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Performing call functions on large amount of data

ldj20
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I'm currently trying to use several graph data science library functions on a relatively large amount of data (millions of nodes and relationships). First off I need to create a projection, so I just copied this from documentation and ran it:

CALL gds.graph.create.cypher(
    graphName: String,
    nodeQuery: String,
    relationshipQuery: String,
    configuration: Map
) YIELD
    graphName: String,
    nodeQuery: String,
    nodeCount: Integer,
    relationshipQuery: String,
    relationshipCount: Integer,
    createMillis: Integer

And this has been running for hours. Obviously I don't know how far along it is, how long it'll take, or if it'll even finish at all due to space constraints. I know when you normally work with large amounts of data you usually use apoc.periodic.iterate. However, to my knowledge, this is not a possibility here. So should I expect these large call functions to finish in a reasonable amount of time? And if not what can I do to improve them?

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