Hello! On Mon, Jun 10, 2019 at 4:28 PM Sebastian Hellmann <hellm...@informatik.uni-leipzig.de> wrote: > > Hi Guillaume, > > On 06.06.19 21:32, Guillaume Lederrey wrote: > > Hello all! > > There has been a number of concerns raised about the performance and > scaling of Wikdata Query Service. We share those concerns and we are > doing our best to address them. Here is some info about what is going > on: > > In an ideal world, WDQS should: > > * scale in terms of data size > * scale in terms of number of edits > * have low update latency > * expose a SPARQL endpoint for queries > * allow anyone to run any queries on the public WDQS endpoint > * provide great query performance > * provide a high level of availability > > Scaling graph databases is a "known hard problem", and we are reaching > a scale where there are no obvious easy solutions to address all the > above constraints. At this point, just "throwing hardware at the > problem" is not an option anymore. We need to go deeper into the > details and potentially make major changes to the current architecture. > Some scaling considerations are discussed in [1]. This is going to take > time. > > I am not sure how to evaluate this correctly. Scaling databases in general is > a "known hard problem" and graph databases a sub-field of it, which are > optimized for graph-like queries as opposed to column stores or relational > databases. If you say that "throwing hardware at the problem" does not help, > you are admitting that Blazegraph does not scale for what is needed by > Wikidata.
Yes, I am admitting that Blazegraph (at least in the way we are using it at the moment) does not scale to our future needs. Blazegraph does have support for sharding (what they call "Scale Out"). And yes, we need to have a closer look at how that works. I'm not the expert here, so I won't even try to assert if that's a viable solution or not. > From [1]: > > At the moment, each WDQS cluster is a group of independent servers, sharing > nothing, with each server independently updated and each server holding a > full data set. > > Then it is not a "cluster" in the sense of databases. It is more a redundancy > architecture like RAID 1. Is this really how BlazeGraph does it? Don't they > have a proper cluster solution, where they repartition data across servers? > Or is this independent servers a wikimedia staff homebuild? It all depends on your definition of a cluster. We have groups of machine collectively serving some coherent traffic, but each machine is completely independent from others. So yes, the comparison to RAID1 is adequate. > Some info here: > > - We evaluated some stores according to their performance: > http://www.semantic-web-journal.net/content/evaluation-metadata-representations-rdf-stores-0 > "Evaluation of Metadata Representations in RDF stores" Thanks for the link! That looks quite interesting! > - Virtuoso has proven quite useful. I don't want to advertise here, but the > thing they have going for DBpedia uses ridiculous hardware, i.e. 64GB RAM and > it is also the OS version, not the professional with clustering and > repartition capability. So we are playing the game since ten years now: > Everybody tries other databases, but then most people come back to virtuoso. > I have to admit that OpenLink is maintaining the hosting for DBpedia > themselves, so they know how to optimise. They normally do large banks as > customers with millions of write transactions per hour. In LOD2 they also > implemented column store features with MonetDB and repartitioning in clusters. I'm not entirely sure how to read the above (and a quick look at virtuoso website does not give me the answer either), but it looks like the sharding / partitioning options are only available in the enterprise version. That probably makes it a non starter for us. > - I recently heard a presentation from Arango-DB and they had a good cluster > concept as well, although I don't know anybody who tried it. The slides > seemed to make sense. Nice, another one to add to our list of options to test. > All the best, > > Sebastian > > > > > Reasonably, addressing all of the above constraints is unlikely to > ever happen. Some of the constraints are non negotiable: if we can't > keep up with Wikidata in term of data size or number of edits, it does > not make sense to address query performance. On some constraints, we > will probably need to compromise. > > For example, the update process is asynchronous. It is by nature > expected to lag. In the best case, this lag is measured in minutes, > but can climb to hours occasionally. This is a case of prioritizing > stability and correctness (ingesting all edits) over update latency. > And while we can work to reduce the maximum latency, this will still > be an asynchronous process and needs to be considered as such. > > We currently have one Blazegraph expert working with us to address a > number of performance and stability issues. We > are planning to hire an additional engineer to help us support the > service in the long term. You can follow our current work in phabricator [2]. > > If anyone has experience with scaling large graph databases, please > reach out to us, we're always happy to share ideas! > > Thanks all for your patience! > > Guillaume > > [1] https://wikitech.wikimedia.org/wiki/Wikidata_query_service/ScalingStrategy > [2] https://phabricator.wikimedia.org/project/view/1239/ > > -- > All the best, > Sebastian Hellmann > > Director of Knowledge Integration and Linked Data Technologies (KILT) > Competence Center > at the Institute for Applied Informatics (InfAI) at Leipzig University > Executive Director of the DBpedia Association > Projects: http://dbpedia.org, http://nlp2rdf.org, > http://linguistics.okfn.org, https://www.w3.org/community/ld4lt > Homepage: http://aksw.org/SebastianHellmann > Research Group: http://aksw.org -- Guillaume Lederrey Engineering Manager, Search Platform Wikimedia Foundation UTC+2 / CEST _______________________________________________ Wikidata mailing list Wikidata@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wikidata
