concurrency in random walk

[yliu34]

Hello,

I'm currently working on running the random walk algorithm in parallel through python drivers. However, I have not found a way to make it. First, I tried the multiprocessing tool in python and it turned out that it could not be used with python drivers. Afterward, I tried the concurrency parameter of the random walk algorithm. But it did not save time when I increased the number and run the task on either my computer or a cluster. I am wondering if anyone has a similar experience and can help me with this. Thank you in advance. The code I am using is as follows:

CALL gds.beta.randomWalk.stream(
'example',
{
walkLength: 10,
walksPerNode: 1,
randomSeed: 42,
concurrency: 10
}
)
YIELD nodeIds, path
RETURN nodeIds, [node IN nodes(path) | node.name ] AS event_name

[TrevorS]

Hello @yliu34 

Thank you for posting to the Community!
Are you still having difficulty with your query or have you been able to resolve this yourself?

If you were able to resolve the issue, can you please post what you did so I can mark it as a solution for others who may encounter a similar issue?

Thanks!

[yliu34]

Hi Trevor,

Unfortunately, I have not solved the problem. I will post the solution if there is one.

Yang

[TrevorS]

You can also create a ticket for this at https://github.com/neo4j.
Please reply back with your ticket number if you decide to do so!