I have a graph like this
V('Producer')-E('RESPONSIBLE_PRODUCER)->V('Event')<-E('INSPECTED')-V('Engineer')
V('Event')<-E('ALIGNED_PRODUCER')-V('Producer')
That is, each 'Event' vertex has two incoming edges: one that terminates at an 'Engineer' vertex and another that terminates at a 'Producer' vertex. But the function of the Producer vertices are different depend on the edge label.
I want to get the originating Producer, the Event, Engineer and terminating Producer.
I have this gremlin code:
g.V().hasLabel('Producer').
as('responsible').
has('ProdId', 1234567).
out("RESPONSIBLE_PRODUCER").hasLabel('Event').as('event').
in("INSPECTED").hasLabel('Engineer').as('engineer').
select('responsible', 'event', 'engineer').
by(valueMap('name')).by(valueMap('name')).by(valueMap('name'))
That is, I chose a given Producer and get the Event and Engineer then return some details about each of those vertices.
I also want the Producer aligned to the Event in the same query but am not sure how to do this.
Any help is greatly appreciated.
You are looking for project:
g.V().has('Producer', 'ProdId', '1').as('r').
out("RESPONSIBLE_PRODUCER").hasLabel('Event').
project('responsible', 'event', 'engineer', 'aligned').
by(select('r').values('name')).
by(values('name')).
by(in('INSPECTED').values('name')).
by(in('ALIGNED_PRODUCER').values('name'))
You can see a "live" example of your problem here
Related
I am trying to retrieve all the node and properties details in parent-child hierarchy.
Nested within each other.
Since I am new with gremlin, graphDB I am having really tough time to get it done.
Please suggest a solution and if you could walk me through it, it will be great.
Following is my structure
And I am trying to keep the response as clean as possible.
I am using cosmosDB and Gremlin.
NET api for this.
I tried the following but it gave me response in key value,
g.V("some_id").repeat(out()).emit().tree().path()
g.V("some_id").emit().repeat(both().simplePath()).dedup()
please any kind of suggestion would be great.
I"m not sure what format you want your result, but use of path(), tree() or subgraph() would typically give you the graph structure. Since you are using CosmosDB, you're only options are path() and tree() as subgraph() does not appear to be supported.
Using this sample graph as a simple tree:
g.addV().property(id, '1').as('1').
addV().property(id, '2a').as('2a').
addV().property(id, '2b').as('2b').
addV().property(id, '3a').as('3a').
addV().property(id, '4a').as('4a').
addE('child').from('1').to('2a').
addE('child').from('1').to('2b').
addE('child').from('2a').to('3a').
addE('child').from('3a').to('4a')
you can see the effect of path() which basically gathers the contents of each step Gremlin took:
gremlin> g.V('1').repeat(out()).emit().path()
==>[v[1],v[2a]]
==>[v[1],v[2b]]
==>[v[1],v[2a],v[3a]]
==>[v[1],v[2a],v[3a],v[4a]]
Since I used out() we don't see the edges, but that is easily remedied by adding making a small adjustment to directly consume edges into the path history:
gremlin> g.V('1').repeat(outE().inV()).emit().path()
==>[v[1],e[0][1-child->2a],v[2a]]
==>[v[1],e[1][1-child->2b],v[2b]]
==>[v[1],e[0][1-child->2a],v[2a],e[2][2a-child->3a],v[3a]]
==>[v[1],e[0][1-child->2a],v[2a],e[2][2a-child->3a],v[3a],e[3][3a-child->4a],v[4a]]
Taken together with duplication removed on your application side you have a complete graph with path().
Replacing path() with tree() will essentially do that deduplication by maintaining the tree structure of the path history:
gremlin> g.V('1').repeat(out()).emit().tree()
==>[v[1]:[v[2b]:[],v[2a]:[v[3a]:[v[4a]:[]]]]]
gremlin> g.V('1').repeat(outE().inV()).emit().tree()
==>[v[1]:[e[0][1-child->2a]:[v[2a]:[e[2][2a-child->3a]:[v[3a]:[e[3][3a-child->4a]:[v[4a]:[]]]]]],e[1][1-child->2b]:[v[2b]:[]]]]
The Tree is just represented as a Map where each key represents a like a root and value is another Tree (i.e. the branches from it). It is perhaps better visualized this way:
gremlin> g.V('1').repeat(out()).emit().tree().unfold()
==>v[1]={v[2b]={}, v[2a]={v[3a]={v[4a]={}}}}
gremlin> g.V('1').repeat(out()).emit().tree().unfold().next().value
==>v[2b]={}
==>v[2a]={v[3a]={v[4a]={}}}
If neither of these structures are suitable and subgraph() is not available you can technically just capture and return the edges you traverse as the low level elements of your subgraph as described in this blog post.
Given the comments on this answer I also present the following option which used group():
gremlin> g.V('1').emit().
......1> repeat(outE().group('a').by(outV()).by(inV().fold()).inV()).cap('a').unfold()
==>v[1]=[v[2a], v[2b]]
==>v[3a]=[v[4a]]
==>v[2a]=[v[3a]]
It's not exactly a "tree" but if you know the root (in this case v[1]) you can find its key in the Map. The values are the children. You can then look up each of those keys in the Map to find if they have children and so on. For example, we can lookup v[2b] and find that it has no children while looking up [v2a] reveals a single child of [v3a]. Gremlin can be pretty flexible in getting answers if you can be sorta flexible in how you deal with the results.
I am creating a vertex with multiple edges but need a bit of help writing a query to retrieve the data.
Creation query
g.addV("referral")
.as("r")
.property("createdAt", Date.now())
.addE("prospect")
.from_("r")
.to(__.V(user.id))
.addE("opportunity")
.from_("r")
.to(__.V(second_user.id))
.addE("referredBy")
.from_("r")
.to(__.V(business.id))
.select("r")
.next()
I want to run a query that gets data from the first and second user. So far I have
g.V(business.id) //business
.in_("opportunity")
.as("referral")
.outV("referredBy")
.as("referrer")
.inV("prospect")
.as("prospect")
.select("referral", "referrer", "prospect")
.toList()
.next()
I'm getting an error when running this query. I basically want an array of a referral, referrer and prospect in one object that I can iterate through. Also any help on making my initial query better would be helpful.
Please let me know if this makes sense or if you need any other info. Any help would be appreciated.
The errors are because you are using outV when you should be using out. You only need to use inV and outV after outE and inE. So your query should be
g.V(business.id) //business
.in("opportunity")
.as("referral")
.out("referredBy")
.as("referrer")
.in("prospect")
.as("prospect")
.select("referral", "referrer", "prospect")
.toList()
Also you don't need next as you already have toList.
Lastly rather than use as and select I would look at the path step instead.
g.V(business.id) //business
.in("opportunity")
.out("referredBy")
.in("prospect")
.path()
.toList()
Using the gremlin console connected remotely to a Neptune DB instance, I am grabbing all edges with a specific label and want to sort them by the id of the out vertex. I'm getting this error: "code":"UnsupportedOperationException","detailedMessage":"com.amazon.neptune.storage.volcano.ast.CutoffNode cannot be cast to com.amazon.neptune.storage.volcano.ast.AbstractGroupNode".
Sample data:
g.addV('user').property(id,'1').
addV('content').property(id,'2').
addE('history').property('val',9).from(g.V('1')).to(g.V('2'))
Queries and outputs:
g.E().hasLabel('history').order().by('val')
==>e[3][1-history>2]
g.E().hasLabel('history').outV().id()
==>1
g.E().hasLabel('history').order().by(outV().id())
{"requestId":<stuff>,"code":"UnsupportedOperationException","detailedMessage":
"com.amazon.neptune.storage.volcano.ast.CutoffNode cannot be cast to
com.amazon.neptune.storage.volcano.ast.AbstractGroupNode"}
I expect the result of that last one to be the same as the first. I've tried the same traversal in a TinkerGraph and didn't get an error, so judging by that and the message it's specifically a Neptune problem. Googling hasn't brought up anything.
Is there a traversal that will do what I'm looking for? What am I doing wrong?
I will look into why the error is being thrown but in the near term I think this workaround should work. Please let me know if it does not.
g.E().order().by(identity().outV().id())
Cheers,
Kelvin
I have this code which essentially updates properties, removes all old IsOfType edges and adds new IsOfType edges (if I remove all the method/class abstraction and make it inline):
traversal = g.V("Entity:633471488:519").as("entity");
//update properties
traversal.property("text", "new text");
traversal.property("description", "new description");
//drop typeEdges
traversal.select("entity").outE("IsOfType").drop();
//even that causes the same issue(!): traversal.select("entity").outE("HasInner").drop();
System.out.println("traversal after type edges deletion: " +traversal);
//make new typeEdges
traversal.V("Entity:996942848:518").as("type-0").addE("IsOfType").from("entity").to("type-0");
System.out.println("traversal after type edges addition: " +traversal);
//storage
traversal.select("entity").forEachRemaining({})
Everything works (even the drop of existing IsOfType edges). But the creation of the new IsOfType edges doesn't seem to be resulting in new edges on the graph. If I comment out the drop, then creation works fine (!) It is as if the DropStep which is before the addEdgeStep is happening at the end. I even tried to drop other type of edge and it is causing the same issue (!). It might be that implicit transaction handling is deciding to commit when a drop() happens as it is with next(), iterate() and forEachRemaining() ?? If that is the case then drops and creations can't happen within the same transaction using Fluent API which renders it not very useful for real applications :(
Here is the state of the traversals after the deletion and after the additon of two IsOfType edges in my run (I tried both Java and Datastax Studio Console):
traversal after type edges deletion:
[
GraphStep(vertex,[Entity:633471488:519])#[entity],
AddPropertyStep({value=[Entity], key=[atClass]}),
AddPropertyStep({value=[FilmWithSuperCategories aaa], key=[text]}),
AddPropertyStep({value=[dffsdfsd f2313], key=[description]}),
SelectOneStep(entity)#[entity],
VertexStep(OUT,[IsOfType],edge),
DropStep
]
traversal after type edges addition:
[
GraphStep(vertex,[Entity:633471488:519])#[entity],
AddPropertyStep({value=[Entity], key=[atClass]}),
AddPropertyStep({value=[FilmWithSuperCategories aaa], key=[text]}),
AddPropertyStep({value=[dffsdfsd f2313], key=[description]}),
SelectOneStep(entity)#[entity],
VertexStep(OUT,[IsOfType],edge),
DropStep,
GraphStep(vertex,[Entity:996942848:518])#[type-0],
AddEdgeStep({~from=[[SelectOneStep(entity)]], ~to=[[SelectOneStep(type-0)]], label=[IsOfType]}),
GraphStep(vertex,[Entity:1489781376:516])#[type-1],
AddEdgeStep({~from=[[SelectOneStep(entity)]], ~to=[[SelectOneStep(type-1)]], label=[IsOfType]})
]
Edit
From what I read here (http://tinkerpop.apache.org/docs/current/reference/#drop-step)
The drop()-step (filter/sideEffect) is used to remove element and properties from the graph (i.e. remove). It is a filter step because the traversal yields no outgoing objects.
There are no objects being returned so it is not possible to do anything after a drop happens! so I am curious how I can do multiple drops/additions in a single transaction using DSE Graph Fluent API
Thanks!
You can wrap your drop in a sideEffect step, e.g.:
g.V(entity1).as("a").sideEffect(outE().filter(inV().is(entity2)).drop()).
V(entity2).addE("link").from("a")
I am trying to trace messages in a graph of messages. For example, node A sends message to node B which sends message to node C (and so on), how can I devise a query in Cypher that will keeping calling the next node until a terminal node is reached.
A -> B -> C -> D -> E -> F
start search is A, returns a list containing B,C,D,E,F (in the classic neo4j graph visualisation where these nodes are connected because B sent message to C and so on til F.
The code I have is
MATCH p=(a { address: "A" })-[r]->(b)
RETURN *
This only returns me A and the nodes A sent a message to. How can I modify it to accomplish the recursive call I am seeking.
Note: I have referred to this post and browsed the neo4j manual. However, I still don't get it (either could not find the answer or perhaps I am not 'getting it'). Any help is truly appreciated!
This call:
MATCH p=(a { address: "A" })-[r*]->(b)
RETURN b;
will match as many hops away from A as you want, because of the asterisk on the relationship. The b variable will end up being everything that's downstream of a.
I'm not sure what you mean by "call the next node". This will just return the data behind that node. You don't actually need recursion to do this at all with cypher and neo4j. Rather, you should just ask cypher for what data you want, and it will get it for you. If you were implementing this stuff on a non-graph database, you might use recursion as part of a depth-first or breadth-first search, but it simply isn't necessary with a graph DB. The query language handles all of that for you.