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JBoss World 2011
much talked about keynote ended with a big bang - a live demo that many
thought we were insane to even try and pull off - and has sparked off a
lot of interest, many claiming JBoss has got its mojo back
. One of the things people keep asking is, what actually went on? How did we build such a demo? How can we do the same?
Firstly, if you did not attend the keynote or did not watch it online, I recommend that you stop reading this now, and go and watch the keynote. A recording is available online
(the demo starts at about minute 35).
Ok, now that you've been primed,
lets talk about the role Infinispan played in that demo. The demo
involved reading mass volumes of real-time data off a Twitter stream,
and storing these tweets in an Infinispan grid. This primary grid
as Grid-A), and ran off 3 large rack-mount servers. The Infinispan
nodes were standalone, bootstrapped off a simple Main class, and formed a
cluster, running in asynchronous distributed mode
with 2 data owners.
Andrew Sacamano did an excellent job of building an HTML 5-based webapp to visualise what goes on in such a grid, making use of cache listeners
pushing events to browsers and browsers rendering the "spinning
spheres" using HTML 5's canvas tag. So now we could visualise data and
data movement within a grid of Infinispan nodes.
Twitter data started to populate the grid, we fired up a second grid
(Grid-B) consisting of 8 nodes. Again, these nodes were configured using
asynchronous distribution and 2 data owners, but this time these nodes
were running on very small and cheap plugtop computers. These plugtops -
- are constrained devices with 512MB of RAM, a 1GHz ARM processor.
Yes, your iPhone has more grunt :-) And yes, these sub-iPhone devices were running a real data grid!
The purpose of this was to demonstrate the extremely low footprint and
overhead Infinispan imposes on your hardware (we even had to run the zero assembly port of OpenJDK
an interpreted-mode JVM, since the processor only had a 16-bit bus!).
We also had a server running JBossAS running Andrew's cool visualisation
webapp rendering the contents of Grid-B, so people could "see" the data
in both grids.
We then fired up Drools
to have it mine the contents of Grid-A and send it to Grid-B applying
some rules to select the interesting tweets, namely the ones having the
. With this in place, we then invited the audience to
participate - by tweeting with hashtag #JBW, as well as the hashtag of
your favourite JBoss project - e.g., #infinispan :-) People were
allowed to vote for more than one project, and the most prolific tweeter
was to win a prize. This started a frenzy of tweeting, and was
reflected in the two grid visualisations.
Not only Infinispan is very quick here: needless to say, Drools was sending the tweets from Grid-A to Grid-B using HornetQ
, the fastest JMS implementation on the planet.
Jay Balunas of Richfaces
built a TwitterStream app with live updates of these tweets for various
devices, including iPhones, iPads, Android phones and tablets, and of
course, desktop web browsers, grabbing data off Grid-B. Christian
Sadilek and Mike Brock from the Errai
team also built a tag-cloud application visualising popular tags as a
tag cloud, again off Grid-B, making use of Errai to push events to the
After simulating Mark Proctor to
try cheating the system with a script, we could recover the correct
votes: clear Grid-B, update the Drools rules to have it discard the
cheat tweets, and have a cleaned up stream of tweets flow to Grid-B.
All applications, including
Drools and the visualizations, where using a JPA interface to store or
load the tweets: it was powered by an early preview of HibernateOGM
which aims to abstract any NoSQL store as a JPA persistence store while
still providing some level of consistency. As HibernateOGM is not
feature complete, it was using Hibernate Search
to provide query capabilities via a Lucene index, and using the
Infinispan integration of Hibernate Search to distribute the index on
We then demonstrated failover,
as we invited the winner to come up on stage to choose and brutally
un-plug one of the plugtops of his choice from Grid-B - this plugtop
became his prize. Important to note, the webapps running off the grid
did not risk to lose any data, Drools pulling stuff off Grid-A onto
Grid-B was still able to continue running, the Lucene index could
continually be updated and queried by the remaining nodes.
From an Infinispan perspective, what did this demo make use of?
So a fairly simple setup, using
simple embeddable components, cheap hardware, to build a fairly complex
application with excellent failover and scalability properties.
So we where depending on wi-fi connectivity, internet access, a live tweet stream, technology previews and people's cooperation!
To make things more interesting,
the day before the demo one of the servers died; hardware failure:
didn't survive the trip. A second server, meant to serve the UI webapps,
started reporting failures on all network interfaces just before
starting the demo: it could not figure out hardware addresses of cluster
peers, and we had no time to replace him: its backup was already dead.
Interesting enough we could tap in some advanced parameters of the
JGroups configuration to workaround this issue.
was pre-recorded! Actually the backup plan was to have Mark Little
dancing a tip-tap; next year we will try to stretch our demo even more
so you might see that dance!
So here you can see the recording of the event: http://www.jboss.org/jbw2011keynote
or listen to the behind the scenes podcast
After the demo, we did hear of a
large commercial application using Infinispan and Drools in precisely
this manner - except instead of Twitter, the large data stream was
flight seat pricing, changing dynamically and constantly, and eventually
rendered to web pages of various travel sites - oh, and they weren't
running on plugtops in case you were thinking ;) So, the example isn't
How do you use Infinispan? We'd love for you to share stories with us.
The Java Zone is brought to you in partnership with ZeroTurnaround. Check out this 8-step guide to see how you can increase your productivity by skipping slow application redeploys and by implementing application profiling, as you code!