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Cosmos DB doesn't support grouping by anything that is not a primitive (I've already sent a request for them to fix this). But in the meantime, how could I go by doing groupCount() by multiple values without needing arrays, or using lambdas (which are also not supported)

This is what I would like to do

g.V().groupCount().by(values('id', 'name').fold())

But I cannot use values().fold(). Any suggestions?

GalmWing
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1 Answers1

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Hmm, the only (ugly) workaround I can think of is this:

g.V().
  group().
    by('id').
    by(groupCount().by('name')).
  unfold().
  match(__.as('kv').select(keys).as('k'),
        __.as('kv').select(values).unfold().as('v')).
  project('key','value').
    by(union(select('k'), select('v').by(keys)).fold()).
    by(select('v').by(values))

So basically a nested grouping by primitive values, followed by an unfolding and regrouping into a map made of only primitive keys. The result will look similar to this:

==>[key:[id1,name1],value:1]
==>[key:[id2,name2],value:2]
==>[key:[id3,name3],value:1]
...

UPDATE

Since CosmosDB doesn't support match(), the query would look like this:

g.V().
  group().
    by('id').
    by(groupCount().by('name')).
  unfold().as('kv').
  select(keys).as('k').
  select('kv').select(values).unfold().as('v').
  project('key','value').
    by(union(select('k'), select('v').by(keys)).fold()).
    by(select('v').by(values))
Daniel Kuppitz
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