I have a fairly deep tree that consists of an initial "transaction" node (call that the 0th layer of the tree), from which there are 50 edges to the next nodes (call it the 1st later of the tree), and then from each of those around 35 on average to the second layer, and so on...
The initial node is a :txnEvent and all the rest are :mEvent
mEvent nodes have 4 properties, one of them called channel_name
Now, I would like to retrieve all paths that go down to the 4th layer such that those paths contain a node with channel_name==A and also channel_name==B
This query:
match (n: txnEvent)-[r:TO*1..4]->(m:mEvent) return COUNT(*);
Is telling me there are only 1,667,444 paths to consider.
However, the following query:
MATCH p = (n:txnEvent)-[:TO*1..4]->(m:mEvent)
WHERE ANY(k IN nodes(p) WHERE k.channel_name='A')
AND ANY(k IN nodes(p) WHERE k.channel_name='B')
RETURN
EXTRACT (n in nodes(p) | n.channel_name),
EXTRACT (n in nodes(p) | n.step),
EXTRACT (n in nodes(p) | n.event_type),
EXTRACT (n in nodes(p) | n.event_device),
EXTRACT (r in relationships(p) | r.weight )
Takes almost 1 minute to execute (neo4j's UI on port 7474)
For completness, neo4j is telling me:
"Started streaming 125517 records after 2 ms and completed after 50789 ms, displaying first 1000 rows."
So I'm wondering whether there's something obvious I'm missing. All of the properties that nodes have are indexed by the way. Is the query slow, or is it fast and the streaming is slow?
UDATE: This query, that doesn't stream data back:
MATCH p = (n:txnEvent)-[:TO*1..4]->(m:mEvent)
WHERE ANY(k IN nodes(p) WHERE k.channel_name='A')
AND ANY(k IN nodes(p) WHERE k.channel_name='B')
RETURN
COUNT(*)
Takes 35s, so even though it's faster, presumably because no data is returned, I feel it's still quite slow.
UPDATE 2:
Ideally this data should go into a jupyter notebook with a python kernel.