Re: Count Query Optimization


Nicolas Trangosi
 

Hi,
You may try to use denormalization by setting property1 from inV also on edge. 
Then once edges are updated, following query should work:

g.V().has('property1', 'A').aggregate('v').outE().has('property1','E').has('inVproperty1', 'B').aggregate('e').inV().aggregate('v').select('v').dedup().as('vetexCount').select('e').dedup().as('edgeCount').select('vetexCount','edgeCount').by(unfold().count())


Le mer. 17 mars 2021 à 14:05, Vinayak Bali <vinayakbali16@...> a écrit :
Hi Marc,

Using local returns the output after each count. For example:

==>[vetexCount:184439,edgeCount:972]
==>[vetexCount:184440,edgeCount:973]
==>[vetexCount:184441,edgeCount:974]
==>[vetexCount:184442,edgeCount:975]
==>[vetexCount:184443,edgeCount:976]
==>[vetexCount:184444,edgeCount:977]
==>[vetexCount:184445,edgeCount:978]
==>[vetexCount:184446,edgeCount:979]
==>[vetexCount:184447,edgeCount:980]
==>[vetexCount:184448,edgeCount:981]
==>[vetexCount:184449,edgeCount:982]
==>[vetexCount:184450,edgeCount:983]
==>[vetexCount:184451,edgeCount:984]
==>[vetexCount:184452,edgeCount:985]
==>[vetexCount:184453,edgeCount:986]
==>[vetexCount:184454,edgeCount:987]
==>[vetexCount:184455,edgeCount:988]
==>[vetexCount:184456,edgeCount:989]
==>[vetexCount:184457,edgeCount:990]
==>[vetexCount:184458,edgeCount:991]
==>[vetexCount:184459,edgeCount:992]
==>[vetexCount:184460,edgeCount:993]
==>[vetexCount:184461,edgeCount:994]
==>[vetexCount:184462,edgeCount:995]
==>[vetexCount:184463,edgeCount:996]
==>[vetexCount:184464,edgeCount:997]
==>[vetexCount:184465,edgeCount:998]

You can suggest some other approach too. I really need it working.

Thanks & Regards,
Vinayak

On Wed, Mar 17, 2021 at 5:54 PM <hadoopmarc@...> wrote:
Hi Vinayak,

Referring to you last post, what happens if you use aggregate(local, 'v') and aggregate(local, 'e'). The local modifier makes the aggregate() step lazy, which hopefully gives janusgraph more opportunity to batch the storage backend requests.
https://tinkerpop.apache.org/docs/current/reference/#store-step

Best wishes,    Marc



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Nicolas Trangosi

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