Paths, Entities, and Types in Spring Data for Neo4j (also, I'm back)

I know it's been awhile since my last post, but, I assure you--one and all--that I have not left you kind folks for good.  I can also assure you that the cause of my literary absence has everything to do with being loaded down with work and is not a result of my gallivanting around the world whilst trying strange and wonderful new beers.

(Boy, do I ever wish that was the case.)

Strange AND wonderful!
[Courtesy: FOX]

No, I've managed to find some time in which to write a bit about something I've been looking into concerning SDN: Paths with multiple entity types.

So, without further ado, let's begin.

Yes, quite.
[Courtesy: samuelrunge.com and Monty Python)

Disclaimer

While the topics I'm about to go into could very well have solutions to them that I have yet to uncover, I'm presenting my findings and questions in the hopes that not only will someone find the discussion interesting/useful, but, that it might also help lead me to better solutions.

So, please do read on and try to keep the caveat above in mind.

Retrieving Heterogeneous Paths

If you'll recall from several posts ago, I had been attempting to write a web application based around the concept of a simple recommendation engine and a software retailer (a la Babbage's from the last century).  The implementation was being done using a Spring-based Java stack with Neo4j as the data store.

I had gotten to a point where I was able to load data into Neo4j via a method not unlike the one from Cineasts' (which can be found as part of the Spring Data Neo4j Reference).  A quick recap of the domain model follows below.

The domain model in question.

One important task of any recommendation engine is the ability to suggest entities that are relevant to a given starting point via some sequence of relationships.  Implementing such an engine, while quite doable, is something that I will eventually get to.

Another, more simple, task is to be able to see how two entities are related, i.e. "how do I get from point A to point B?".  As an example, one such question might be, "How is game A related to game B, even though the difference in publication dates is large?"  And yes, this type of question is extremely similar to the "Six Degrees of Separation" question.

I bet he's a gamer.
[Couresty: Wikipedia]

Some Basic Code

You might also recall that I had implemented a GameRepository class with the following signature:

 
public interface GameRepository extends GraphRepository<Game>, RelationshipOperationsRepository<Game>

With the above repository extending the GraphRepository and RelationshipOperationsRepository interfaces, we are provided with a host of cool (and handy) methods out of the box (tip: make sure you're comfortable with the "convention over configuration" paradigm, as there is a bit of magic that goes on with those OOTB methods).

As you'd expect, we can also add additional methods to the interface.  One example of a method you might want to add could be a custom Cypher query that returns all Game nodes with a particular property (the implementation of this is outside the scope of this post, but, it's actually pretty simple; if people want to see it, just shoot me a note!).

However, today we're looking to address the "Six Degrees of Separation" question (minus the limit on the degrees of separation), i.e. "how are node A and node B related"?

So let's give this a (very simple) shot:

 
@Query("START n=node(1), x=node(97) MATCH p = shortestPath( n-[*]-x ) RETURN p")
Iterable<EntityPath<Game, Game> > getPath();

Given that the nodes with IDs 1 and 97 are "Game" nodes, the Cypher query above is essentially determining how the two nodes are related.

(For the sake of this post, I'm ignoring the fact that there could be multiple "shortest paths" between the two nodes as it has little bearing on the goal of this post.)

Quickly going over the return type, SDN allows us to return back an EntityPath given a starting node type and an ending node type which, in this case, is the Game type.  An EntityPath is capable of storing nodes and their relationships as part of a Cypher path.  The Iterable portion of the return type is necessary unless you want to use EndResult instead of Iterable.

We can then access the individual path(s) via the Iterable return type.

(NOTE: There is currently a bug with SDN that throws an exception when calling a single path's .nodes() or .nodeEntities().  This bug has been around since SDN 2.1.RC4.)

Traversing the Returned Path

There's a reason my explanation of the code used stops where it does.  Those of you with a keen eye and/or are familiar with OOP/OOD will identify a potentially big stumbling block: How do you iterate through a path of nodes and/or relationships with potentially wholly disparate, unrelated types?  Given that this is SDN and is geared towards integrating easily with Java and POJOs, the issue becomes apparent.

How do we solve this?

Solution 1

Make sure the nodes you are after all either implement a common interface or are derived from a common class.

Seem too good to be true?  You're right, because it is.  While there may be some scenarios in which this solution might work, it is often the case in a graph database the nodes/relationships are entirely unrelated concepts/types, e.g. Game and Customer, or, Game and Developer.  This separation would imply that there are likely methods and attributes that are specific to a given type that would have no business being in a shared superclass or interface.

Solution 2

Employ some form of reflection.

There it is: The "r" word.  Reflection is generally quite costly and so immediately handicaps its appeal.

A "poor man's" reflection might be to implement a series of "if/else" blocks to check types and perform some appropriate casting.  I think we can see that this could and would become very ugly and difficult to maintain.

What about full-on automated reflection?  Well, we run into a bit of a snag with that, too: In a typical assignment operation, we have a left-hand side (LHS) and a right-hand side (RHS), e.g. TheClass theClassInstance = new TheClass();.  The RHS of the assignment is fairly straight forward with reflection.  Since SDN persists a __type__ attribute/property into a given node/relationship, we can fetch it and use it for casting (since it's typically a fully-qualified type name).  It might look something like this:

// n = Node object in question
String theType = (String)n.getProperty("__type__", "");

// we could then make the RHS of the assignment something like: (LHS) = template.convert(n, class<theType>;

But what about the LHS?  Without an "if/else" block, how can we treat the returned string theType as a first-class citizen that would declare the type for the LHS?  As far as I'm aware, there is no way to do this (of course there might be ways I've just not seen, but, I have a feeling they'd be just as expensive as the rest of the assignment).  Java is a strongly-typed language, and so I'm sure most of us would expect this outcome.

So we see that this "solution" isn't really much of one.

Solution 3

Somehow modify the query to work with a @MapResult-annotated interface to deal with the results (note: At least as of SDN 2.3.1, @MapResult has been deprecated in favour of @QueryResult.  I haven't done too much with @QueryResult so your mileage may vary).  This obviously requires more knowledge ahead of time of the types of paths, nodes and relationships you're planning on returning which may limit the kinds of heterogeneous queries you can execute.

So What Else Can Be Done?

I recently attended GraphConnect 2013 in New York City where I had a chance to meet up with Michael Hunger (a name which should require little or no introduction in the graph database/Spring Data continuum).  We had a great conversation about the very subject of this post.

His overall insights into Spring Data and its purpose, merits and detractors were very helpful, especially from a conceptual standpoint.

The number one point to take away--and perhaps it's quite obvious but it's worth reiterating--is this: Spring Data is not a magic bullet.  Given the differences in concepts here (i.e. a strongly-typed, object-oriented language and a graph-based, schema-free data store), there is bound to be limitations.

Spring Data's strong point is ease of integration.  A typical use case for SDN is likely to be one where relatively few nodes/relationships are needed to be returned.  SDN is not meant to necessarily "explore" graphs.

In order to truly resolve such differences, it would seem to me to make more sense to either layer SDN on top of another layer of abstraction, or even to go direct to the Neo4j API.

Perhaps an even better approach would be to use a Domain-Specific Language (DSL) such as Groovy or JRuby; something that is much more loosely-typed, flexible, and still able to be integrated into the Java stack.

(Shameless plug: Check out Pacer, a powerful, JRuby-based graph traversal engine.)

Summary/Conclusion

In this post, we have seen that exploring subgraphs and paths with SDN is not as straightforward as we'd perhaps like; however, it is clear that SDN was not built to accomplish such features (at least not yet).

Spring Data for Neo4j's strong suit is ease of integration.  As should be evident from this post and others, it is easy and straightforward to get SDN into existing/legacy Java applications, and to quickly stand-up Java-based applications that rely more on "end results" than "exploration" per se.

Ok, folks; as always, I definitely welcome comments,feedback, and questions.  If you can think of a better way to approach this kind of problem space or even if I have something wrong here, please do let me know and I'll be sure to make good use of such feedback.

Thanks for reading, and we'll see you on the next post!

Spring Data Neo4j 2.3.1.RELEASE and Neo4j 1.9.4 Upgrading

I'm back with a quick post (with more to come soon).

I was in the middle of upgrading my little test project to a newer version of Spring Data Neo4j and Neo4j itself when I came across a few little points that others might find useful (though it should be noted that Neo4j is set to release 2.0 very soon and is currently doing milestone releases).

I upgraded SDN to 2.3.1.RELEASE and Neo4j (all aspects of it, including Cypher) to 1.9.4.

Here are a couple "gotchas" I encountered:

Dependencies

It would seem that CGLIB has been moved out of one of the Neo4j or SDN dependencies; however, I also found that--with the SDN/Neo4j combination I'm using--that a specific version is required, namely 2.2.2.

Adding this bit into my POM fixed things up nicely:

<dependency>

    <groupId>cglib</groupId>

    <artifactId>cglib</artifactId>

    <version>2.2.2</version>

</dependency>

No bean named 'graphDatabaseService' is defined

This one was fun.  As confirmed in this Neo4j forum thread (which actually uses Neo4j 1.7 and SDN 2.1.0.Build-Snapshot), when configuring Neo4j in an application context, the bean ID for the graph database service (whether it's embedded or from a server) must be "graphDatabaseService", similar to this:

<bean id="graphDatabaseService"

class="org.springframework.data.neo4j.rest.SpringRestGraphDatabase">

<constructor-arg index="0" value="http://someserver:7474/db/data" />

</bean>

If this little nuance is overlooked, you could very well see exceptions when, say, starting up your application server with your SDN-based application.

In my case, Maven compiled my WAR file just fine, but, starting up Tomcat produced a slew of exceptions.

It would seem that this is an ongoing issue, though, perhaps it's a necessary change from the SDN folks.  We'll just have to see!

Hopefully some people find these tidbits useful.

We'll see you on the next post!

Spring Data Neo4j, @MapResult, Cypher, Casing and You!

A quick tip for those of you who are using Cypher with Spring Data Neo4j (SDN):

If you're using the @MapResult way in your Neo4j repositories, be careful of what you use in the corresponding @ResultColumn annotations.

For example, let's say you have the following repository definition (assume that you don't want to use the built-in findAll() method in this case; this example can be extended to other mapping results WLOG):

 
public interface MyRepository extends GraphRepository, RelationshipOperationsRepository {
 @Query("START n=node:__types__(className='com.yourorg.yourproject.entities.MyModel') RETURN COLLECT(n)")
 MyModelData getAllMyModels();
 
 @MapResult
 public interface MyModelData
 {
  @ResultColumn("COLLECT(n)")
  Iterable getMyModels(); 
 }
}

What you'd expect getAllMyModels() to do is to simply return all of those nodes that meet the Cypher criteria (note that the Cypher query above is very similar to what is generated by SDN in its findAll() method; the index referenced is, in fact, created and persisted by SDN).

However, if you call this code, you will get an error similar to the following:

"org.springframework.data.neo4j.support.conversion.NoSuchColumnFoundException: Expexted a column named COLLECT(n) to be in the result set."

You're probably scratching your head and asking yourself at this point, "But I am returning 'COLLECT(n)'!  It's right there in the Cypher query!"

And you're completely right--it is there!

However, try running that same query in the Neo4j web console (wherever your graph database is residing).

Dig through the results, and you'll see that the column returned isn't, in fact, "COLLECT(n)", but, "collect(n)".

Yep, you got it!  It's case sensitive!

So if you change

@ResultColumn("COLLECT(n)")

...to...

@ResultColumn("collect(n)")

...(note that casing of "collect") you'll be good as gold.

Remember that the next time you're diving deep into SDN.

And, as an update, I continue to work on the project I started back in June, and am finally making some headway.  I'm coming across some interesting stuff, and I hope to share more in the coming weeks.

We'll see you on the next post!

Persisting to Neo4j via Spring Data (or, "Aren't We Persistent?")

Hi gang!

Ok, I'm back with a new post, this time with a post about a couple quirks I ran into while implementing some test cases for Spring Data using Neo4j.  They're not bugs by any stretch; it's just new behaviour to get used to as you venture into the Spring Data world (which I'm loving, by the way).

During my copious amounts of downtime (that should be read while imagining me rolling my eyes so hard that I fall over backwards in my chair), I've been putting together a little playground for me to mess around with and play with Spring Data.

It's definitely evolving and changing as I change things up and try out new ideas, and I fully plan on sharing more about this in future posts.

For now, though, I'm just discussing a couple potential pitfalls newcomers to Spring Data might fall prey to (please pardon the prepositional phrase; I'm sure it won't be the last one).

Background
I've wanted to play with Spring Data a bit more seriously for some time now, so I started a few weeks ago and, I have to say, I'm loving every second of it.  (I'm already a huge Spring fan, and the annotations continue to make my life easier.)

My sandbox goes something like this: After having gone through the docs for Spring Data (especially "Good Relationships"), I thought I'd try out something similar for myself, borrowing the whole "store" concept (as it seems to me to be the best, first choice for implementing a graph database).

Instead of using the whole "movie store" concept, I switched to something a little different to avoid total code reuse (I do borrow some code from the link above but modify it an awful lot).

For any geeks around my age (or older), you will remember a certain computer software retailer called Babbage's.  I have fond memories of begging my parents to go into the store every time we passed one, which wasn't often (at least I don't think it was...).  GameStop Corporation went on to purchase Babbage's (and EB Games, and a bunch of other software retailers), so you're unlikely to see a Babbage's by that name.

With that short trip down memory lane finished (more like memory cul de sac), I decided to model my domain after the concept of a software retailer.  My store will cleverly enough be called Von Neumann's (any CS major and most geeks out there are currently groaning at that joke).

Domain Model
Currently, the domain model consists of the following:

Even looking at the UML diagram above, we can see that it's based on a graph model (can you pick out the entities and/or the relationship(s)?).

Test Cases' Setup
After setting up the relevant project (which I did as a Maven project), I set forth creating some tasks using JUnit.  Before creating the actual test cases, I needed to make sure I had my testing context setup.  I also needed away to ensure that any data being persisted was wiped clean after each run.

Fortunately, instead of having to create such functionality for my project, I learned that Neo4j already has a handy solution!  The ImpermanentGraphDatabase.  This little gem can be found in the Neo4j kernel.  Specifically, I added these lines to my POM (you can see the specific version I'm using, too):


<dependency>
<groupId>org.neo4j</groupId>
<artifactId>neo4j-kernel</artifactId>
<version>1.8.M03</version>
</dependency>

...and then adding the following line to my testing context:

<bean id="graphDBService" class="org.neo4j.test.ImpermanentGraphDatabase" destroy-method="shutdown"/>

And presto!  A suitable testing graph database for my test cases!

(Warning: I am using the latest version that I found worked best for me and is compatible with all my other dependencies.  ImpermanentGraphDatabase as available in earlier versions of Neo4j, as well.)

It should also be noted that I make use of both the Neo4j repositories interfaces AND the Neo4jOperations class for persisting and retrieval.

Another note is that I've made the entire test class @Transactional.

Test Cases Proper
I'll list two of them below and a couple of the quirks I noticed.

Ensuring a Customer Can Make a Purchase
This test case consists of creating a Customer object, a couple Game objects, and making sure that Purchases can be created, persisted and retrieved (along with the associated entities). 

 
 @Test
 public void customerCanMakePurchases()
 {
  // setup our game constants
  final int QTY = 1;
  final String GAME_TITLE = "Space Weasel 3.5";
  final String GAME_TITLE_2 = "The Space Testing Game";
  final String GAME_DESC = "Rodent fun in space!";
  final String GAME_DESC_2 = "Tests in space!";
  final int STOCK_QTY = 10;
  final float PRICE = 59.99f;
  
  // setup our customer constants
  final String FIRST_NAME = "Edgar";
  final String LAST_NAME = "Neubauer";
  
  // create our customer for this test
  Customer customer1 = new Customer();
  
  // set the customer's properties (NOTE: "firstName" is an indexed property in the Customer entity, but "lastName" is not!)
  customer1.setFirstName(FIRST_NAME);
  customer1.setLastName(LAST_NAME);

  // create our games for this test
  Stock game1 = new Game(GAME_TITLE, GAME_DESC, STOCK_QTY, PRICE);
  Stock game2 = new Game(GAME_TITLE_2, GAME_DESC_2, STOCK_QTY + 5, PRICE + 5);

First, do the setup.  (And, for the sake of brevity, I'm leaving out the annotated entities.)

Nothing strange going on here--just creating two games and a single customer.  It is worth noting (for later on) that "firstName" is an indexed property of the Customer entity/node.  This means that it is searchable (also recall that Neo4j's default indexing engine is Lucene).

It had to be done.

The games we've chosen are clearly AAA-title games.  These tests should be interesting.

  // save entities BEFORE saving the relationships!
  template.save(game1);
  template.save(game2);
  template.save(customer1);

  // make those purchases! Support our test economy!
  // (NOTE: "makePurchase" actually uses the "template" parameter to persist the relationship, so no need to do it again)
  Purchase p1 = customer1.makePurchase(template, game1, QTY);  
  Purchase p2 = customer1.makePurchase(template, game2, QTY);

Above, we make sure to persist the 2 games and single customer.  We also do this prior to persisting any relationships.  This is necessary.  In this case, I make use of an instance variable called "template" which is actually an instance of  Neo4jOperations.  This is one way of accessing the necessary persistence/retrieval functionality we need.

We then create 2 Purchase objects/relationships (Purchase is actually a relationship entity).  It is also worth noting that, instead of using the "template" object to persist the relationships, I've followed the Neo4j tutorial book "Good Relationships" and attempted another way of doing persistence, i.e. by passing the "template" object into the necessary method and having the method (in this case makePurchase) actually do the persisting of the newly-created Purchase.

Again, both "game1" and "game2" need to be persisted prior to persisting any relationships between them.

Still with me?

  // retrieve the customer
  Customer customer1Found = this.customerRepository.findByPropertyValue("firstName", FIRST_NAME);
  
  //
  // Tests
  //
  
  // can we find/retrieve the customer?
  assertNotNull("Unable to find customer.", customer1Found);
  
  // can we find the specific customer for which we are looking?
  assertEquals("Returned customer but not the one searched for.", FIRST_NAME, customer1Found.getFirstName());
  
  // does the retrieved customer have its non-indexed properties returned, as well?
  assertEquals("Returned customer doesn't have non-indexed properties returned.", LAST_NAME, customer1Found.getLastName());

  // retrieve the customer's purchases
  // (NOTE: We case as a Collection just to make checking the number of puchases easier)  
  Iterable purchasesIt = customer1Found.getPurchases();
  Collection purchases = IteratorUtil.asCollection(purchasesIt);
  
  // do we have the correct number of purchases?
  assertEquals("Number of purchases do not match.", 2, purchases.size());

So now we get to some actual testing.

The tests above are all straightforward.  We ensure the following:

1. We can retrieve a persisted node, specifically via an indexed property.
2. We can retrieve the correct persisted node for which we are searching.
3. We can view non-indexed properties from the retrieved node.
4. We can retrieve the correct number of relationships of the retrieved node.

As noted in Section 9.3 of "Good Relationships", we use Iterable for those node properties that are collections and are to be left as read-only, and Collection or Set for those collections that can be modified.

  // go through the actual purchases...
  Iterator purchIt = purchasesIt.iterator();
  Purchase purchase1 = purchIt.next();
  
  // retrieving objects via Spring Data pulls lazily by default; for eager mapping, use @Fetch (but be forewarned!)
  // ...this means we have to use the fetch() method to finish loading related objects
  Stock s1 = template.fetch(purchase1.getItem());

What if we want to view a node's related nodes' data?

By default, Spring Data loads an entity's relationships lazily, which makes perfect sense (just picture how much memory would be needed if you had a very large, highly connected graph).  Also remember that there are implicit relationships between entities if an entity is contained as a property of another entity.

(Courtesy of Paramount Picture's Forrest Gump)
"Mama said eager loading is like a box of chocolates: You never know what you're gonna get."
Well, at least the chocolates had an easily-determined, finite number in the box...

It is possible to have an eager retrieval by using the @Fetch annotation (be warned, though, that it will currently only work, by default, on node entities and collections of relationships that are based on Collection, Set, or Iterable; Spring Data may expand that in later releases, but I believe you can extend the mappings to work with other classes, if you so desire).

So, with our lazily-loaded relationships, we can use "template"'s fetch method to finish loading in the missing data.  It's as simple as that!  Anyone familiar with ORM will get this immediately.

  // can we retrieve our first purchase successfully w/ its details?
  assertEquals("Purchased item not persisted properly.", GAME_TITLE, s1.getTitle());

  purchase1 = purchIt.next();  
  Stock s2 = template.fetch(purchase1.getItem());
  
  // can we retrieve our second purchase successfully w/ its details?
  assertEquals("Purchased item not persisted properly.", GAME_TITLE_2, s2.getTitle());
  
  // if we're here, then all test ran succesfully.  Hooray!
 }

Above, we run a couple more tests to ensure that we can, in fact, retrieve and view lazily-loaded objects from Neo4j.

Nothing to it!

Making Friends the Easy Way: By Creating Them!
For these tests, we're going to have a look at something a bit more social, i.e. customers befriending other customers (how Utopian!).  I suppose we could make them "rivals" or "enemies", but that's a bit too sinister for this blog (for now...).

Anyway, I have prior to this test method a setup method (annotated with the @Before JUnit annotation) that creates 5 customers (if you're interested, I persist them using a CustomerRespoitory I created by extending the GraphRepository and RelationshipOperationsRepository interfaces).

 @Test
 public void customerFriends()
 {
  // add friends
  c1.addFriend(c2);
  c1.addFriend(c3);
  c1.addFriend(c4);
  c1.addFriend(c5);

  // be careful! setting a "Direction.BOTH" relationship in one node entity will have the ENTIRE relationship saved (*including the adjoining node*) when saving just ONE of the two entities!
  // ...if you save both, Neo4j will remove the duplication (and you'll be left wondering why c1 is a friend of c2, but not vice versa)
  
  // save c1's friends
  customerRepository.save(c1);

In the code above, we have the customer "c1" make friends with the other customers (he's a social butterfly).

Now, perhaps the most important part of this whole blog is shown here (and below).  It has to do with relationships, specifically those that are annotated as being "Direction.BOTH".

As you can see from the comments in the code above, we need to be careful about how we create relationships between nodes and save them.  If we were to create the relationship between, say "c1" and "c2", and then persist each node (and therefore the relationships, which the customer repository will handle), we would notice that the relationships have gone awry, and that the duplicate relationship from "c2" has been removed.

So, what we're going to do is the following (keeping in mind that "c1" and "c2" have already been persisted in the setup method):

1. Persist "c1" (and thereby its friendship to "c2").
2. Retrieve "c2".
3. Add any other friends' relationships to the retrieved "c2" (while not befriending back to "c1").
4. Persist "c2" (and thereby its friendships to those added in Step 3).

Step 1 is done above.

  // we can't just continue to add friends to this.c2, as once we try to save this.c2, it'll remove the duplicate relationship between c1 and c2.
  // ...so, to get around this, we retrieve the persisted object from the DB
  Customer c2Found = customerRepository.findByPropertyValue("lastName", C2_LNAME);
  c2Found.addFriend(c3);
  c2Found.addFriend(c4);
  c2Found.addFriend(c5);

  // save c2's friends, which will preserve the existing relationship with c1! Old friends can remain friends!
  customerRepository.save(c2Found);

As you can see above, we finish the remaining steps (2 through 4).

Again, note that we DO NOT create a reciprocal relationship from "c2" to "c1".  (One would hope a friendship relationship would be reciprocal; unless you have stalkers or something...)

This would totally help.

All that's left now is to run some tests to ensure that our friends have remained friends throughout all this persisting!

  // retrieve c1 for some tests
  Customer c1Found = customerRepository.findByPropertyValue("lastName", C1_LNAME);
  
  Iterable c1Friends = c1Found.getFriends();
  Collection c1FriendsSet = IteratorUtil.asCollection(c1Friends);
  Iterator custIt = c1Friends.iterator();
  
  int numFriends = 0;
  
  // let's make sure all of c1's friends were retrieved
  assertTrue("Friend not found.", c1FriendsSet.containsAll(IteratorUtil.asCollection(c1.getFriends())));
  
  // let's also make sure that c1 and c2 are still buds specifically (these two are inseparable...you should see them at ComicCon!)
  assertTrue("Friend not found.", c1FriendsSet.contains(c2));
  
  // let's make sure the exact number of friends returned is correct 
  while (custIt.hasNext())
  {   
   custIt.next();
   numFriends++;
  } // while
  
  assertEquals("Number of friends returned incorrect.", 4, numFriends);

  // if we're here, all is well! Huzzah!
}

Above, as in the first test, we make sure that all of the friendships have been properly preserved, both from "c1"'s and "c2"'s perspective.

Conclusion
In this post, we have seen the basics of persisting with Spring Data and a couple of the quirks I ran into.  These are documented within the Spring Data documentation, but it never hurts to bring these little nuances out into the light even further.

We also saw that the ImpermanentGraphDatabase is available to us through the Neo4j kernel which is a wonderful tool for implementing test cases with quick setup and teardown--no needing to write initializers and cleaners for a Neo4j installation!

So there we have it!  A first pass through persisting with Spring Data and implementing some unit tests using Neo4j and JUnit.

If anyone has any questions or I've made a mistake, please feel free to leave feedback.

We'll see you on the next post!