Hadoop for Enterprises

Hadoop’s usage as a big data processing framework gains a lot of attention lately. Now, not only big players see, that they can embrace the data their sites or products are generating and develop their businesses on it. For that to happen two things are needed: the data itself and means of processing really big amounts of it.

Gathering data is relatively easy. These are not necessarily structured data, you don’t need to plan their usage at first. Just start collecting them and than you may experiment with their potential usage. If they’ll come out as useless rubbish – deleting them won’t be hard But imagine the values it may contribute to your business:

  • faster services – working on optimized data
  • more clients – because of more relevant search results
  • happy clients – your service can “read their minds”
  • etc.

There are many companies that utilize Hadoop ecosystem for their own needs. You can read about some of them here: http://wiki.apache.org/hadoop/PoweredBy But since that page lacks insight into specific applications of Hadoop I’ve tried to delve into

details of how Hadoop helped tame some companies’ big data sets.

Facebook

Being a social network provider, a widely used one, they require no introduction. However if you’ve lived under a rock for last couple years just visit their website http://facebook.com

Their main usage is data warehousing. Since they require to be able to access the data fast and reliably they had a need for real-time querying of their huge, and always growing data set. Their switch from MySQL databases was required due to the increasing workloads they experienced with standard databases. What they got “out of the box” with Hadoop was all the benefits of distributed file system (HDFS features). They expanded the ideas behind that even further and implemented truly Highly Available file system without Single Point of Failure.

Facebook has 3 interesting usage scenarios in which Hadoop plays a major role:

  • Titan – is Facebook’s messaging system. It processes messages exchanged between users. Ensures that it happens fast and without glitches. Here Hadoop is used mainly as a huge, unlimited storage.
  • Puma – Facebook Insights – a tool providing page statistics for advanced Facebook users. Based on streams of data (clicks, likes, shares, comments and impressions) it graphs those data and makes it available near instantly.
  • ODS – Operational Data Store – which stores Facebook’s internal metrics – collections of OS and cluster health metrics. And it facilitates multiple accounting solutions.

Twitter

This popular micro-blogging platform, where you can register your account and follow friends and celebrities for their micro-messages does some pretty interesting things with their Hadoop cluster.

One of their motivations is to speed up their web-page’s functionality. That is why the compute users’ friendships in Twitter’s social graph with Hadoop. Using connections between users they calculate their relationship to each other and estimate groups of users.

Since this service’s users generate lots of content, the company conducts researches based on natural language processing. They probe what could be told about a user from his tweets. They use tweets’ contents for advertisement purpose, trends analysis and many more.

From tweets and user’s behaviours they characterise usage scenarios. Also, they gather usage statistics, like number of searches daily, number of tweets. Based on this seemingly irrelevant data they run comparisons of different types of users. Twitter analyzes data to determine whether mobile users, users who use third party clients or power users use Twitter differently from average users. Of course theses seem like really specific applications but nevertheless they are very original and base on the data that Twitter has been gathering for some time now.

EBay

Being the biggest auctioning site on the Internet, EBay uses Hadoop processing for increasing search relevance based on click-stream data, user data. This seems pretty obvious, considering their area of operation.

However the also have one other interesting thing – they try hard to automatically fill auctioned objects’ metadata, based on the descriptions and other data provided by users. They employ data mining approach for this tasks and judging from their constant growth it seems to work

LinkedIn

Social network for professionals, thou a lot smaller than Facebook. Based on click-streams they discover relations between users. All the data concerning latest visits on your profile or people you may know from other places – this comes from Hadoop based analysis of those clicks people make all the time on their sites.

Also a very neat feature, called InMaps (http://inmaps.linkedinlabs.com/) analyse declared schools and companies and generates data for graph with clustered friends of yours.

Last.fm

This on-line radio site, praised by many for its invaluable recommendations’ system seems like a rather small and simple service. But behind the facade of simple web page there are lots of data being processed, so that their services could match a certain level of perfection.

Such large volume of their data comes from scrobbles. Each users of their service listening to a song generates a note about this fact – called scrobble. Based on that and user profiles they calculate global band popularity charts, maps of bands’ popularity and many more usage statistics and timeline charts.

Conclusion

They just try to detect and trace new patterns in seemingly chaotic data sets. Perhaps you could also do the same? Analyze your data and expand your business value?

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Look forward to checking out your web page yet again.

I like what you guys are up too. This type of clever work and reporting!

Keep up the awesome works guys I’ve added you guys to my own blogroll.

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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

Wicket form submit not safe for redirecting to intercept page

The problem When you have a form, that anybody can see, but only logged on users can POST, you may want to redirect the user to the login page, and back to the form after login Using wicket 1.3/1.4, if you do that using redirectToInterceptPage(loginP...The problem When you have a form, that anybody can see, but only logged on users can POST, you may want to redirect the user to the login page, and back to the form after login Using wicket 1.3/1.4, if you do that using redirectToInterceptPage(loginP...