Thanks for the feedback!
Sounds good. I also hope the changes can be integrated into a stable
version soon.
Best regards
Jan
Am Mittwoch, 20. September 2017 00:54:44 UTC+2 schrieb Roman Kuzmik:
>
> Thanks for a hint!
>
> We have wrote small service faced to calculate facets.
> It split my huge AQL provided above into 5 queries:
>
> - main - to filter, sort and retrieve matching entities:
> -
>
> LET docs = (FOR a IN Asset
>
> FILTER a.name like 'test-asset-%'
>
> SORT a.name
>
> RETURN a)
>
> RETURN {
>
> counts: (RETURN {
>
> total: LENGTH(docs),
>
> offset: 0,
>
> to: 5
>
> }),
>
> items: (FOR a IN docs LIMIT 0, 5 RETURN a)
>
> }
>
> - 4 small ones to purely calculate facets:
> -
>
> LET docs = (FOR a IN Asset
>
> FILTER a.name like 'test-asset-%'
>
> RETURN a)
>
> LET attributeX = (
>
> FOR a in docs
>
> COLLECT attr = a.attributeX WITH COUNT INTO length
>
> RETURN { value: attr, count: length}
>
> )
>
> RETURN {
>
> counts: (RETURN {
>
> total: LENGTH(docs),
>
> offset: 0,
>
> to: -1,
>
> facets: {
>
> attributeX: {
>
> from: 0,
>
> to: 1000,
>
> total: LENGTH(attributeX)
>
> }
>
> }
>
> }),
>
> facets: {
>
> attributeX: (FOR a in attributeX LIMIT 0, 1000 return a)
>
> }
>
> }
>
> We run these using Java's 8 Fork/Join and basically execute Map(split into
> sub-queries)/Reduce(merge results) potentially against ArangoDB cluster.
> We run custom ArangoDB build from Jan's feature branch. And results are
> pretty impressive.
> Remember, we have started with 140 secs for the full AQL and now we are
> down to 11 seconds (with sort/filter + skiplist on name) or 4 seconds (w/o
> soft/filter and 4 facets).
>
> I think, we are satisfied for now :-) and hope this PR will make it to
> 'master'.
>
> Also, would be awesome to see if AQL-pipeline will be advanced in the
> future to accomodate more analytical type of queries (facets with
> sub-facets, ElasticSearch style of sub-grouping, etc)
>
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