I have a set of nodes extracted from a network bitcoin transaction network using the following query:
MATCH (root:Address {AddressID: $val})-[r*..k]->(target:Transaction)
RETURN DISTINCT(target.Hash) AS Targets
where k = 1, 3 and 5 (i.e. hops away from the root node). The result is a set of nodes (~210000) in a .csv file with two columns: [k, TxHash]
I would like to create the relationship files between the extracted nodes. The easiest way would be to create a nested for loop in the following manner:
q1 = """
MATCH (src:Transaction {Hash: $val1})-[op:OutgoingPayment]->(a:Address)-[ip:IncomingPayment]->(dst:Transaction {Hash: $val2})
RETURN DISTINCT(dst.Hash) AS Target
"""
for src in neighbors:
for dst in neighbors:
output = graph.run(q1, parameters = {"val1": str(src), "val2": str(dst)}).to_data_frame()
Even though it's the easiest way, it will also take a lot of time. Is there some other more efficient way to achieve this?
Thank you!
P.S. The overall goal is starting from a seed node to visit its neighbors for k = 1, 2, ..., n and create the appropriate .csv files for bulk import in neo4j. In other words, identify a specific subgraph, create the appropriate .csv files and re-import it in a new neo4j db.
