Hi Luca,
Thanks for the advice. However in your query I am unable to filter by
timestamp on the edge. Instead, I ended up with:
SELECT inV().name AS name, COUNT(*) AS weight FROM (
SELECT FROM (
SELECT expand(outE("UserUsedTag"))
FROM user
WHERE username = "john.doe"
) WHERE timestamp > date('2015-04-25 05:00:22')
AND timestamp < date('2015-04-25 05:01:10')
)
GROUP BY in
ORDER BY weight DESC
soccer 5020
baseball 4939
Query executed in 0.468 sec. Returned 2 record(s)
The above query seems to take into account all indexes (index on
User.username and UserUsedTag.timestamp).
Still, 468ms for ~10k records. Am I correct then that OrientDB in the end
is a tradeoff, i.e. it's a lot more developer friendly and has tons of
features, but at the cost of rougly ~40x the performance of a traditional
relational DB such as PostgreSQL?
On Sunday, April 26, 2015 at 6:33:38 PM UTC+8, l.garulli wrote:
>
> On 25 April 2015 at 16:41, Jean-Sebastien Lemay <[email protected]
> <javascript:>> wrote:
>
>> Hi there,
>>
>
> Hi Jean-Sebastien
>
>
>>
>> OK -- I'm a bit surprised, in a way; this is a straightforward SELECT
>> statement.
>>
>> I decided to run another experiment. My scenario: determine which tags
>> are a given user's favourite.
>>
>> My query in OrientDB:
>> SELECT in.name AS name, COUNT(in.name) AS weight
>> FROM UserUsedTag
>> WHERE "john.doe" IN out.username
>> AND timestamp < date()
>> GROUP BY in.name
>> ORDER BY weight DESC
>> Query executed in 0.487 sec. Returned 2 record(s)
>> soccer 5042
>> baseball 4958
>>
>
> This is not the most efficient way to do that, because the index on
> username wouldn't be used. With a Graph Database, you should lookup at the
> stating vertex and then cross relationships. Try this:
>
> select name, count(*) as weight
> from (
> select expand( in() ) from User where username = "john.doe"
> ) group by name, order by weight
>
> Assure to have an index on User.username. I'd suggest a Unique index of
> type HASH_INDEX.
>
> Lvc@
>
>
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