DDevelopment & Design

Apache HISE. Nowy element otwartego stosu aplikacji SOA.

Apache HISE (Human Interactions Service Engine) to projekt, którego celem jest implementacja specyfikacji WS-HumanTask (Web Services Human Task). Specyfikacja ta opisuje zadania wykonywane przez ludzi jako usługi podlegające mechanizmom orkiestracji. HISE znajduje się obecnie w inkubatorze Apache. Obsługa procesów biznesowych jest zwykle realizowana za pomocą orkiestracji usług sieciowych. Mechanizmem tym steruje język BPEL (Business Process Execution Language). BPEL pozwala na definiowanie procesów w usługach sieciowych oraz koordynację wywoływania zewnętrznych usług. Język BPEL pozwala wyrazić konstrukcje zgodne z paradygmatem programowania strukturalnego, a jednocześnie umożliwia tworzenie równoległych ścieżek wykonania. Human Task w SOA BPEL jest dojrzałym produktem. Nie daje jednak możliwości opisu procesów wymagających zaangażowania ludzi. Tymczasem interakcje z ludźmi są istotnym elementem każdego, nawet najbardziej zautomatyzowanego, procesu biznesowego. Potrzeba znalezienia w SOA odpowiedniego miejsca dla usług realizowanych przez osobę ujawnia się zawsze podczas prac nad integracją usług w przedsiębiorstwach. Odpowiedzią na tę potrzebę jest wydana w 2007 roku, po kilku latach gromadzenia doświadczeń w dziedzinie integracji, specyfikacja Web Services Human Task. Implementacja WS-HumanTask stwarza możliwość szerszej adaptacji technologii BPEL. Celem specyfikacji WS-HumanTask jest umożliwienie włączenia zadań realizowanych przez ludzi do istniejących już mechanizmów orkiestracji. Aby było to możliwe, zadania te muszę być traktowane przez system jak zewnętrzne usługi. Dlatego zadania WS-HumanTask składają się z jednej strony z interfejsu wyrażonego przy pomocy WSDL i opisującego usługę, z drugiej – z zestawu funkcji pozwalających na zarządzanie zadaniami. W tej sytuacji fakt realizacji usługi przez osobę, a nie przez komponent systemu informatycznego, nie ma znaczenia. Specyfikacja WS-HumanTask opisuje sposób definiowania usług i cykl życia zadań w powiązaniu z rolami osób je obsługujących. Komponent implementujący specyfikację wczytuje definicje zadań (human task definition) zawierające: specyfikację WSDL usług realizowanej przez zadania, użytkowników mogących realizować zadania bądź nimi zarządzać, sposoby eskalacji i informacje o oczekiwanych czasach wykonania, informacje o sposobie prezentacji na liście zadań i sposobach realizacji w różnych środowiskach klienckich. HISE w opensourceowym stosie SOA Znajdujący się obecnie w inkubatorze projekt Apache HISE będzie w pełni implementował specyfikację WS-HumanTask. Rozwiązanie będzie dystrybuowane w postaci modułów pozwalających na uruchomienie w różnych środowiskach. W tej chwili utworzone dystrybucje pozwalają na uruchomienie aplikacji w kontenerze serwletów lub jako komponentu OSGi w ServiceMix4.

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DDevelopment & Design

Thought static method can’t be easy to mock, stub nor track? Wrong!

No matter why, no matter is it a good idea. Sometimes one just wants to check or it's necessary to be done. Mock a static method, woot? Impossibru!

In pure Java world it is still a struggle. But Groovy allows you to do that really simple. Well, not groovy alone, but with a great support of Spock.

Lets move on straight to the example. To catch some context we have an abstract for the example needs. A marketing project with a set of offers. One to many.

import spock.lang.Specification

class OfferFacadeSpec extends Specification {

    OfferFacade facade = new OfferFacade()

    def setup() {
        GroovyMock(Project, global: true)
    }

    def 'delegates an add offer call to the domain with proper params'() {
        given:
            Map params = [projId: projectId, name: offerName]

        when:
            Offer returnedOffer = facade.add(params)

        then:
            1 * Project.addOffer(projectId, _) >> { projId, offer -> offer }
            returnedOffer.name == params.name

        where:
            projectId | offerName
            1         | 'an Offer'
            15        | 'whasup!?'
            123       | 'doskonała oferta - kup teraz!'
    }
}
So we test a facade responsible for handling "add offer to the project" call triggered  somewhere in a GUI.
We want to ensure that static method Project.addOffer(long, Offer) will receive correct params when java.util.Map with user form input comes to the facade.add(params).
This is unit test, so how Project.addOffer() works is out of scope. Thus we want to stub it.

The most important is a GroovyMock(Project, global: true) statement.
What it does is modifing Project class to behave like a Spock's mock. 
GroovyMock() itself is a method inherited from Specification.  The global flag is necessary to enable mocking static methods.
However when one comes to the need of mocking static method, author of Spock Framework advice to consider redesigning of implementation. It's not a bad advice, I must say.

Another important thing are assertions at then: block. First one checks an interaction, if the Project.addOffer() method was called exactly once, with a 1st argument equal to the projectId and some other param (we don't have an object instance yet to assert anything about it).
Right shit operator leads us to the stub which replaces original method implementation by such statement.
As a good stub it does nothing. The original method definition has return type Offer. The stub needs to do the same. So an offer passed as the 2nd argument is just returned.
Thanks to this we can assert about name property if it's equal with the value from params. If no return was designed the name could be checked inside the stub Closure, prefixed with an assert keyword.

Worth of  mentioning is that if you want to track interactions of original static method implementation without replacing it, then you should try using GroovySpy instead of GroovyMock.

Unfortunately static methods declared at Java object can't be treated in such ways. Though regular mocks and whole goodness of Spock can be used to test pure Java code, which is awesome anyway :)No matter why, no matter is it a good idea. Sometimes one just wants to check or it's necessary to be done. Mock a static method, woot? Impossibru!

In pure Java world it is still a struggle. But Groovy allows you to do that really simple. Well, not groovy alone, but with a great support of Spock.

Lets move on straight to the example. To catch some context we have an abstract for the example needs. A marketing project with a set of offers. One to many.

import spock.lang.Specification

class OfferFacadeSpec extends Specification {

    OfferFacade facade = new OfferFacade()

    def setup() {
        GroovyMock(Project, global: true)
    }

    def 'delegates an add offer call to the domain with proper params'() {
        given:
            Map params = [projId: projectId, name: offerName]

        when:
            Offer returnedOffer = facade.add(params)

        then:
            1 * Project.addOffer(projectId, _) >> { projId, offer -> offer }
            returnedOffer.name == params.name

        where:
            projectId | offerName
            1         | 'an Offer'
            15        | 'whasup!?'
            123       | 'doskonała oferta - kup teraz!'
    }
}
So we test a facade responsible for handling "add offer to the project" call triggered  somewhere in a GUI.
We want to ensure that static method Project.addOffer(long, Offer) will receive correct params when java.util.Map with user form input comes to the facade.add(params).
This is unit test, so how Project.addOffer() works is out of scope. Thus we want to stub it.

The most important is a GroovyMock(Project, global: true) statement.
What it does is modifing Project class to behave like a Spock's mock. 
GroovyMock() itself is a method inherited from Specification.  The global flag is necessary to enable mocking static methods.
However when one comes to the need of mocking static method, author of Spock Framework advice to consider redesigning of implementation. It's not a bad advice, I must say.

Another important thing are assertions at then: block. First one checks an interaction, if the Project.addOffer() method was called exactly once, with a 1st argument equal to the projectId and some other param (we don't have an object instance yet to assert anything about it).
Right shit operator leads us to the stub which replaces original method implementation by such statement.
As a good stub it does nothing. The original method definition has return type Offer. The stub needs to do the same. So an offer passed as the 2nd argument is just returned.
Thanks to this we can assert about name property if it's equal with the value from params. If no return was designed the name could be checked inside the stub Closure, prefixed with an assert keyword.

Worth of  mentioning is that if you want to track interactions of original static method implementation without replacing it, then you should try using GroovySpy instead of GroovyMock.

Unfortunately static methods declared at Java object can't be treated in such ways. Though regular mocks and whole goodness of Spock can be used to test pure Java code, which is awesome anyway :)
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

Distributed scans with HBase

HBase is by design a columnar store, that is optimized for random reads. You just ask for a row using rowId as an identifier and you get your data instantaneously. Performing a scan on part or whole table is a completely different thing. First of all, it is sequential. Meaning it is rather slow, because it doesn't use all the RegionServers at the same time. It is implemented that way to realize the contract of Scan command - which has to return results sorted by key. So, how to do this efficiently?HBase is by design a columnar store, that is optimized for random reads. You just ask for a row using rowId as an identifier and you get your data instantaneously. Performing a scan on part or whole table is a completely different thing. First of all, it is sequential. Meaning it is rather slow, because it doesn't use all the RegionServers at the same time. It is implemented that way to realize the contract of Scan command - which has to return results sorted by key. So, how to do this efficiently?