Local process cluster management for distributed computation
How can you build a responsive and robust nodejs server that does some heavy computational lifting? Some node libraries (like the awesome node-bcrypt) do their own threading internally and combine that with an async API. This allows libraries to internally thread their calls and use multiple cores.
While this is pretty awesome, it is significant work for library implementors, and as this pattern becomes rampant, the application author loses fine grained control over the resource usage of their server as well as the relative priority of compute tasks.
If you just naively run computation on the main evaluation thread, you're blocking node.js from doing anything else and making your whole server unresponsive.
node-compute-cluster is a tiny abstraction around a group of
processes and the built-in IPC introduced in NodeJS 0.6.x. It provides a simple
API by which you can allocate and run work on a cluster of computation processes.
This allows you to perform multiprocessing at a more granular level, and produce
a responsive yet efficient computation server.
$ npm install compute-cluster
First you write your main program:
const computecluster = ;// allocate a compute clustervar cc =module: './worker.js';var toRun = 10// then you can perform work in parallelfor var i = 0; i < toRun; i++cc;;
Next you write your
All done! Now you're distributing your computational load across multiple processes.
Allocates a computation cluster. Options include:
module- required the path to the module to load
max_processes- the maximum number of processes to spawn (default is
ciel(#cpus * 1.25))
max_backlog- the maximum length of the backlog, -1 indicates no limit (default is 10 * max_processes) an error will be returned when max backlog is hit.
max_request_time- the maximum amount of time a request should take, in seconds. An error will be returned when we expect a request will take longer.
var cc = 'compute-cluster'module: './foo.js'max_backlog: -1;
An error event will be emited in exceptional circumstances. Like if a child crashes. Catch error events like this:
Default behavior is to exit on error if you don't catch.
Events raise that hold an english, developer readable string describing the state of the implementation.
enqueue a job to be run on the next available compute process, spawning one
if required (and
max_processes isn't hit).
args will be passed into the process (available via
cb is optional, and will be invoked with two params,
err indicates hard errors, response indicates successful roundtrip to the
compute process and is whatever the decided to
process.send() in response.
Kill all child processes, invoking callback (with err param) when complete.
Copyright (c) 2011, Lloyd Hilaiel firstname.lastname@example.org
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