Taking huge time to count node which has multiple edge with same specific node?

[kalyan_b_aninda]

here is my scenario

Hello

I have specific node label named C . some of this this has multiple edges of same relationship "HAS_DEVICE" with specific node node D. so far I have tried variable length but counting those nodes is taking so much time . here is my query

Match(n:C)-[r:HAS_DEVICE*2..10]-(d:D) return count(n.IDENTITYID),d.DEVICEID as deviceid;

the query is taking huge time . My graph has 10,448,975 nodes and 11,038,864 relationship. I have put identityid as constraints . Is there any wrong of my code or am I something missing here. Kindly help me out

I was expecting output like this
n.Identityid. d.deviceid
3. xyzzy
2. fdfda

[Cobra]

Hello @kalyan.b.aninda

Why have you put relationships hops (*2..10) in your query?

Regards,
Cobra

[kalyan_b_aninda]

oh hello @Cobra cobra cause I have same relationship has_device more than 2 edges so I have put a range here .

[Cobra]

I think there is a misunderstanding, you have to use jumps when you want a path with depth. It's not your case.

You should have a look at this topic to count relations:

Optimize getting all incoming and outgoing edges for each node and computing the difference in amoun... Cypher

Hello @tomas.vrba This is a solution: MATCH (n) CALL { WITH n MATCH (n)-[r]->() RETURN count(r) AS occurrences UNION WITH n MATCH (n)<-[r]-() RETURN count(r) AS occurrences } WITH n, collect(occurrences) AS values SET n.balance = values[0] - values[1] To speed-up this query, you can do several things if you are not working on all nodes of the database: specify a label or a relation type specify a UNIQUE CONSTRAINT and use the index created in a WHERE clause Rega…

Regards,
Cobra

[kalyan_b_aninda]

I am checking it :). but the variable length query gave me the actual picture of nodes which are connected with same relationship multiple times with other specific node. Actually I was happy with that but counting these nodes seems cumbersome to me any way checking your solution. I have got reply after a long time from you 🙂

[Cobra]

This query should solve your problem?

MATCH (n:C)-[r:HAS_DEVICE]->(d:D)
RETURN d.DEVICEID AS deviceid, count(n.IDENTITYID) AS total

[kalyan_b_aninda]

@cobra I wanted to filter those nodes which have same relationship>=2 with d nodes. I tried this query before post but it shows unfiltered report.
like
deviceid. identityid
ererere. 1

[kalyan_b_aninda]

here I one of your solution is similar to me

Query all the paths to one node with one kind of relationship neo4j Cypher

Hi, Cobra. Thanks for the quick reply. But we have a little bit of misunderstanding here. I mean I want to use cypher query to get the result set, not using Neo4j desktop to hide the relationships in the result set. What I want to do here is using "DEPEND_ON" relationships to get all the paths(nodes connected using “DEPEND_ON” relationships) to the node with certain "gav" property value. In other word, using cypher query to exclude the "NEXT" relationships from the resulted subgraph, only ke…

here in your problem NEXT relationship is directed to multiple times in some specific node from other node . that specific node is my d node and others nodes are my C nodes, I wanted to count C nodes

[Cobra]

You have depth in your database?
Do you have?
(A)->(B)->(C)
Or
(A)->(C)
(B)->(C)

Your first post show looks like the second option.

Regards,
Cobra

[kalyan_b_aninda]

Ok I am giving you screen shot what I am getting after

match(n:CUSTOMER)-[r:HAS_DEVICE*2..10]-(d:DEVICE) return n,r,d

so here I can limit my range in number. the brown nodes are device and red nodes are customer so I am trying to find out count of customers which are using same device with HAS_DEVICE relationship . you see there is many customer who are using same device. **I am wanting the direct 1 hop customers count from single devices those have >= 2 edges with customer **

[Cobra]

Could you create a dummy example I can work on?

[kalyan_b_aninda]

@cobra I have managed a solution . I have counted all customer nodes which are connected with each device then export it as csv. After that I ran a python script to filter most connected customer with single device . It worked :). Thank you for your help