Two queries related to gremlin are as follows:
Want to stop the traversal when a condition is satisfied during repeated condition check.
g.V().has('label_','A')).emit().repeat(inE().outV()).until(has('stop',1)).project('depth','values').by(valueMap('label_','stop'))
I want the query to stop returning further values when the stop is equal to 1 for the node encountered during the repeat statement. But the query doesn't stop and return all the records.
Output required:
=>{label_='A',stop=0}
=>{label_='B',stop=0}
=>{label_='C',stop=1}
Query to return traversal values in the following format considering if edge exists between them. Considering the graph as A->E1->B->E2->C. The output must be as follows
=> A,E1,B
=> B,E2,C
A, B, C, E1, E2 represents properties respectively where is the starting node
For the first part, it seems you traversing on the in edges and not on the out is this on purpose? if so replace the out() in the repeat to in
g.V().has(label, 'A').emit().
repeat(out()).until(has('stop', 1)).
project('label', 'stop').
by(label).
by(values('stop'))
example: https://gremlify.com/ma2xkkszkzr/1
for the second part, I'm still not sure what you meant if you just want to get all edges with their out and in you can use elementMap:
g.E().elementMap()
example: https://gremlify.com/ma2xkkszkzr/4
and if not supported you can maybe do something like this:
g.E().local(union(
outV(),
identity(),
inV()
).label().fold())
example: https://gremlify.com/ma2xkkszkzr/2
Related
In my graph there are 2 type of labels: a and b and a boolean property travel_by.
I would like to perform BFS (with max depth of 5): start from a given node and get all the first nodes with label a.
I tried to do something like this:
g.V(<node_to_start_from>).repeat(__.both().has("travel_by", True).simplePath())
.times(5)
.until(__.hasLabel('a')).toList()
But this query is stuck for a really long time (even if I change to times(2))
A common way to do this is to use loops
g.V(<node_to_start_from>).
repeat(__.both().has("travel_by", True).simplePath()).
until(__.hasLabel('a').or().loops().is(5)).
hasLabel('a').
toList()
The second has prevents anything other than items with a label of 'a' from being part of the result in cases where loops has reached 5.
Can someone help me please with this simple query...Many thanks in advance...
I am using the following gremlin query and it works well giving me the original vertex (v) (with id-=12345), its edges (e) and the child vertex (id property). However, say if the original vertex 'v' (with id-12345) has no outgoing edges, the query returns nothing. I still want the properties of the original vertex ('v') even if it has no outgoing edges and a child. How can I do that?
g.V().has('id', '12345').as('v').
outE().as('e').
inV().
as('child_v').
select('v', 'e', 'child_v').
by(valueMap()).by(id).by(id)
There are a couple of things going on here but the major update you need to the traversal is to use a project() step instead of a select().
select() and project() steps are similar in that they both allow you to format the results of a traversal however they differ in (at least) one significant way. select() steps function by allowing you to access previously traversed and labeled elements (via as). project() steps allow you take the current traverser and branch it to manipulate the output moving forward.
In your original traversal, when there are no outgoing edges from original v so all the traversers are filtered out during the outE() step. Since there are no further traversers after the outE() step then remainder of the traversal has no input stream so there is no data to return. If you use a project() step after the original v you're able to return the original traverser as well as return the edges and incident vertex. This does lead to a slight complication when handling cases where no out edges exist. Gremlin does not handle null values, such as no out edges existing, you need to return some constant value for these statements using a coalesce statement.
Here is functioning version of this traversal:
g.V().hasId(3).
project('v', 'e', 'child_v').
by(valueMap()).
by(coalesce(outE().id(), constant(''))).
by(coalesce(out().id(), constant('')))
Currently you will get a lot of duplicate data, in the above query you will get the vertex properties E times. probably will be better to use project:
g.V('12345').project('v', 'children').
by(valueMap()).
by(outE().as('e').
inV().as('child').
select('e', 'child').by(id).fold())
example: https://gremlify.com/a1
You can get the original data format if you do something like this:
g.V('12345').as('v').
coalesce(
outE().as('e').
inV().
as('child_v')
select('v', 'e', 'child_v').
by(valueMap()).by(id).by(id),
project('v').by(valueMap())
)
example: https://gremlify.com/a2
I have a (broken) piece of gremlin code to generate the shortest path from a given vertex to one which has the parameter test_parameter. If that parameter is not found on an edge, no paths should be returned.
s.V(377524408).repeat(bothE().has('date', between(1554076800, 1556668800)).otherV()) /* date filter on edges */
.until(or(__.bothE().has('test_property', gt(0)),
loops().is(4))) /* broken logic! */
.path()
.local(unfold().filter(__.has('entity_id')).fold()) /* remove edges from output paths*/
The line that's broken is .until(or(__.outE().has('test_property', gt(0)), loops().is(4))).
At present - and it makes sense as to why - it gives all paths that are 4 hops from the starting vertex.
I'm trying to adapt it so that if the traverse is at 4 iterations, and if the property test_property is not found, then it should not return any paths. If test_property is found, it should return only the path(s) to that vertex.
I've attempted to put a times(4) constraint in and removing the loops() condition, but don't know how to have both the times(4) this and the .has('test_property', gt(0)) constraint.
Daniel's answer has few issues (see comments).
This query returns the correct result:
g.V(377524408)
.repeat(bothE().has('date', between(1554076800, 1556668800)).otherV().simplePath().as("v"))
.until(and(bothE().has('tp', gt(0)), loops().is(lte(4))))
.select(all, "v")
.limit(1)
The simplePath() is required so we won't go back and forth and avoid circles.
The repeat loop is until the condition is met AND we have not reached max hop.
The limit(1) return only the first (shortest) path. Omit to get all paths.
Note that if the graph is directed it is better to use outE() and not bothE().
This should work:
s.V(377524408).
repeat(bothE().has('date', between(1554076800, 1556668800)).otherV().as('v')).
times(4).
filter(bothE().has('test_property', gt(0))).
select(all, 'v')
Also note, that I replaced your local(unfold().filter(__.has('entity_id')).fold()) with something much simpler (assuming that the sole purpose was the removal of edges from the path).
I'm relatively new to Gremlin, and the company I'm with is looking to implement a graph database with some temporary edges within it. Each vertex could have 1 or more edge, and each edge would have a property on it that is essentially isTemporary true/false.
When traversing the graph, if "isTemporary" = true we should follow that edge, otherwise we should follow the edge where "isTemporary" = false.
I.e.,
A-[isTemporary:true, value 1] -> B
A-[isTemporary:false, value 2] -> C
B-[isTemporary: false, value 3] -> D
Running a single gremlin query should return A->B->D in this case.
I've looked through TinkerPop3 documentation, and it seems like "choose" may be what I want to use here, but all the examples seem to return a value, when what I want is a traversal to come back so I can repeatedly act on the traversal.
Any help would be appreciated.
You could be looking for the coalesce step.
Considering this graph:
g.addV().as('a').property('name', 'A').
addV().as('b').property('name', 'B').
addV().as('c').property('name', 'C').
addV().as('d').property('name', 'D').
addE('someLink').from('a').to('b').
property('isTemporary', true).property('value', 1).
addE('someLink').from('a').to('c').
property('isTemporary', false).property('value', 2).
addE('someLink').from('b').to('d').
property('isTemporary', false).property('value', 3)
The following query will return all paths from A to D, attempting to traverse via isTemporary: true edges if present, or via isTemporary: false edges otherwise (coalesce step), iteratively.
g.V().has('name', 'A').
repeat(
coalesce(
outE().has('isTemporary', true).inV(),
outE().has('isTemporary', false).inV()
)
).
until(has('name', 'D')).
path().by('name')
Result:
==>[A,B,D]
I have a Neo4j graph with directed cycles. I have had no issue finding all descendants of A assuming I don't care about loops using this Cypher query:
match (n:TEST{name:"A"})-[r:MOVEMENT*]->(m:TEST)
return n,m,last(r).movement_time
The relationships between my nodes have a timestamp property on them, movement_time. I've simulated that in my test data below using numbers that I've imported as floats. I would like to traverse the graph using the timestamp as a constraint. Only follow relationships that have a greater movement_time than the movement_time of the relationship that brought us to this node.
Here is the CSV sample data:
from,to,movement_time
A,B,0
B,C,1
B,D,1
B,E,1
B,X,2
E,A,3
Z,B,5
C,X,6
X,A,7
D,A,7
Here is what the graph looks like:
I would like to calculate the descendants of every node in the graph and include the timestamp from the last relationship using Cypher; so I'd like my output data to look something like this:
Node:[{Descendant,Movement Time},...]
A:[{B,0},{C,1},{D,1},{E,1},{X,2}]
B:[{C,1},{D,1},{E,1},{X,2},{A,7}]
C:[{X,6},{A,7}]
D:[{A,7}]
E:[{A,3}]
X:[{A,7}]
Z:[{B,5}]
This non-Neo4J implementation looks similar to what I'm trying to do: Cycle enumeration of a directed graph with multi edges
This one is not 100% what you want, but very close:
MATCH (n:TEST)-[r:MOVEMENT*]->(m:TEST)
WITH n, m, r, [x IN range(0,length(r)-2) |
(r[x+1]).movement_time - (r[x]).movement_time] AS deltas
WHERE ALL (x IN deltas WHERE x>0)
RETURN n, collect(m), collect(last(r).movement_time)
ORDER BY n.name
We basically find all the paths between any of your nodes (beware cartesian products get very expensive on non-trivial datasets). In the WITH we're building a collection delta's that holds the difference between two subsequent movement_time properties.
The WHERE applies an ALL predicate to filter out those having any non-positive value - aka we guarantee increasing values of movement_time along the path.
The RETURN then just assembles the results - but not as a map, instead one collection for the reachable nodes and the last value of movement_time.
The current issue is that we have duplicates since e.g. there are multiple paths from B to A.
As a general notice: this problem is much more elegantly and more performant solvable by using Java traversal API (http://neo4j.com/docs/stable/tutorial-traversal.html). Here you would have a PathExpander that skips paths with decreasing movement_time early instead of collection all and filter out (as Cypher does).