Re: Degree-Centrality Filtering & Search – Scalable Strategies for OLTP

"" <zblu...@...>

Thank you Boxuan,

Was using the term “job” pretty loosely.  Your inference about doing these things within ingest/deletion process makes sense.

I know there is a lot on the community’s plate now, but if my above solution is truly optimal for current state, I wonder if a JG feature addition may help tackle this problem more consistently. Something like an additional, 3rd , index type (in addition to “graph” and “vertex-centric” indices) . i.e. “edge-connection” or “degree-centrality” index. The feature would require a mixed indexing backend, and minimally a mechanism to choose vertex and edge label combinations to count IN, OUT, and/or BOTH degree centrality.

Not sure what the level of effort or implementation details would be, but this is a very common business requirement for graph-based search.  If JanusGraph has native/tested support for it, it would make JanusGraph even easier to champion.




On Tuesday, December 29, 2020 at 3:19:46 AM UTC-5 li...@... wrote:
Hi Zach,

Personally I think your workaround is the most optimal one. JanusGraph does not store number of edges as metadata in the vertex (there are both Pros & Cons for doing / not doing this).

Btw do you have to have another job doing centrality calculation separately? If your application is built on top of JanusGraph, then probably you can maintain the “outDegree” property when inserting/deleting edges.

Best regards,

On Dec 29, 2020, at 6:49 AM, <zb...@...> wrote:

Hello all,

Curious about best approaches/practices for scalable degree-centrality search filters on large (millions to billions of nodes) JanusGraphs.  i.e. something like :




Suppose the has-step narrows down to a large number of vertices (hundreds of thousands), then performing that form of count on that many vertices will result in timeouts and inefficiencies (at least in my experience).  My workaround for this has been pre-calculating centrality in another job and writing to a Vertex Property that can subsequently be included in a mixed index. So we can do:




This works, but it is yet another calculation we must maintain in our pipeline and while sufficing, it seems like more of a workaround then a great solution. I was hoping there was a more optimal approach/strategy. Please let me know. 

Thank you,


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