Zookeeper + Curator = Distributed sync

An application developed for one of my recent projects at TouK involved multiple servers. There was a requirement to ensure failover for the system’s components. Since I had already a few separate components I didn’t want to add more of that, and since there already was a Zookeeper ensemble running – required by one of the services, I’ve decided to go that way with my solution. What is Zookeeper? Just a crude distributed synchronization framework. However, it implements Paxos-style algorithms (http://en.wikipedia.org/wiki/Paxos_(computer_science)) to ensure no split-brain scenarios would occur. This is quite an important feature, since I don’t have to care about that kind of problems while using this app. You just need to create an ensemble of a couple of its instances – to ensure high availability. It is basically a virtual filesystem, with files, directories and stuff. One could ask why another filesystem? Well this one is a rather special one, especially for distributed systems. The reason why creating all the locking algorithms on top of Zookeeper is easy is its Ephemeral Nodes – which are just files that exist as long as connection for them exists. After it disconnects – such file disappears. With such paradigms in place it’s fairly easy to create some high level algorithms for synchronization. Having that in place, it can safely integrate multiple services ensuring loose coupling in a distributed way. Zookeeper from developer’s POV With all the base services for Zookeeper started, it seems there is nothing else, than just connect to it and start implementing necessary algorithms. Unfortunately, the API is quite basic and offers files and directories abstractions with the addition of different node type (file types) – ephemeral and sequence. It is also possible to watch a node for changes. Using bare Zookeeper is hard! Creating connections is tedious – and there is lots of things to take care of. Handling an established connection is hard – when establishing connection to ensemble, it’s necessary to negotiate a session also. During the whole process a number of exceptions can occur – these are “recoverable” exceptions, that can be gracefully handled and not break the connection. class="c8"><span>So, Zookeeper API is hard.</span></p><p class="c1"><span></span></p><p class="c8"><span>Even if one is proficient with that API, then there come recipes. The reason for using Zookeeper is to be able to implement some more sophisticated algorithms on top of it. Unfortunately those aren&rsquo;t trivial and it is again quite hard to implement them without bugs.</span> And since distributed systems are hard, why would anyone want another difficult to handle tool? Enter Curator <p class="c8"><span>Happily, guys from Netflix implemented a nice abstraction for dealing with Zookeeper internals. They called it Curator and use it extensively in the company&rsquo;s environment. Curator offers consistent API for Zookeeper&rsquo;s functionality. It even implements a couple of recipes for distributed systems.</span> File read/write <p class="c8"><span>The basic use of Zookeeper is as a distributed configuration repository. For this scenario I only need read/write capabilities, to be able to write and read files from the Zookeeper filesystem. This code snippet writes a sample json to a file on ZK filesystem.</span> <a href=”#” name="0"></a> EnsurePath ensurePath = new EnsurePath(markerPath); ensurePath.ensure(client.getZookeeperClient()); String json = “...”; if (client.checkExists().forPath(statusFile(core)) != null) client.setData().forPath(statusFile(core), json.getBytes()); else client.create().forPath(statusFile(core), json.getBytes()); Distributed locking Having multiple systems there may be a need of using an exclusive lock for some resource, or perhaps some big system requires it’s components to synchronize based on locks. This “recipe” is an ideal match for those situations. ref="#" name="b0329bbbf14b79ffaba1139881914aea887ef6a3"></a> lock = new InterProcessSemaphoreMutex(client, lockPath); lock.acquire(5, TimeUnit.MINUTES); … do sth … lock.release();  (from https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/LockingRemotely.java) Sevice Advertisement <p class="c8"><span>This is quite an interesting use case. With many small services on different servers it is not wise to exchange ip addresses and ports between them. When some of those services may go down, while other will try to replace them - the task gets even harder. </span> That’s why, with Zookeeper in place, it can be utilised as a registry of existing services. If a service starts, it registers into the ServiceRegistry, offering basic information, like it’s purpose, role, address, and port. Services that want to use a specific kind of service request an access to some instance. This way of configuring easily decouples services from their configuration. Basically this scenario needs ? steps: <span>1. Service starts and registers its presence (</span><span class="c5"><a class="c0" href="https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerAdvertiser.java#L44">https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerAdvertiser.java#L44</a></span><span>)</span><span>:</span> ServiceDiscovery discovery = getDiscovery(); discovery.start(); ServiceInstance si = getInstance(); log.info(si); discovery.registerService(si); 2. Another service – on another host or in another JVM on the same machine tries to discover who is implementing the service (https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerFinder.java#L50): <a href=”#” name="3"></a> instances = discovery.queryForInstances(serviceName); The whole concept here is ridiculously simple – the service advertising its presence just stores a file with its whereabouts. The service that is looking for service providers just look into specific directory and read stored definitions. In my example, the structure advertised by services looks like this (+ some getters and constructor – the rest is here: https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/model/WorkerMetadata.java): public final class WorkerMetadata { private final UUID workerId; private final String listenAddress; private final int listenPort; } Source code <p class="c8"><span>The above recipes are available in Curator library (</span><span class="c5"><a class="c0" href="http://curator.incubator.apache.org/">http://curator.incubator.apache.org/</a></span><span>). Recipes&rsquo; usage examples are in my github repo at </span><span class="c5"><a class="c0" href="https://github.com/zygm0nt/curator-playground">https://github.com/zygm0nt/curator-playground</a></span> Conclusion <p class="c8"><span>If you&rsquo;re in need of a reliable platform for exchanging data and managing synchronization, and you need to do it in a distributed fashion - just choose Zookeeper. Then add Curator for the ease of using it. Enjoy!</span> image comes from: http://www.flickr.com/photos/jfgallery/2993361148 all source code fragments taken from this repo: https://github.com/zygm0nt/curator-playground An application developed for one of my recent projects at TouK involved multiple servers. There was a requirement to ensure failover for the system’s components. Since I had already a few separate components I didn’t want to add more of that, and since there already was a Zookeeper ensemble running – required by one of the services, I’ve decided to go that way with my solution. What is Zookeeper? Just a crude distributed synchronization framework. However, it implements Paxos-style algorithms (http://en.wikipedia.org/wiki/Paxos_(computer_science)) to ensure no split-brain scenarios would occur. This is quite an important feature, since I don’t have to care about that kind of problems while using this app. You just need to create an ensemble of a couple of its instances – to ensure high availability. It is basically a virtual filesystem, with files, directories and stuff. One could ask why another filesystem? Well this one is a rather special one, especially for distributed systems. The reason why creating all the locking algorithms on top of Zookeeper is easy is its Ephemeral Nodes – which are just files that exist as long as connection for them exists. After it disconnects – such file disappears. With such paradigms in place it’s fairly easy to create some high level algorithms for synchronization. Having that in place, it can safely integrate multiple services ensuring loose coupling in a distributed way. Zookeeper from developer’s POV With all the base services for Zookeeper started, it seems there is nothing else, than just connect to it and start implementing necessary algorithms. Unfortunately, the API is quite basic and offers files and directories abstractions with the addition of different node type (file types) – ephemeral and sequence. It is also possible to watch a node for changes. Using bare Zookeeper is hard! Creating connections is tedious – and there is lots of things to take care of. Handling an established connection is hard – when establishing connection to ensemble, it’s necessary to negotiate a session also. During the whole process a number of exceptions can occur – these are “recoverable” exceptions, that can be gracefully handled and not break the connection. class="c8"><span>So, Zookeeper API is hard.</span></p><p class="c1"><span></span></p><p class="c8"><span>Even if one is proficient with that API, then there come recipes. The reason for using Zookeeper is to be able to implement some more sophisticated algorithms on top of it. Unfortunately those aren&rsquo;t trivial and it is again quite hard to implement them without bugs.</span> And since distributed systems are hard, why would anyone want another difficult to handle tool? Enter Curator <p class="c8"><span>Happily, guys from Netflix implemented a nice abstraction for dealing with Zookeeper internals. They called it Curator and use it extensively in the company&rsquo;s environment. Curator offers consistent API for Zookeeper&rsquo;s functionality. It even implements a couple of recipes for distributed systems.</span> File read/write <p class="c8"><span>The basic use of Zookeeper is as a distributed configuration repository. For this scenario I only need read/write capabilities, to be able to write and read files from the Zookeeper filesystem. This code snippet writes a sample json to a file on ZK filesystem.</span> <a href=”#” name="0"></a> EnsurePath ensurePath = new EnsurePath(markerPath); ensurePath.ensure(client.getZookeeperClient()); String json = “...”; if (client.checkExists().forPath(statusFile(core)) != null) client.setData().forPath(statusFile(core), json.getBytes()); else client.create().forPath(statusFile(core), json.getBytes()); Distributed locking Having multiple systems there may be a need of using an exclusive lock for some resource, or perhaps some big system requires it’s components to synchronize based on locks. This “recipe” is an ideal match for those situations. ref="#" name="b0329bbbf14b79ffaba1139881914aea887ef6a3"></a> lock = new InterProcessSemaphoreMutex(client, lockPath); lock.acquire(5, TimeUnit.MINUTES); … do sth … lock.release();  (from https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/LockingRemotely.java) Sevice Advertisement <p class="c8"><span>This is quite an interesting use case. With many small services on different servers it is not wise to exchange ip addresses and ports between them. When some of those services may go down, while other will try to replace them - the task gets even harder. </span> That’s why, with Zookeeper in place, it can be utilised as a registry of existing services. If a service starts, it registers into the ServiceRegistry, offering basic information, like it’s purpose, role, address, and port. Services that want to use a specific kind of service request an access to some instance. This way of configuring easily decouples services from their configuration. Basically this scenario needs ? steps: <span>1. Service starts and registers its presence (</span><span class="c5"><a class="c0" href="https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerAdvertiser.java#L44">https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerAdvertiser.java#L44</a></span><span>)</span><span>:</span> ServiceDiscovery discovery = getDiscovery(); discovery.start(); ServiceInstance si = getInstance(); log.info(si); discovery.registerService(si); 2. Another service – on another host or in another JVM on the same machine tries to discover who is implementing the service (https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerFinder.java#L50): <a href=”#” name="3"></a> instances = discovery.queryForInstances(serviceName); The whole concept here is ridiculously simple – the service advertising its presence just stores a file with its whereabouts. The service that is looking for service providers just look into specific directory and read stored definitions. In my example, the structure advertised by services looks like this (+ some getters and constructor – the rest is here: https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/model/WorkerMetadata.java): public final class WorkerMetadata { private final UUID workerId; private final String listenAddress; private final int listenPort; } Source code <p class="c8"><span>The above recipes are available in Curator library (</span><span class="c5"><a class="c0" href="http://curator.incubator.apache.org/">http://curator.incubator.apache.org/</a></span><span>). Recipes&rsquo; usage examples are in my github repo at </span><span class="c5"><a class="c0" href="https://github.com/zygm0nt/curator-playground">https://github.com/zygm0nt/curator-playground</a></span> Conclusion <p class="c8"><span>If you&rsquo;re in need of a reliable platform for exchanging data and managing synchronization, and you need to do it in a distributed fashion - just choose Zookeeper. Then add Curator for the ease of using it. Enjoy!</span> image comes from: http://www.flickr.com/photos/jfgallery/2993361148 all source code fragments taken from this repo: https://github.com/zygm0nt/curator-playground

An application developed for one of my recent projects at TouK involved multiple servers. There was a requirement to ensure failover for the system’s components. Since I had already a few separate components I didn’t want to add more of that, and since there already was a Zookeeper ensemble running – required by one of the services, I’ve decided to go that way with my solution.

What is Zookeeper?

Just a crude distributed synchronization framework. However, it implements Paxos-style algorithms (http://en.wikipedia.org/wiki/Paxos_(computer_science)) to ensure no split-brain scenarios would occur. This is quite an important feature, since I don’t have to care about that kind of problems while using this app. You just need to create an ensemble of a couple of its instances – to ensure high availability. It is basically a virtual filesystem, with files, directories and stuff. One could ask why another filesystem? Well this one is a rather special one, especially for distributed systems. The reason why creating all the locking algorithms on top of Zookeeper is easy is its Ephemeral Nodes – which are just files that exist as long as connection for them exists. After it disconnects – such file disappears.

With such paradigms in place it’s fairly easy to create some high level algorithms for synchronization.

Having that in place, it can safely integrate multiple services ensuring loose coupling in a distributed way.

Zookeeper from developer’s POV

With all the base services for Zookeeper started, it seems there is nothing else, than just connect to it and start implementing necessary algorithms. Unfortunately, the API is quite basic and offers files and directories abstractions with the addition of different node type (file types) – ephemeral and sequence. It is also possible to watch a node for changes.

Using bare Zookeeper is hard!

Creating connections is tedious – and there is lots of things to take care of. Handling an established connection is hard – when establishing connection to ensemble, it’s necessary to negotiate a session also. During the whole process a number of exceptions can occur – these are “recoverable”
exceptions, that can be gracefully handled and not break the connection.

So, Zookeeper API is hard. Even if one is proficient with that API, then there come recipes. The reason for using Zookeeper is to be able to implement some more sophisticated algorithms on top of it. Unfortunately those aren’t trivial and it is again quite hard to implement them without bugs.

And since distributed systems are hard, why would anyone want another difficult to handle tool?

Enter Curator

Happily, guys from Netflix implemented a nice abstraction for dealing with Zookeeper internals. They called it Curator and use it extensively in the company’s environment. Curator offers consistent API for Zookeeper’s functionality. It even implements a couple of recipes for distributed systems.

File read/write

The basic use of Zookeeper is as a distributed configuration repository. For this scenario I only need read/write capabilities, to be able to write and read files from the Zookeeper filesystem. This code snippet writes a sample json to a file on ZK filesystem.

EnsurePath ensurePath = new EnsurePath(markerPath);
ensurePath.ensure(client.getZookeeperClient());
String json = “...”;
if (client.checkExists().forPath(statusFile(core)) != null)
     client.setData().forPath(statusFile(core), json.getBytes());
else
     client.create().forPath(statusFile(core), json.getBytes());

Distributed locking

Having multiple systems there may be a need of using an exclusive lock for some resource, or perhaps some big system requires it’s components to synchronize based on locks. This “recipe”
is an ideal match for those situations.

lock = new InterProcessSemaphoreMutex(client, lockPath);
lock.acquire(5, TimeUnit.MINUTES);
… do sth …
lock.release();

 (from https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/LockingRemotely.java)

Sevice Advertisement

This is quite an interesting use case. With many small services on different servers it is not wise to exchange ip addresses and ports between them. When some of those services may go down, while other will try to replace them – the task gets even harder.

That’s why, with Zookeeper in place, it can be utilised as a registry of existing services.

If a service starts, it registers into the ServiceRegistry, offering basic information, like it’s purpose, role, address, and port.

Services that want to use a specific kind of service request an access to some instance. This way of configuring easily decouples services from their configuration.

Basically this scenario needs ? steps:

1. Service starts and registers its presence (https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerAdvertiser.java#L44

ServiceDiscovery discovery = getDiscovery();
            discovery.start();
            ServiceInstance si = getInstance();
            log.info(si);
            discovery.registerService(si);

2. Another service – on another host or in another JVM on the same machine tries to discover who is implementing the service (https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/curator/WorkerFinder.java#L50):

instances = discovery.queryForInstances(serviceName);

The whole concept here is ridiculously simple – the service advertising its presence just stores a file with its whereabouts. The service that is looking for service providers just look into specific directory and read stored definitions.

In my example, the structure advertised by services looks like this (+ some getters and constructor – the rest is here: https://github.com/zygm0nt/curator-playground/blob/master/src/main/java/pl/touk/model/WorkerMetadata.java):

public final class WorkerMetadata {
    private final UUID workerId;
    private final String listenAddress;
    private final int listenPort;
}

Source code

The above recipes are available in Curator library (http://curator.incubator.apache.org/
usage examples are in my github repo at https://github.com/zygm0nt/curator-playground

Conclusion

If you’re in need of a reliable platform for exchanging data and managing synchronization, and you need to do it in a distributed fashion – just choose Zookeeper. Then add Curator for the ease of using it. Enjoy!


  1. image comes from: http://www.flickr.com/photos/jfgallery/2993361148
  2. all source code fragments taken from this repo: https://github.com/zygm0nt/curator-playground
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33rd Degree day 2 review

Second day of 33rd had no keynotes, and thus was even more intense. A good conference is a conference, where every hour you have a hard dilemma, because there are just too many interesting presentations to see. 33rd was definitely such a conference, and the seconds day really shined.

There were two workshops going on through the day, one about JEE6 and another about parallel programming in Java. I was considering both, but decided to go for presentations instead. Being on the Spring side of the force, I know just as much JEE as I need, and with fantastic GPars (which has Fork/Join, actors, STM , and much more), I won't need to go back to Java concurrency for a while.

GEB - Very Groovy browser automation

Luke Daley works for Gradleware, and apart from being cheerful Australian, he's a commiter to Grails, Spock and a guy behind Geb, a  browser automation lib using WebDriver, similar to Selenium a bit (though without IDE and other features).

I have to admit, there was a time where I really hated Selenium. It just felt so wrong to be writing tests that way, slow, unproductive and against the beauty of TDD. For years I've been treating frontend as a completely different animal. Uncle Bob once said at a Ruby conference: "I'll tell you what my solution to frontend tests is: I just don't". But then, you can only go so far with complex GUIs without tests, and once I've started working with Wicket and its test framework, my perspective changed. If Wicked has one thing done right, it's the frontend testing framework. Sure tests are slow, on par with integration tests, but it is way better than anything where the browser has to start up front, and I could finally do TDD with it.

Working with Grails lately, I was more than eager to learn a proper way to do these kind of tests with Groovy.

GEB looks great. You build your own API for every page you have, using CSS selectors, very similar to jQuery, and then write your tests using your own DSL. Sounds a bit complicated, but assuming you are not doing simple HTML pages, this is probably the way to go fast. I'd have to verify that on a project though, since with frontend, too many things look good on paper and than fall out in code.

The presentation was great, Luke managed to answer all the questions and get people interested. On a side note, WebDriver may become a W3C standard soon, which would really easy browser manipulation for us. Apart from thing I expected Geb to have, there are some nice surprises like working with remote browsers (e.g. IE on remote machine), dumping HTML at the end of the test and even making screenshots (assuming you are not working with headless browser).

Micro services - Java, the Unix Way

James Lewis works for ThoughtWorks and gave a presentation, for which alone it was worth to go to Krakow. No, seriously, that was a gem I really didn't see coming. Let me explain what it was about and then why it was such a mind-opener.
ThoughtWorks had a client, a big investment bank, lots of cash, lots of requirements. They spent five weeks getting the analysis done on the highest possible level, without getting into details yet (JEDI: just enough design initially). The numbers were clear: it was enormous, it will take them forever to finish, and what's worse, requirements were contradictory. The system had to have all three guarantees of the CAP theorem, a thing which is PROVED to be impossible.
So how do you deal with such a request? Being ThoughtWorks you probably never say "we can't", and having an investment bank for a client, you already smell the mountains of freshly printed money. This isn't something you don't want to try, it's just scary and challenging as much as it gets.
And then, looking at the requirements and drawing initial architecture, they've reflected, that there is a way to see the light in this darkness, and not to end up with one, monstrous application, which would be hard to finish and impossible to maintain. They have analyzed flows of data, and came up with an idea.
What if we create several applications, each so small, that you can literally "fit it in your head", each communicating with a simple web protocol (Atom), each doing one thing and one thing only, each with it's own simple embedded web server, each working on it's own port, and finding out other services through some location mechanism. What if we don't treat the web as an external environment for our application, but instead build the system as if it was inside the web, with the advantages of all the web solutions, like proxies, caches, just adding a small queue before each service, to be able to turn it off and on, without loosing anything. And we could even use a different technology, with different pair of CAP guarantees, for each of those services/applications.
Now let me tell you why it's so important for me.
If you read this blog, you may have noticed the subtitle "fighting chaos in the Dark Age of Technology". It's there, because for my whole IT life I've been pursuing one goal: to be able to build things, that would be easy to maintain. Programming is a pure pleasure, and as long as you stay near the "hello world" kind of complexity, you have nothing but fun. If we ever feel burned out, demotivated or puzzled, it's when our systems grow so much, that we can no longer understand what's going on. We lose control. And from that point, it's usually just a way downward, towards complete chaos and pain.
All the architecture, all the ideas, practices and patterns, are there for just this reason - to move the border of complexity further, to make the size of "possible to fit in your head" larger. To postpone going into chaos. To bring order and understanding into our systems.
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That has changed a lot in my life. No longer I have to choose one database, one language and one architecture for the whole application. I can divide and conquer, choose what I want to sacrifice and what advantages I want here, in this specific place of my app, not worrying about other places where it won't fit.
But there is one problem in here: the limit of technologies I'm using, to keep the system simple, and not require omnipotence to be able to maintain, to fix bugs or implement Change Requests.
And here is the accidental solution, ThoughtWorks' micro services bring: if you system is build of the web, of small services that do one thing only, and communicate through simple protocol (like Atom), there is little code to understand, and in case of bugs or Change Requests, you can just tear down one of the services. and build it anew.
James called that "Small enough to throw them away. Rewrite over maintain". Now, isn't that a brilliant idea? Say you have a system like that, build over seven years ago, and you've got a big bag of new requests from your client. Instead of re-learning old technologies, or paying extra effort to try to bring them up-to-date (which is often simply impossible), you decide which services you are going to rewrite using the best tools of your times, and you do it, never having to dig into the original code, except for specification tests.
Too good to be true? Well, there are caveats. First, you need DevOps in your teams, to get the benefits of the web inside your system, and to build in the we as opposite to against it. Second, integration can be tricky. Third, there is not enough of experience with this architecture, to make it safe. Unless... unless you realize, that UNIX was build this way, with small tools and pipes.
That, perhaps. is the best recommendation possible.

Concurrency without Pain in Pure Java

Throughout the whole conference, Grzegorz Duda had a publicly accessible wall, with sticky notes and two sides: what's bad and what's good. One of the note on the "bad" side was saying: "Sławek Sobótka and Paweł Lipiński at the same time? WTF?". 
I had the same thought. I wanted to see both. I was luckier though, since I'm pretty sure I'll yet be able too see their presentations this year, as 33rd is the first conference in a long run of conferences planned for 2012. Not being able to decide which one to see, I've decided to go for Venkat Subramaniam and his talk about concurrency. Unless we are lucky at 4Developers, we probably won't see Venkat again this year.
Unfortunately for me, the talk ("show" seems like a more proper word), was very basic, and while very entertaining, not deep enough for me. Venkat used Closure STM to show how bad concurrency is in pure Java, and how easy it is with STM. What can I say, it's been repeated so often, it's kind of obvious by now.
Venkat didn't have enough time to show the Actor model in Java. That's sad, as the further his talk, the more interesting it was. Perhaps there should be a few 90min sessions next year?

Smarter Testing with Spock

After the lunch, I had a chance to go for Sławek Sobótka again, but this time I've decided to listen to one of the commiters of Spock, the best thing in testing world since Mockito. 
Not really convinced? Gradle is using Spock (not surprisingly), Spring is starting to use Spock. I've had some experience with Spock, and it was fabulous. We even had a Spock workshop at TouK, lately. I wanted to see what Luke Daley can teach me in an hour. 
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What's new in Groovy 2.0?

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We are in the days, were the performance difference between Java and Groovy falls to a mere 20%.  That's really little compared to where it all started from (orders of magnitude). That's cool. Also, after reading some posts and successful stories about Groovy++ use, I'd really like to try static compilation with this language
Someone from the audience asked a good question. Why not use Groovy++ as the base for static compilation instead. It turned out that Groovy++ author was also there. The main reason Guillaume gave, were small differences in how they want to handle internal things. If static compilation works fine with 2.0, Groovy++ may soon die, I guess.

Scala for the Intrigued


For the last talk this day, I've chosen a bit of Scala, by Venkat Subramaniam. That was unfortunately a completely basic introduction, and after spending 15 minutes listening about differences between var and val, I've left to get prepared to the BOF session, which I had with Maciek Próchniak.

BOF: Beautiful failures


I'm not in the position to review my own talk, and conclude whether it's failure was beautiful or not, but there is one things I've learned from it.
Never, under none circumstances, never drink five coffees the day you give a talk. To keep my mind active without being overwhelmed by all the interesting knowledge, I drank those five coffees, and to my surprise, when the talk started, the adrenaline shot brought me over the level, where you loose your breath, your pulse, and you start to loose control over your own voice. Not a really nice experience. I've had the effects of caffeine intoxication for the next two days. Lesson learned, I'm staying away from black beans for some time.
If you want the slides, you can find them here.
And that was the end of the day. We went to the party, to the afterparty, we got drunk, we got the soft-reset of our caches, and there came another day of the conference.

You can find my review from the last day in here.