On 7/13/20 1:41 PM, Adam Sanchez wrote:
> Hi,
>
> I have to launch 2 million queries against a Wikidata instance.
> I have loaded Wikidata in Virtuoso 7 (512 RAM, 32 cores, SSD disks with RAID
> 0).
> The queries are simple, just 2 types.
>
> select ?s ?p ?o {
> ?s ?p ?o.
> filter (?s = ?param)
> }
>
> select ?s ?p ?o {
> ?s ?p ?o.
> filter (?o = ?param)
> }
>
> If I use a Java ThreadPoolExecutor takes 6 hours.
> How can I speed up the queries processing even more?
>
> I was thinking :
>
> a) to implement a Virtuoso cluster to distribute the queries or
> b) to load Wikidata in a Spark dataframe (since Sansa framework is
> very slow, I would use my own implementation) or
> c) to load Wikidata in a Postgresql table and use Presto to distribute
> the queries or
> d) to load Wikidata in a PG-Strom table to use GPU parallelism.
>
> What do you think? I am looking for ideas.
> Any suggestion will be appreciated.
>
> Best,Hi Adam, You need to increase the memory available to Virtuoso. If you are at your limits that's when the Cluster Edition will come in handy i.e., enabling you build a large pool or memory from a sharded DB horizontally partitioning over of collection of commodity computers. There is a public Google Spreadsheet covering a variety of public Virtuoso instances that should aid you in this process [1]. Links: [1] https://docs.google.com/spreadsheets/d/1-stlTC_WJmMU3xA_NxA1tSLHw6_sbpjff-5OITtrbFw/edit#gid=812792186 -- Regards, Kingsley Idehen Founder & CEO OpenLink Software Home Page: http://www.openlinksw.com Community Support: https://community.openlinksw.com Weblogs (Blogs): Company Blog: https://medium.com/openlink-software-blog Virtuoso Blog: https://medium.com/virtuoso-blog Data Access Drivers Blog: https://medium.com/openlink-odbc-jdbc-ado-net-data-access-drivers Personal Weblogs (Blogs): Medium Blog: https://medium.com/@kidehen Legacy Blogs: http://www.openlinksw.com/blog/~kidehen/ http://kidehen.blogspot.com Profile Pages: Pinterest: https://www.pinterest.com/kidehen/ Quora: https://www.quora.com/profile/Kingsley-Uyi-Idehen Twitter: https://twitter.com/kidehen Google+: https://plus.google.com/+KingsleyIdehen/about LinkedIn: http://www.linkedin.com/in/kidehen Web Identities (WebID): Personal: http://kingsley.idehen.net/public_home/kidehen/profile.ttl#i : http://id.myopenlink.net/DAV/home/KingsleyUyiIdehen/Public/kingsley.ttl#this
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