Re: hasNext() slow for large number of incoming edges
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It will definitely be a valid and valuable feature, if we could expose the streaming capacity to end users. If I recall correctly, the low-level results are indeed streamed (it might vary depending on the storage backend), but the interface is not exposed to the upper level APIs. Do you want to create a feature request on GitHub? Otherwise I can do it later.
Regarding your particular usecase, you said you had triples like <microsoft> <rdfs:type> <company>, which you modelled as V('microsoft') -> E('rdfs:type') -> V('company'). I suggest you model “type” as a property rather an edge. So, you will not create a vertex called “company”. Rather, you create a vertex called “microsoft” with a property “type” whose value is “company”, e.g.
g.addV().property(“value”, “microsoft”).property(“type”, “company”)
Rule of thumb: when you anticipate a super node, consider modeling it as a property rather than a vertex. Edges should be used to describe “relationships between nodes” rather than “properties attached to nodes”. This is the difference between a RDF and a property graph.
On Thu, Jan 27, 2022 at 12:51 AM Matthew Nguyen via lists.lfaidata.foundation <nguyenm9=aol.com@...> wrote: