DDevelopment & Design

OVal – validate your models quickly and effortlessly!

Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this va…Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this va…

Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this validations – sure, it would. But there were some advanced rules XSD would not handle, or would render the schema document very complicated.

Rules I needed to express were like:

  • person’s first_name and last_name should be of appropriate length – between 2 and 20, and additionally one could pass a zero-length string just to remove the previous value
  • state field should consist only defined values – as in dictionary value – this one would be completable with XSD’s enumerations, but would require often changing schema files and redistributing them to interested parties :(

The library I’ve decided to use for this task is OVal and it came out really nice! Read on to find out the details!

Oval is quite mature library that allows POJO validation, but is not JSR303 (bean validation) implementation. It has converters that enable it to understand those annotations, but I’m not sure about the compatibility.

I’ve tried only a subset of the available checks, among which were:

  • NotNull
  • NotEmpty
  • Length

There are many more, and their attributes give interesting ways to configure the validation process. But using them was rather easy and did not require to much brainstorming. What I really needed were custom checks. And in this area OVal shows it’s strength. Implementing a check is really easy.

I needed an annotation that would check a field against some values in a dictionary. If field’s value was in the given set, than the validation would succeed, if not, an exception would be thrown. To accomplish this task it is required to implement two classes: annotation class and check class – called by the validation engine on a given field.

Let’s start with our new annotation:

 

In the above snippet I’ve defined a check-annotation, that would be used like this:

 

You can pass file – containing dictionary values for this field. There is also message field in the annotation which is an error message returned by the validation engine of failed check – pretty handy. And can be expressed in .properties file as:

 

Placeholder, like context, will be replaced with correct values supplied by the validation engine.

Annotating a field is not enough. It is also needed to create a validator for this kind of check. The name of the class is already defined in DictionaryValue annotation, it is called DictionaryValueCheck and I’ve done this check this way:

 

What this basically does is:

  1. when file is set – read dictionary content from the file into map
  2. upon check request just lookup value in dictionary parsed from the input file

And that’s it!

For me Oval is really great tool. With it at ones disposal it is extremely easy to create any imaginable validation you need. This library is really easy to use and offers lots of handy features.

But perhaps I’m reinventing the wheel and all this can be done easily with some other library? Share Your opinion!

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DDevelopment & Design

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>

  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

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>

  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
DDevelopment & Design

ODEO new release

Recently, I released a new version 1.1.34 of ODEO (it's ODE tuned for Oracle and ServiceMix).You can check details (and downloads) here: http://top.touk.pl/confluence/display/top/ODEO.This version contains yet another set of fixes, which drive your BPE...Recently, I released a new version 1.1.34 of ODEO (it's ODE tuned for Oracle and ServiceMix).You can check details (and downloads) here: http://top.touk.pl/confluence/display/top/ODEO.This version contains yet another set of fixes, which drive your BPE...