Data storage is one of the most crucial parts of any applications, and we use many different tools and tricks to keep it in a good shape. We frequently use both old school relational systems with new approaches commonly known as NoSQL. We write sophisticated queries and use optimization techniques to give our end users the greatest possible experience. So why is persistence very often skipped in the testing efforts? Is it really that complex and painful to setup? During this talk we will have a closer look at Arquillian Persistence Extension together with NoSQLUnit. These tools remove that burden and boilerplate to make you a happy and productive programmer again! Join this session and see for yourself that writing tests for your data storage logic is as easy as writing normal unit tests!

1. Testing Polyglot
Persistence Done Right
Alex Soto
@alexsotob
Bartosz Majsak
@majson

2. ● Open source advocate
● lordofthejars.com curator
● Father
[alex@geecon ~]$ whoami
@alexsotob lordofthejars

3. ● Java Developer by day
● Open source junkie by night
● Conference speaker by passion
[bartek@geecon ~]$ whoami
@majson bartoszmajsak

4. FIRST things first

5. Fast Run more often
Isolated Can be executed in any order
Repeatable Always return the same result
Self-Validating Know exactly their purpose
Timely Run before code

6. Frequently omittedrules
in Persistencetests

7. FAST
Fast

8. FAST
Network access
Long bootstrap
Humongous amount of data

9. FASTHSQLDB
MongoDB (fongo)
Neo4J
Cassandra
Infinispan
HBase

10. Isolation

11. ISOLATION
BeerRepository beerRepository;
@Test
public void should_persist_beer() {
beerRepository.save(new Beer(“Mocny Full”));
}
@Test
public void should_count_beers() {
int beers = beerRepository.count();
assertThat(beers).isEqualTo(??);
}
}

12. ISOLATION
DBUnit
Unitils
NoSQLUnit
Arquillian Persistence Extension

13. Plain Old SQL World

14. Text
TITLE

15. Text
TITLE

16. FIRST ATTEMPT

17. FIRST ATTEMPT

18. FIRST ATTEMPT

19. FIRST ATTEMPT

20. <dataset>
<brewery id="1" name="Brew Dog" country="Scotland" />
<beer id="1" name="End of History" price="756"
alcohol="55.0" brewery_id="1" />
</dataset>
We can do better

21. And even better

22. Hipster’s world of
NoSQL

23. nding Topic
Why NoSQL?

24. Why NoSQL?
Clustering from scratch
“Schemaless”
Polyglot
More Natural for Developer

26. Manage Lifecycle
Maintain Database State
Polyglot Persistence
Spring Data Support

27. Text
Not a single point of access

28. Supported EnginesMongoDB
CouchDB
asticsearch
Neo4j
Redis
Infinispan
HBase
Cassandra

29. Text
Starting/Stopping Databases

30. Manging MongoDB Lifecycle

31. Text
Seeding Database with the Known Data

32. Seeding Database with Known Data

33. Demo Time

34. Arquillian

35. TITLE
Integration

36. TITLE
Containers

37. Text
TITLE
Deployments

38. TITLE

39. TITLE

40. TITLE

41. TITLE

42. TITLE

43. TITLE

44. @RunWith(Arquillian.class)
public class FluidOunceConverterTestCase {
@Deployment
public static JavaArchive createDeployment() {
return ShrinkWrap.create(JavaArchive.class, "test.jar")
.addClasses(FluidOunceConverter.class,
FluidOunceConverterBean.class);
}
@Inject
FluidOunceConverter converter;
@Test
public void should_convert_fluid_ounces_to_millilitres() {
// given
double ouncesToConvert = 8d;
double expectedMillilitres = 236.588237d;
// when
double ouncesInMl = converter.convertToMillilitres(ouncesToConvert);
// then
assertThat(ouncesInMl).isEqualTo(expectedMillilitres);
}
}

45. Demo Time

46. ● @UsingDataSet / @ShouldMatchDataSet
● @Cleanup / @CleanupUsingScript
● @ApplyScriptBefore / After
● @CreateSchema
● JPA 2nd level cache eviction

47. Demo Time

48. ● Standalone mode
● Scriptable data sets
● Full NoSQLUnit integration
● Schema validation
FUTURE