So its not obvious from the javadocs on how to modify properties of a Vertex after adding into graph.
I tried TinkerPop way.
GraphTraversalSource g = DseGraph.traversal(dseSession);
g.V().toStream().forEach(vertex -> vertex.property("name", "Santosh"));
But I get an exception
Exception in thread "main" java.lang.IllegalStateException: Property addition is not supported
at org.apache.tinkerpop.gremlin.structure.Element$Exceptions.propertyAdditionNotSupported(Element.java:133)
at org.apache.tinkerpop.gremlin.structure.util.detached.DetachedVertex.property(DetachedVertex.java:91)
at com.trimble.tpaas.profilex.random.MainGraphConnectivity.lambda$testSchemaCreation$0(MainGraphConnectivity.java:41)
at org.apache.tinkerpop.gremlin.process.traversal.Traversal.forEachRemaining(Traversal.java:250)
at java.util.Spliterators$IteratorSpliterator.forEachRemaining(Spliterators.java:1801)
at java.util.stream.ReferencePipeline$Head.forEach(ReferencePipeline.java:580)
at com.trimble.tpaas.profilex.random.MainGraphConnectivity.testSchemaCreation(MainGraphConnectivity.java:41)
at com.trimble.tpaas.profilex.random.MainGraphConnectivity.main(MainGraphConnectivity.java:23)
So question where can I refer to understand how to modify an existing vertex property using DSE java driver or otherwise.
When you connect to a DSE Graph with the DataStax Java Driver:
g = DseGraph.traversal(dseSession)
or the TinkerPop Driver for that matter:
graph = EmptyGraph.instance()
g = graph.traversal().withRemote('conf/remote-graph.properties')
the results you receive are disconnected from the database. In TinkerPop we call that state "detached". So vertices returned from g.V() are in a "detached" state and you can't directly interact with them as though they are backed by the database for storing their properties.
All database mutations should occur through the Traversal API (i.e. Gremlin). So, if you want to add a property to all vertices in your graph, you might do:
g.V().property('name','Santosh').iterate()
Related
When running Neo4j embedded, the default configuration doesn't have the automatic node index set as fulltext (meaning that all Lucene queries are case sensitive). How can I configure the automatic index to be fulltext?
For starters, you must perform this on a new database. The automatic index is lazily created, which means that it isn't created until the first access. You have until the first access to perform this configuration. If you attempt to change the property after it's already been created, it won't work. So the first step is to load the database with automatic indexing enabled (node or relationship).
val db = new GraphDatabaseFactory().newEmbedddedDatabaseBuilder("path/to/db").
setConfig(GraphDatabaseSettings.node_keys_indexable, "label,username").
setConfig(GraphDatabaseSettings.node_auto_indexing, "true").newGraphDatabase()
Now, before you do anything, you have to set the configuration properties. You can find out about the possible properties and values here. To do this, we just need two more lines.
val autoIndex = db.index.forNodes("node_auto_index")
db.index.setConfiguration(autoIndex, "type", "fulltext")
And that's all there is to it. You can now create vertices and relationships and the automatic index will be created and populated. You can get use the following code to query it using any Lucene query.
autoIndex.getAutoIndex.query("label:*caseinsensitive*")
I'm using neo4j 1.8.2 and am trying to retrieve all nodes from a graph, but I am getting UnsupportedOperationException.
GraphDatabaseService db = GraphDatabaseFactory.databaseFor("http://localhost:7474/db/data/");
Iterable<Node> nodes = GlobalGraphOperations.at(db).getAllNodes();
I found it in the API documentation, so I can't understand, what am I doing wrong.
Where did you find it?
The REST Graph Database doesn't support this operation (or at least not if called from GlobalGraphOperations
The db.getAllNodes() is implemented using a remote cypher query which is what you should do as well.
new RestCypherQueryEngine(restGraphDb.getRestAPI()).query(....)
or
restGraphDB.query()
It seems you can't do this with a remote database. Check the source, it frequently throws UnsupportedOperationExceptions. Maybe an embedded database is an option for you?
I have a legacy dataset (ENRON data represented as GraphML) that I would like to query. In an comment in a related question, #StefanArmbruster suggests that I use Cypher to query the database. My query use case is simple: given a message id (a property of the Message node), retrieve the node that has that id, and also retrieve the sender and recipient nodes of that message.
It seems that to do this in Cypher, I first have to create an index of the nodes. Is there a way to do this automatically when the data is loaded from the graphML file? (I had used Gremlin to load the data and create the database.)
I also have an external Lucene index of the data (I need it for other purposes). Does it make sense to have two indexes? I could, for example, index the Neo4J node ids into my external index, and then query the graph based on those ids. My concern is about the persistence of these ids. (By analogy, Lucene document ids should not be treated as persistent.)
So, should I:
Index the Neo4j graph internally to query on message ids using Cypher? (If so, what is the best way to do that: regenerate the database with some suitable incantation to get the index built? Build the index on the already-existing db?)
Store Neo4j node ids in my external Lucene index and retrieve nodes via these stored ids?
UPDATE
I have been trying to get auto-indexing to work with Gremlin and an embedded server, but with no luck. In the documentation it says
The underlying database is auto-indexed, see Section 14.12, “Automatic Indexing” so the script can return the imported node by index lookup.
But when I examine the graph after loading a new database, no indexes seem to exist.
The Neo4j documentation on auto indexing says that a bunch of configuration is required. In addition to setting node_auto_indexing = true, you have to configure it
To actually auto index something, you have to set which properties
should get indexed. You do this by listing the property keys to index
on. In the configuration file, use the node_keys_indexable and
relationship_keys_indexable configuration keys. When using embedded
mode, use the GraphDatabaseSettings.node_keys_indexable and
GraphDatabaseSettings.relationship_keys_indexable configuration keys.
In all cases, the value should be a comma separated list of property
keys to index on.
So is Gremlin supposed to set the GraphDatabaseSettings parameters? I tried passing in a map into the Neo4jGraph constructor like this:
Map<String,String> config = [
'node_auto_indexing':'true',
'node_keys_indexable': 'emailID'
]
Neo4jGraph g = new Neo4jGraph(graphDB, config);
g.loadGraphML("../databases/data.graphml");
but that had no apparent effect on index creation.
UPDATE 2
Rather than configuring the database through Gremlin, I used the examples given in the Neo4j documentation so that my database creation was like this (in Groovy):
protected Neo4jGraph getGraph(String graphDBname, String databaseName) {
boolean populateDB = !new File(graphDBName).exists();
if(populateDB)
println "creating database";
else
println "opening database";
GraphDatabaseService graphDB = new GraphDatabaseFactory().
newEmbeddedDatabaseBuilder( graphDBName ).
setConfig( GraphDatabaseSettings.node_keys_indexable, "emailID" ).
setConfig( GraphDatabaseSettings.node_auto_indexing, "true" ).
setConfig( GraphDatabaseSettings.dump_configuration, "true").
newGraphDatabase();
Neo4jGraph g = new Neo4jGraph(graphDB);
if (populateDB) {
println "Populating graph"
g.loadGraphML(databaseName);
}
return g;
}
and my retrieval was done like this:
ReadableIndex<Node> autoNodeIndex = graph.rawGraph.index()
.getNodeAutoIndexer()
.getAutoIndex();
def node = autoNodeIndex.get( "emailID", "<2614099.1075839927264.JavaMail.evans#thyme>" ).getSingle();
And this seemed to work. Note, however, that the getIndices() call on the Neo4jGraph object still returned an empty list. So the upshot is that I can exercise the Neo4j API correctly, but the Gremlin wrapper seems to be unable to reflect the indexing state. The expression g.idx('node_auto_index') (documented in Gremlin Methods) returns null.
the auto indexes are created lazily. That is - when you have enabled the auto-indexing, the actual index is first created when you index your first property. Make sure you are inserting data before checking the existence of the index, otherwise it might not show up.
For some auto-indexing code (using programmatic configuration), see e.g. https://github.com/neo4j-contrib/rabbithole/blob/master/src/test/java/org/neo4j/community/console/IndexTest.java (this is working with Neo4j 1.8
/peter
Have you tried the automatic index feature? It's basically the use case you're looking for--unfortunately it needs to be enabled before you import the data. (Otherwise you have to remove/add the properties to reindex them.)
http://docs.neo4j.org/chunked/milestone/auto-indexing.html
I am using Gremlin and Neo4j to manipulate the ENRON dataset from infochimps. This dataset has two types of vertexes, Message and Email Addresss and two types of edges, SENT and RECEVIED_BY. I would like to create a custom index on this dataset that creates a Lucene document for each vertex of type: 'Message' and incorporates information from associated vertexes (e.g., v.in(), v.out()) as additional fields in the Lucene document.
I am thinking of code along the lines of
g = new Neo4jGraph('enron');
PerFieldAnalyzerWrapper analyzer =
new PerFieldAnalyzerWrapper(new StandardAnalyzer());
analyzer.addAnalyzer("sender", new KeywordAnalyzer());
analyzer.addAnalyzer("recipient", new KeywordAnalyzer());
IndexWriter idx = new IndexWriter (dir,analyzer,IndexWriter.MaxFieldLength.UNLIMITED);
g.V.filter{it.type == 'Message'}.each { v ->
Document doc = new Document();
doc.add(new Field("subject", v.subject));
doc.add(new Field("body", v.body));
doc.add(new Field("sender", v.in().address);
v.out().each { recipient ->
doc.add(new Field("recipient", recipient.address));
}
idx.addDocument(doc);
}
idx.close();
My questions are:
Is there a better way to enumerate vertexes for indexing?
Can I use auto-indexing for this, and if so, how to I specify what should be indexed?
Can I specify my own Analyzer, or am I stuck with the default? What is the default?
If I must create my own index, should I be using gremlin for this, or am I better off with a Java program?
I will be talking about direct Neo4j access here since I'm not well travelled in Gremlin.
So you'd like to build a Lucene index "outside of" the graph itself? Otherwise you can use the built in graphDb.index().forNodes( "myIndex", configForMyIndex ) to get (created on demand) a Lucene index associated with neo4j. You can then add multiple fields to each document by calling index.add( node, key, value ), where each node will be represented by one document in that Lucene index.
1) In Gremiln... I don't know
2) See http://docs.neo4j.org/chunked/milestone/auto-indexing.html
3) See http://docs.neo4j.org/chunked/milestone/indexing-create-advanced.html
4) Do you need to create it outside of the db entirely? If so, why?
I just finished an import with a Java process and it's really easy, in my opinion better inclusive through Gremlin.
Anyway, if the process is failing is because of you CAN'T create a new object of StandardAnalyzer. All the constructors of that class require parameters, so you should create a wrapper class or create it with the right version of Lucene like paramater in the constructor.
Neo4J, until today, accepts only until the lucene version 36.
I don't understand this paradigm I guess?
For a small single server or development environment... I hate having to load 100's of thousands of records just to analyze it in a graph... am I missing the big picture here?
UPDATE (3/21/2012 10:38a):
My current setup:
Default Install
Default Configs
Server Setup
Creating nodes via REST API
How do you instantiate your database, embedded or server? Are you running ImpermanentGraphDatabase, because that's the in-memory test database. If you use the normal EmbeddedGraphDatabase your graph is persisted trasactionally along the way when you insert your data.
Please give a little more information.
If using Java embedded transactions must be closed when saving objects or they might get lost. In earlier versions this was done by calling finally { tx.finish(); }, later versions (2.1+) it should happen automatically when instantiated within the try-with-resource. (This makes it possible to run into problems if the Transaction tx is instantiated outside the try clause).
GraphDatabaseService graphDb = new GraphDatabaseFactory().newEmbeddedDatabase(DB_PATH);
try (Transaction tx = graphDb.beginTx()) {
// create some nodes here
}