Hi Markus,

Great that you checked that out. I can confirm that the simplified query worked 
for me, too. It took 15.6s and revealed roughly the same number of results 
(323789).

When I loaded the results into http://zbw.eu/beta/sparql/econ_pers/query, an 
endpoint for "economics-related" persons, it matched with 36050 persons 
(supposedly the "most important" 8 percent of our set).

What I normally would do to get the according Wikipedia site URLs, is a query 
against the wikidata endpoint, which references the relevant wikidata URIs via 
a "service" clause:

PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX schema: <http://schema.org/>
#
construct {
  ?gnd schema:about ?sitelink .
}
where {
  service <http://zbw.eu/beta/sparql/econ_pers/query> {
    ?gnd skos:prefLabel [] ;
         skos:exactMatch ?wd .
    filter(contains(str(?wd), 'wikidata'))
  }
  ?sitelink schema:about ?wd ;
            schema:inLanguage ?language .
  filter (contains(str(?sitelink), 'wikipedia'))
  filter (lang(?wdLabel) = ?language && ?language in ('en', 'de'))
}

This however results in a java error. 

If "service" clauses are supposed to work in the wikidata endpoint, I'd happily 
provide addtitional details in phabricator.

For now, I'll get the data via your java example code :)

Cheers, Joachim

-----Ursprüngliche Nachricht-----
Von: Wikidata [mailto:[email protected]] Im Auftrag von 
Markus Kroetzsch
Gesendet: Samstag, 13. Februar 2016 22:56
An: Discussion list for the Wikidata project.
Betreff: Re: [Wikidata] SPARQL CONSTRUCT results truncated

And here is another comment on this interesting topic :-)

I just realised how close the service is to answering the query. It turns out 
that you can in fact get the whole set of (currently >324000 result items) 
together with their GND identifiers as a download *within the timeout* (I tried 
several times without any errors). This is a 63M json result file with >640K 
individual values, and it downloads in no time on my home network. The query I 
use is simply this:

PREFIX wd: <http://www.wikidata.org/entity/> PREFIX wdt: 
<http://www.wikidata.org/prop/direct/>

select ?item ?gndId
where {
   ?item wdt:P227 ?gndId ; # get gnd ID
         wdt:P31  wd:Q5  . # instance of human } ORDER BY ASC(?gndId) LIMIT 10

(don't run this in vain: even with the limit, the ORDER clause requires the 
service to compute all results every time someone runs this. Also be careful 
when removing the limit; your browser may hang on an HTML page that large; 
better use the SPARQL endpoint directly to download the complete result file.)

It seems that the timeout is only hit when adding more information (labels and 
wiki URLs) to the result.

So it seems that we are not actually very far away from being able to answer 
the original query even within the timeout. Certainly not as far away as I 
first thought. It might not be necessary at all to switch to a different 
approach (though it would be interesting to know how long LDF takes to answer 
the above -- our current service takes less than 10sec).

Cheers,

Markus


On 13.02.2016 11:40, Peter Haase wrote:
> Hi,
>
> you may want to check out the Linked Data Fragment server in Blazegraph:
> https://github.com/blazegraph/BlazegraphBasedTPFServer
>
> Cheers,
> Peter
>> On 13.02.2016, at 01:33, Stas Malyshev <[email protected]> wrote:
>>
>> Hi!
>>
>>> The Linked data fragments approach Osma mentioned is very 
>>> interesting (particularly the bit about setting it up on top of an 
>>> regularily updated existing endpoint), and could provide another 
>>> alternative, but I have not yet experimented with it.
>>
>> There is apparently this: 
>> https://github.com/CristianCantoro/wikidataldf
>> though not sure what it its status - I just found it.
>>
>> In general, yes, I think checking out LDF may be a good idea. I'll 
>> put it on my todo list.
>>
>> --
>> Stas Malyshev
>> [email protected]
>>
>> _______________________________________________
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>
>
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>


--
Markus Kroetzsch
Faculty of Computer Science
Technische Universität Dresden
+49 351 463 38486
http://korrekt.org/

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