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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How to use mocks in controller tests

Even since I started to write tests for my Grails application I couldn't find many articles on using mocks. Everyone is talking about tests and TDD but if you search for it there isn't many articles.

Today I want to share with you a test with mocks for a simple and complete scenario. I have a simple application that can fetch Twitter tweets and present it to user. I use REST service and I use GET to fetch tweets by id like this: http://api.twitter.com/1/statuses/show/236024636775735296.json. You can copy and paste it into your browser to see a result.

My application uses Grails 2.1 with spock-0.6 for tests. I have TwitterReaderService that fetches tweets by id, then I parse a response into my Tweet class.


class TwitterReaderService {
Tweet readTweet(String id) throws TwitterError {
try {
String jsonBody = callTwitter(id)
Tweet parsedTweet = parseBody(jsonBody)
return parsedTweet
} catch (Throwable t) {
throw new TwitterError(t)
}
}

private String callTwitter(String id) {
// TODO: implementation
}

private Tweet parseBody(String jsonBody) {
// TODO: implementation
}
}

class Tweet {
String id
String userId
String username
String text
Date createdAt
}

class TwitterError extends RuntimeException {}

TwitterController plays main part here. Users call show action along with id of a tweet. This action is my subject under test. I've implemented some basic functionality. It's easier to focus on it while writing tests.


class TwitterController {
def twitterReaderService

def index() {
}

def show() {
Tweet tweet = twitterReaderService.readTweet(params.id)
if (tweet == null) {
flash.message = 'Tweet not found'
redirect(action: 'index')
return
}

[tweet: tweet]
}
}

Let's start writing a test from scratch. Most important thing here is that I use mock for my TwitterReaderService. I do not construct new TwitterReaderService(), because in this test I test only TwitterController. I am not interested in injected service. I know how this service is supposed to work and I am not interested in internals. So before every test I inject a twitterReaderServiceMock into controller:


import grails.test.mixin.TestFor
import spock.lang.Specification

@TestFor(TwitterController)
class TwitterControllerSpec extends Specification {
TwitterReaderService twitterReaderServiceMock = Mock(TwitterReaderService)

def setup() {
controller.twitterReaderService = twitterReaderServiceMock
}
}

Now it's time to think what scenarios I need to test. This line from TwitterReaderService is the most important:


Tweet readTweet(String id) throws TwitterError

You must think of this method like a black box right now. You know nothing of internals from controller's point of view. You're only interested what can be returned for you:

  • a TwitterError can be thrown
  • null can be returned
  • Tweet instance can be returned

This list is your test blueprint. Now answer a simple question for each element: "What do I want my controller to do in this situation?" and you have plan test:

  • show action should redirect to index if TwitterError is thrown and inform about error
  • show action should redirect to index and inform if tweet is not found
  • show action should show found tweet

That was easy and straightforward! And now is the best part: we use twitterReaderServiceMock to mock each of these three scenarios!

In Spock there is a good documentation about interaction with mocks. You declare what methods are called, how many times, what parameters are given and what should be returned. Remember a black box? Mock is your black box with detailed instruction, e.g.: I expect you that if receive exactly one call to readTweet with parameter '1' then you should throw me a TwitterError. Rephrase this sentence out loud and look at this:


1 * twitterReaderServiceMock.readTweet('1') >> { throw new TwitterError() }

This is a valid interaction definition on mock! It's that easy! Here is a complete test that fails for now:


import grails.test.mixin.TestFor
import spock.lang.Specification

@TestFor(TwitterController)
class TwitterControllerSpec extends Specification {
TwitterReaderService twitterReaderServiceMock = Mock(TwitterReaderService)

def setup() {
controller.twitterReaderService = twitterReaderServiceMock
}

def "show should redirect to index if TwitterError is thrown"() {
given:
controller.params.id = '1'
when:
controller.show()
then:
1 * twitterReaderServiceMock.readTweet('1') >> { throw new TwitterError() }
0 * _._
flash.message == 'There was an error on fetching your tweet'
response.redirectUrl == '/twitter/index'
}
}

| Failure: show should redirect to index if TwitterError is thrown(pl.refaktor.twitter.TwitterControllerSpec)
| pl.refaktor.twitter.TwitterError
at pl.refaktor.twitter.TwitterControllerSpec.show should redirect to index if TwitterError is thrown_closure1(TwitterControllerSpec.groovy:29)

You may notice 0 * _._ notation. It says: I don't want any other mocks or any other methods called. Fail this test if something is called! It's a good practice to ensure that there are no more interactions than you want.

Ok, now I need to implement controller logic to handle TwitterError.


class TwitterController {

def twitterReaderService

def index() {
}

def show() {
Tweet tweet

try {
tweet = twitterReaderService.readTweet(params.id)
} catch (TwitterError e) {
log.error(e)
flash.message = 'There was an error on fetching your tweet'
redirect(action: 'index')
return
}

[tweet: tweet]
}
}

My tests passes! We have two scenarios left. Rule stays the same: TwitterReaderService returns something and we test against it. So this line is the heart of each test, change only returned values after >>:


1 * twitterReaderServiceMock.readTweet('1') >> { throw new TwitterError() }

Here is a complete test for three scenarios and controller that passes it.


import grails.test.mixin.TestFor
import spock.lang.Specification

@TestFor(TwitterController)
class TwitterControllerSpec extends Specification {

TwitterReaderService twitterReaderServiceMock = Mock(TwitterReaderService)

def setup() {
controller.twitterReaderService = twitterReaderServiceMock
}

def "show should redirect to index if TwitterError is thrown"() {
given:
controller.params.id = '1'
when:
controller.show()
then:
1 * twitterReaderServiceMock.readTweet('1') >> { throw new TwitterError() }
0 * _._
flash.message == 'There was an error on fetching your tweet'
response.redirectUrl == '/twitter/index'
}

def "show should inform about not found tweet"() {
given:
controller.params.id = '1'
when:
controller.show()
then:
1 * twitterReaderServiceMock.readTweet('1') >> null
0 * _._
flash.message == 'Tweet not found'
response.redirectUrl == '/twitter/index'
}


def "show should show found tweet"() {
given:
controller.params.id = '1'
when:
controller.show()
then:
1 * twitterReaderServiceMock.readTweet('1') >> new Tweet()
0 * _._
flash.message == null
response.status == 200
}
}

class TwitterController {

def twitterReaderService

def index() {
}

def show() {
Tweet tweet

try {
tweet = twitterReaderService.readTweet(params.id)
} catch (TwitterError e) {
log.error(e)
flash.message = 'There was an error on fetching your tweet'
redirect(action: 'index')
return
}

if (tweet == null) {
flash.message = 'Tweet not found'
redirect(action: 'index')
return
}

[tweet: tweet]
}
}

The most important thing here is that we've tested controller-service interaction without logic implementation in service! That's why mock technique is so useful. It decouples your dependencies and let you focus on exactly one subject under test. Happy testing!