Hi,
Thanks for all the work. I think this is a sensible decision. What
confused me at first is that I did not know BlazeGraph (and when you
google for it, the first thing is an unrelated sourceforge project). An
important insight for me thus was that "BlazeGraph" is the project that
has up until very recently been called "Bigdata", and as such is not the
new, unknown project that I first thought it was.
It seems clear that there are a few issues to address. In particular,
among hundreds of known public SPARQL services [1], there does not seem
to be one that identifies itself as using BlazeGraph/Bigdata. However,
there is clearly potential here and it would be exciting to see the
project maturing into a robust free RDF store and query engine.
Cheers,
Markus
[1] http://sparqles.okfn.org/discoverability
On 05.03.2015 19:49, Nikolas Everett wrote:
TL/DR: We're selected BlazeGraph to back the next Wikidata Query Service.
After Titan evaporated about a month ago we went back to the drawing
board on back ends for a new Wikidata Query Service. We took four weeks
(including a planed trip to Berlin) to settle on a backend. As you can
see from the spreadsheet
<https://docs.google.com/a/wikimedia.org/spreadsheets/d/1MXikljoSUVP77w7JKf9EXN40OB-ZkMqT8Y5b2NYVKbU/edit#gid=0>
we've really blown out the number of options. As you can also see we
didn't finish filling them all out. But we've still pretty much settled
on BlazeGraph <http://www.blazegraph.com/> anyway. Let me first explain
what BlazeGraph is and then defend our decision to stop spreadsheet work.
BlazeGraph is a GPLed RDF triple store that natively supports SPARQL
1.1, RDFS, some OWL, and some extensions. Those are all semantic web
terms and they translate into a "its a graph database with an
expressive, mostly standardized query language and support for inferring
stuff as data is added and removed to the graph". It also has some
features that you'd recognize from nice relational databases: join order
rewriting, smart query planner, hash and nested loop joins, query
rewrite rules, group by, order by, and aggregate functions.
These are all cool features - really the kind of things that we thought
we need but they come with an "interesting" price. Semantic Web is a
very old thing that's had a really odd degree of success. If you have
an hour and half Jim Hendler can explain
<https://www.youtube.com/watch?v=oKiXpO2rbJM> it to you. The upshot is
that _tons_ of people have _tons_ of opinions. The W3C standardizes
RDF, SPARQL, RDFS, OWL, and about a billion other things. There are
(mostly non-W3C) standards for talking about people
<http://xmlns.com/foaf/spec/>, social connections
<http://rdfs.org/sioc/spec/>, and music
<http://musicontology.com/specification/>. And they all have rules. And
Wikidata doesn't. Not like these rules. One thing I've learned from
this project is that this lack of prescribed rules is one of Wikidata's
founding principles. Its worth it to allow openness. So you _can_ set
gender to "Bacon" or put GeoCoordinants on Amber
<https://www.wikidata.org/wiki/Q1053330>. Anyway! I argue that, at
least for now, we should ignore many of these standards. We need to
think of Wikidata Query Service as a tool to answer questions instead of
as a some grand statement about the semantic web. Mapping existing
ontologies onto Wikidata is a task for another day.
I feel like these semantic web technologies and BlazeGraph in particular
are good fits for this project mostly because the quality of our "but
what about X?" questions is very very high. "How much inference should
we do instead of query rewriting?" instead of "Can we do inference? Can
we do query rewriting?" And "Which standard vocabularies should think
about mapping to Wikidata?" Holy cow! In any other system there aren't
"standard vocabularies" to even talk about mapping, much less a
mechanism for mapping them. Much less two! Its almost an overwhelming
wealth and as I elude to above it can be easy to bikeshed.
We've been reasonably careful to reach out people we know are familiar
with this space. We're well aware of projects like the Wikidata Toolkit
and its RDF exports. We've been using those for testing. We've talked
to so many people about so many things. Its really consumed a lot more
time then I'd expected and made the search for the next backend very
long. But I feel comfortable that we're in a good place. We don't know
all the answers but we're sure there _are_ answers.
The BlazeGraph upstream has been super active with us. They've spent
hours with us over hangouts, had me out to their office (a house an hour
and half from mine) to talk about data modeling, and spent a ton of time
commenting on Phabricator tickets. They've offered to donate a formal
support agreement as well. And to get together with us about writing
any features we might need to add to BlazeGraph. And they've added me
as a committer (I told them I had some typos to fix but I have yet to
actually commit them). And their code is well documented.
So by now you've realized I'm a fan. I believe that we should stop on
the spreadsheet and just start work against BlazeGraph because I think
we have phenomenal momentum with upstream. And its a pretty clear
winner on the spreadsheet at this point. But there are two other triple
stores which we haven't fully filled out that might be viable: OpenLink
Virtuoso Open Source and Apache Jena. Virtuoso is open core so I'm
really loath to go too deep into it at his point. Their HA features are
not open source which implies that we'd have trouble with them as an
upstream. Apache Jena just isn't known
<http://www.w3.org/wiki/LargeTripleStores#Jena_TDB_.281.7B.29> to scale
to data as large as BlazeGraph and Virtuoso. So I argue that these are
systems that, in the unlikely event that BlazeGraph goes the way of
Titan, we should start our third round of investigation against. As it
stands now I think we have a winner.
We created a phabricator task <https://phabricator.wikimedia.org/T90101>
with lots of children to run down our remaining questions. The biggest
remaining questions revolve around three areas:
1. Operational issues like "how should the cluster be deployed?" "do we
use HA at all?" "how are rolling restarts done in HA?"
2. How should we represent the data in the database? BlazeGraph (and
only BlazeGraph) has an extension that *could* us called RDR. Should we
use it?
3. Some folks have identified update rate as a risk. Not upstream, but
others familiar with triple stores in general.
Our plans is to work on #2 over the next weeks because it really informs
#1 because there are lots of working set size vs cpu time tradeoffs to
investigate. We'll start on #1 shortly as well. #3 is a potential risk
area so we'll be sure to investigate it soon.
I admit I'm not super happy to leave the spreadsheet in the format its
current unfilled-out state but I'm excited to have something to work
with and think its the right thing to do right now.
So thanks for reading all of this. Please reply with comments.
Thanks again,
Nik
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