//FishFarm wins second prize in GlassFish Community Innovation Awards Program

I recently won with FishFarm the second prize in the GlassFish Community Innovation Awards Program -  which is pretty cool. I would never have thought that I have a chance to win something in the GAP.

Since you probably don't know what FishFarm actually is, I will try to introduce it with this entry.

Formal:

FishFarm = Shoal + Fork/Join Framework
Shoal = simple to use clustering framework currently based on JXTA and used within GlassFish

Fork/Join Framework = pretty cool concurrency framework for local parallelization of tasks (jsr166y targeted for Java 7)

=> FishFarm = simple but pretty cool solution for distributing concurrent tasks over a p2p network [q.e.d.]

Informal:

Project FishFarm is a simple solution for distributing computational intensive tasks over the network based on Java SE APIs.

The goal of this project is to take any task written in the Fork/Join Framework (JSR166y targeted for Java 7) and distribute the computation over multiple nodes in a grid. FishFarm introduces no new frameworks and is also no full featured distribution system.

The initial focus was to make the ForkJoinPool (which is a core part of jsr166y) distributable with as few code changes as possible. Thanks to Doug Lee these modifications are now in trunk of his Fork/Join Framework and he even provided a handful of utility methods to make further extensions simpler.

How it works:

All you need to make your Application distributable is to replace ForkJoinPool with FishFarm's DistributedForkJoin pool.

  ForkJoinPool pool = new DistributedForkJoinPool();

// submit as many tasks you want (nothing changed)
Future futureResult1 = pool.submit(new MyTask());
Future futureResult2 = pool.submit(new LongRunningTask());

// block until done
  System.out.println("result of task 1: " + futureResutl1.get());
// or ask if done
System.out.println("task 2 isDone=" + futureResutl2.isDone());

Every DistributedForkJoinPool is member of a peer2peer network and automatically steals work from overstrained pools if idle. DistributedForkJoinPool extends ForkJoinPool and will complete submitted tasks even when working offline or on node failures. No additional configuration required.

I wouldn't call it ready for production yet but it should be stable enough to have fun ;-)

webstartable demos


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In case you are wondering why you are reading this entry via the RSS feed of my brother's (Adam) blog. This is a bug which confuses both urls, I hope this should be fixed with the next roller deployment.

This is Michael - over and out ;-)


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Comments:

Hi Michael,

I am looking forward to see the Java7 days with cool ForkJoin stuff and your distributed one is surely the way to go... For now, we will stick with ExecutorService for parallel task execution.

Great idea,
-talip

Posted by Talip Ozturk on October 05, 2008 at 12:36 PM CEST #

hi Talip,

thank you for the kind words. I am not sure if my solution is the way to go until i did a lot more QE with loadtests but at least it already caused enough momentum to make jsr166y distributable.

Primary objectives complete ;-)

keep up the good work with Hazelcast!

regards,
michael

Posted by mbien on October 05, 2008 at 04:28 PM CEST #

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