34.7. Traversal

For reading about traversals, see Chapter 35, The Traversal Framework.

For more examples of traversals, see Chapter 5, Data Modeling Examples.

The Matrix

This is the first graph we want to traverse into:

Figure 34.2. Matrix node space view

[Tip]Tip

The source code of this example is found here: NewMatrix.java

Friends and friends of friends. 

private Traverser getFriends(
        final Node person )
{
    TraversalDescription td = graphDb.traversalDescription()
            .breadthFirst()
            .relationships( RelTypes.KNOWS, Direction.OUTGOING )
            .evaluator( Evaluators.excludeStartPosition() );
    return td.traverse( person );
}

Let’s perform the actual traversal and print the results:

int numberOfFriends = 0;
String output = neoNode.getProperty( "name" ) + "'s friends:\n";
Traverser friendsTraverser = getFriends( neoNode );
for ( Path friendPath : friendsTraverser )
{
    output += "At depth " + friendPath.length() + " => "
              + friendPath.endNode()
                      .getProperty( "name" ) + "\n";
    numberOfFriends++;
}
output += "Number of friends found: " + numberOfFriends + "\n";

Which will give us the following output:

Thomas Anderson's friends:
At depth 1 => Morpheus
At depth 1 => Trinity
At depth 2 => Cypher
At depth 3 => Agent Smith
Number of friends found: 4

Who coded the Matrix? 

private Traverser findHackers( final Node startNode )
{
    TraversalDescription td = graphDb.traversalDescription()
            .breadthFirst()
            .relationships( RelTypes.CODED_BY, Direction.OUTGOING )
            .relationships( RelTypes.KNOWS, Direction.OUTGOING )
            .evaluator(
                    Evaluators.includeWhereLastRelationshipTypeIs( RelTypes.CODED_BY ) );
    return td.traverse( startNode );
}

Print out the result:

String output = "Hackers:\n";
int numberOfHackers = 0;
Traverser traverser = findHackers( getNeoNode() );
for ( Path hackerPath : traverser )
{
    output += "At depth " + hackerPath.length() + " => "
              + hackerPath.endNode()
                      .getProperty( "name" ) + "\n";
    numberOfHackers++;
}
output += "Number of hackers found: " + numberOfHackers + "\n";

Now we know who coded the Matrix:

Hackers:
At depth 4 => The Architect
Number of hackers found: 1

Walking an ordered path

This example shows how to use a path context holding a representation of a path.

[Tip]Tip

The source code of this example is found here: OrderedPath.java

Create a toy graph. 

Node A = db.createNode();
Node B = db.createNode();
Node C = db.createNode();
Node D = db.createNode();

A.createRelationshipTo( C, REL2 );
C.createRelationshipTo( D, REL3 );
A.createRelationshipTo( B, REL1 );
B.createRelationshipTo( C, REL2 );

Now, the order of relationships (REL1REL2REL3) is stored in an ArrayList. Upon traversal, the Evaluator can check against it to ensure that only paths are included and returned that have the predefined order of relationships:

Define how to walk the path. 

final ArrayList<RelationshipType> orderedPathContext = new ArrayList<RelationshipType>();
orderedPathContext.add( REL1 );
orderedPathContext.add( withName( "REL2" ) );
orderedPathContext.add( withName( "REL3" ) );
TraversalDescription td = db.traversalDescription()
        .evaluator( new Evaluator()
        {
            @Override
            public Evaluation evaluate( final Path path )
            {
                if ( path.length() == 0 )
                {
                    return Evaluation.EXCLUDE_AND_CONTINUE;
                }
                RelationshipType expectedType = orderedPathContext.get( path.length() - 1 );
                boolean isExpectedType = path.lastRelationship()
                        .isType( expectedType );
                boolean included = path.length() == orderedPathContext.size() && isExpectedType;
                boolean continued = path.length() < orderedPathContext.size() && isExpectedType;
                return Evaluation.of( included, continued );
            }
        } )
        .uniqueness( Uniqueness.NODE_PATH );

Note that we set the uniqueness to Uniqueness.NODE_PATH as we want to be able to revisit the same node dureing the traversal, but not the same path.

Perform the traversal and print the result. 

Traverser traverser = td.traverse( A );
PathPrinter pathPrinter = new PathPrinter( "name" );
for ( Path path : traverser )
{
    output += Paths.pathToString( path, pathPrinter );
}

Which will output:

(A)--[REL1]-->(B)--[REL2]-->(C)--[REL3]-->(D)

In this case we use a custom class to format the path output. This is how it’s done:

static class PathPrinter implements Paths.PathDescriptor<Path>
{
    private final String nodePropertyKey;

    public PathPrinter( String nodePropertyKey )
    {
        this.nodePropertyKey = nodePropertyKey;
    }

    @Override
    public String nodeRepresentation( Path path, Node node )
    {
        return "(" + node.getProperty( nodePropertyKey, "" ) + ")";
    }

    @Override
    public String relationshipRepresentation( Path path, Node from, Relationship relationship )
    {
        String prefix = "--", suffix = "--";
        if ( from.equals( relationship.getEndNode() ) )
        {
            prefix = "<--";
        }
        else
        {
            suffix = "-->";
        }
        return prefix + "[" + relationship.getType().name() + "]" + suffix;
    }
}

Uniqueness of Paths in traversals

This example is demonstrating the use of node uniqueness. Below an imaginary domain graph with Principals that own pets that are descendant to other pets.

Figure 34.3. Descendants Example Graph

In order to return all descendants of Pet0 which have the relation owns to Principal1 (Pet1 and Pet3), the Uniqueness of the traversal needs to be set to NODE_PATH rather than the default NODE_GLOBAL so that nodes can be traversed more that once, and paths that have different nodes but can have some nodes in common (like the start and end node) can be returned.

final Node target = data.get().get( "Principal1" );
TraversalDescription td = db.traversalDescription()
        .uniqueness( Uniqueness.NODE_PATH )
        .evaluator( new Evaluator()
{
    @Override
    public Evaluation evaluate( Path path )
    {
        boolean endNodeIsTarget = path.endNode().equals( target );
        return Evaluation.of( endNodeIsTarget, !endNodeIsTarget );
    }
} );

Traverser results = td.traverse( start );

This will return the following paths:

(2)--[descendant,2]-->(3)<--[owns,5]--(4)
(2)--[descendant,0]-->(0)<--[owns,3]--(4)

In the default path.toString() implementation, (1)--[knows,2]-->(4) denotes a node with ID=1 having a relationship with ID 2 or type knows to a node with ID-4.

Let’s create a new TraversalDescription from the old one, having NODE_GLOBAL uniqueness to see the difference.

[Tip]Tip

The TraversalDescription object is immutable, so we have to use the new instance returned with the new uniqueness setting.

TraversalDescription nodeGlobalTd = td.uniqueness( Uniqueness.NODE_GLOBAL );
results = nodeGlobalTd.traverse( start );

Now only one path is returned:

(2)--[descendant,2]-->(3)<--[owns,5]--(4)

Social network

[Note]Note

The following example uses the new enhanced traversal API.

Social networks (know as social graphs out on the web) are natural to model with a graph. This example shows a very simple social model that connects friends and keeps track of status updates.

[Tip]Tip

The source code of the example is found here: socnet

Simple social model

Figure 34.4. Social network data model

The data model for a social network is pretty simple: Persons with names and StatusUpdates with timestamped text. These entities are then connected by specific relationships.

  • Person

    • friend: relates two distinct Person instances (no self-reference)
    • status: connects to the most recent StatusUpdate
  • StatusUpdate

    • next: points to the next StatusUpdate in the chain, which was posted before the current one

Status graph instance

The StatusUpdate list for a Person is a linked list. The head of the list (the most recent status) is found by following status. Each subsequent StatusUpdate is connected by next.

Here’s an example where Andreas Kollegger micro-blogged his way to work in the morning:

To read the status updates, we can create a traversal, like so:

TraversalDescription traversal = graphDb().traversalDescription()
        .depthFirst()
        .relationships( NEXT );

This gives us a traverser that will start at one StatusUpdate, and will follow the chain of updates until they run out. Traversers are lazy loading, so it’s performant even when dealing with thousands of statuses — they are not loaded until we actually consume them.

Activity stream

Once we have friends, and they have status messages, we might want to read our friends status' messages, in reverse time order — latest first. To do this, we go through these steps:

  1. Gather all friend’s status update iterators in a list — latest date first.
  2. Sort the list.
  3. Return the first item in the list.
  4. If the first iterator is exhausted, remove it from the list. Otherwise, get the next item in that iterator.
  5. Go to step 2 until there are no iterators left in the list.

Animated, the sequence looks like this.

The code looks like:

PositionedIterator<StatusUpdate> first = statuses.get(0);
StatusUpdate returnVal = first.current();

if ( !first.hasNext() )
{
    statuses.remove( 0 );
}
else
{
    first.next();
    sort();
}

return returnVal;