is shared out among many different threads and in the absence of anything fancier, one assumes a first-come-first-served queue of closures.
Erlang, with its light-weight process model is not a language which you would expect would require such an approach: processes are dirt cheap, and the scheduler maps processes onto threads when they are ready to be run — in many ways, the ErlangVM is a glorified implementation of a worker pool, only one that does pre-emption and other fancy features, in a very similar way to an OS kernel. However, we recently found in RabbitMQ a need for a worker pool. (more…)
People tend to like certain software packages to be scalable. This can have a number of different meanings but mostly it means that as you throw more work at the program, it may require some more resources, in terms of memory or CPU, but it nevertheless just keeps on working. Strangely enough, it’s fairly difficult to achieve this with finite resources. With things like memory, the classical hierarchy applies: as you use up more and more faster memory, you start to spill to slower memory — i.e. spilling to disk. The assumption tends to be that one always has enough disk space.
Other resources are even more limited, and are harder to manage. One of these is file descriptors. (more…)