Hi Nicolas,
you've used a "Relational approach". My suggestion is to use the Graph
Design in this way:
create class Author extends V
create class Blog extends V
create class BlogPost extends E
Author and Blog are vertices while BlogPost is an Edge
Then populate your database using some API or direct SQL like:
create vertex Author set login = 'luca', sex = 'm'
...
create vertex Blog set id = 'lucasblog', title = "Luca's Blog"
...
create edge BlogPost from ( select from Author where login = 'luca' ) to
( select from Blog where id = 'lucasblog' ) set id = 'test', title = 'Super
Test'
Then this would be the query:
select login, out('BlogPost').size() from Author where sex = "m"
To have more performance you could create an index against sex:
create property Author.sex string
create index Author.sex notunique
And retry the same query:
select login, out('BlogPost').size() from Author where sex = "m"
Lvc@
On 21 February 2014 12:11, Nicolas Clairon <[email protected]> wrote:
> Hi,
>
> I made a little benchmark of OrientDB with the following data:
>
> 1000 authors
> 10000 blogs
> 100000 blogposts
>
> the data made for the bench was loaded in the documents database.
>
> Here's the schema:
>
> author: {
> '@class':'Author'
> login: string
> sex: string // 'f' or 'm'
> }
>
> blog: {
> '@class':'Blog'
> id: string
> title: string
> }
>
> blogpost: {
> '@class':'BlogPost'
> id: string
> title: string
> authorID: string
> blogID: string
> }
>
> blogpost has a LINK to author and blog.
>
> The query is simple:
>
> 'select author.login, count(*) from BlogPost where author.sex = "m"
> group by author.login'
>
> but it takes 3.782 seconds to complete on a MacBook air 2013 (SSD and 8Go
> of RAM).
>
> In comparison, the triplestore Virtuoso performs the same query in 34ms
> (!) on the same machine.
>
> I made some indexes in Author.login (unique) and Author.sex (not unique)
> without luck...
>
> Is there any hints to know to make OrientDB faster for aggregation ?
>
> Thanks.
>
> N.
>
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