I went to BJUG last week to see a presentation about Jini by someone from GigaSpaces. It was an intensely interesting presentation for a number of reasons. First off, I knew the presenter, Owen Taylor. About 6 years ago, I took a class from him, along with a few other people. The class covered BEA Weblogic and EJBs. I’ve attended (and given a couple) technical presentations in my time including some conferences. I don’t think I’ve ever met someone who was more energetic and practiced at conveying hard concepts than Owen Taylor. Owen! Start blogging!
Another reason it was interesting is that Brian Pontarelli, an old friend, really likes Jini and has told me about some of his experiences. I actually looked into it when Bill DeHora published his entry two classic hardbacks. I downloaded Jini and JavaSpaces (Jini is the framework, JavaSpaces is the tuple space repository.) and started playing with it. The final reason that it was an interesting presentation is that JavaSpaces is something that I have never had a chance to use, and didn’t foresee using in the future. By the end of the presentation, I was convinced that this concept deserved more research, if nothing else.
What follows are my scribbled notes from that meeting, along with a smattering of other comments and thoughts regarding these technologies. More information is here, however no presentation artifacts are available, unfortunately.
The problem with distributed systems is that they move data around a lot. What you really want is for the processing and the data to be at most one step apart. Stored procedures do this, but you can’t change the logic easily.
Jini was originally developed for pervasive computing, but the focus of the presentation was on the enterprise applications that can be built based on that spec. This class of applications has some amazing features, including low latency, extremely high throughput and ‘100%’ uptime capability.
For that reason, many large institutions are looking at replacing or augmenting JEE (nee J2EE) applications with JavaSpace applications. He mentioned that GigaSpaces recruited him with the notion that a laptop could run 3 million events an hour. This kind of blew his mind.
JavaSpaces is the command pattern–code and data are distributed, based on Linda. Orbitz uses the technology and talks about 100% uptime. Anyplace where you are batching, you can now do it in real time. The key is to keep everytihing in memory and use replication for persistance, rather than disk. (Eventually you want to push it to disk, for reporting and auditing purposes, but you can do that asynchronously.) Databases tend to be used as a bus between in memory processes right now, and you can replace that with a JavaSpace.
Jini is composed of discrete objects that can run anywhere; more to the point, they don’t care where they run. It also expects failure, as opposed to many other technologies that simply assume that things will run correctly. Jini is a LAN based technology, though Owen mentioned that there are ways to turn it into a WAN technology and cited several examples. I am not competent to give a general overview of Jini–please check out this tutorial for more information.
One thing that really struck me is that all of the complexity that EJB and other JEE technologies hide (clustering, transaction management, thread management, lifecycle), JavaSpaces revels in. Owen actually mentioned that JavaSpaces brings skills that JEE developers currently rarely need to use, like threading and classloading, back into the toolbox, rather than depending on a vendor. That can be a plus and a minus, right? The whole point of not trusting servlet threading to a business developer is that it allows them to focus on the business logic. The problem with much of JEE is that it hasn’t done a very good job of doing this. Do you remember the ‘deployer’ role?
Jini has only interfaces; the named implementations are shipped around transparently. Ha ha, just like EJB remote calls are transparent. However, one very nice aspect of Jini is that when you register an implementation of an interface, you say how long the implementation is going to be available (the lease length). As a service provider, you can keep track of that lease and re-register yourself when it is near to up. Of course, if the service is no longer available, for whatever reason, it is not provided to clients–there’s no need for the JVM to garbage collect. The clients do need to be a bit smart about things though.
As for licensing, version 2.0 has been released under an apache license, as opposed to the Sun Community Source License, which was the previous license. This should grow the jini.org community significantly.
Configuration of Jini takes place with a java syntax, which can be a bit confusing, since you don’t compile and execute it. The names of the services (reggie, webster) are a bit cutesy. Webster is the web server which serves implementation classes, but shouldn’t be used in a production environment. Use Tomcat.
Spring and JavaSpaces are complementary; work is in progress to integrate them and completion is expected in the next few months. GigaSpaces has scaled implementations (linearly!) to 2000 cpus on 500 machines….
At this point Owen began talking about various architectural patterns that could be used with Jini; he also covered some war stories. However, I didn’t take any notes–you’ll have to see him talk sometime.
Issues include (so my friend says) versioning. Owen mentioned that debugging isn’t a strong suit. And I did some parallel computing for my senior thesis so I know that splitting up problems so they can be parallelized is not always as easy as you’d like. However, the web paradigm is actually rather suited to parallelization, since you do have the request/response model. The problem is, as it so often is, state.