Multi phased processing in scala

Last time in our project we had to add progress bar for visualization of long time running process. Process was made of a few phases and we had to print in which phase we currently are. In first step we conclude that we need to create a class of Progre…

Last time in our project we had to add progress bar for visualization of long time running process. Process was made of a few phases and we had to print in which phase we currently are. In first step we conclude that we need to create a class of Progress which will be passed as an implicit parameter to our service. Then we will wrap method calls be inProgress method which will notify some e.g. akka actor about phase begin and phase end.

But this approach has some disadvantages. Firstly before we start service’s operation we need to init progress with count of all phases to get know ratio of progress finish. With this approach we had to add some extra counting before operation start.

If we want to keep real progress notifications the numbers of phases had to fit count of inPhase blocks. Some of phases were dynamically computed and some where omitted in case of failure validations results. This code become to be unmaintained.

We found that we need to join computation of phases with real phase processing. In this case we need to change approach from building process to building chain of phases that will run the process. Each phase will take the result of previous phase and transform it to new output. So example process will look like this:

Code giving this chain functionality looks like this:

We’ve used right associative operator :: for building chain of phases. “Body” of phases is piped by andThen: processPrevWrapped andThen processNext. For nil-tail we need to have a factory creating empty chain with identity “body” function.

Also if we have this kind of tool, we can modify piping code according to nature of our flow. For example if we are using scalaz.Validation we can do validating chain which will extract a success from n-step output and pass it to input of next step (like flatMap). In the other hand if n-step will return Failure, we will skip all remaining phases of validating chain.

To make building of chain more production-ready we add some extra features:

  • Chaining of chains (sth like ::: in scala Lists)
  • Transforming of input/output – for adding some “glue” code for simpler phases chaining
  • Wrapping of chains – also some “glue” code doing both input and output transformations
  • Sequencing of chains – sequenced processing of multiple phases with the same input

If you are interested in using similar approach, take a look at my github project: scala-phases-chain. If you want to integrate this tool with akka actors, simply change MultiPhasedProgress.notifyAboutStatus method to look like this:

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Apache HISE + Apache Camel

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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