On 4/5/11 7:45 PM, Juan Sequeda wrote:
On Sat, Apr 2, 2011 at 2:55 PM, Kingsley Idehen
<[email protected] <mailto:[email protected]>> wrote:
All,
I've knocked up a Google spreadsheet that contains stats about our
21 Billion Triples+ LOD cloud cache.
On the issue of Triple Counts, you can't make sense of Data if you
can't count it. We can't depend on SPARQL-FED for distributed
queries, and we absolutely cannot depend on a Web crawl via
follow-your-nose pattern when seeking insights or answers to
queries across massive volumes of data.
The whole BigData game is a huge opportunity for Linked Data and
Semantics to finally shine. By shine I mean: show what was
erstwhile impossible.
Exhibit #1 -- how do we Find the proverbial needle in a haystack
via ad-hoc queries at Web Scale?
Exhibit #2 -- how do we leverage faceted exploration and
navigation of massive data sets at Web Scale?
Exhibit #3 -- how do we perform ad-hoc declarative queries (Join
and Aggregates variety) that used to be confined to a local
Oracle, SQL Server, DB2, Informix, MySQL etc.., at Web Scales esp.
if the Web is now a Global Linked Data Space?
I've issued a challenge to all BigData players to show me a public
endpoint that allows me to perform any of the tasks above. Thus
far, the silence has been predictably deafening :-)
I guess you are the google of the semantic web... assuming that you
can stick in your cache hundreds of billion of triples by the end of
the year... trillions of triples next year..... etc.
This sounds plausible to me. Google did it :)
Hundreds of billions of triples boils down to the total amount of memory
we can cobble together across a cluster, bottom line.
Google has airport size data centers. We are at 21 Billion+ with an
8-node cluster endowed with 48GB RAM per node. Basically, our data
center setup is less than a rounding number when compared to theirs.
By the end of this year, you'll simply have more triples squeezed into
the same cluster config. As far as DBMS tech goes our focus boils down
to maintaining and exceeding current scale while reducing infrastructure
costs. Note, current LOD cloud cache is also based on Virtuoso 6.x
cluster engine (row based storage) rather than the 7.x engine (column
based storage) :-)
Kingsley
Links:
1.
https://spreadsheets.google.com/ccc?key=0AihbIyhlsQSxdHViMFdIYWZxWE85enNkRHJwZXV4cXc&hl=en
<https://spreadsheets.google.com/ccc?key=0AihbIyhlsQSxdHViMFdIYWZxWE85enNkRHJwZXV4cXc&hl=en>
-- LOD Cloud Cache SPARQL stats queries and results
--
Regards,
Kingsley Idehen
President& CEO
OpenLink Software
Web: http://www.openlinksw.com
Weblog: http://www.openlinksw.com/blog/~kidehen
<http://www.openlinksw.com/blog/%7Ekidehen>
Twitter/Identi.ca: kidehen
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Regards,
Kingsley Idehen
President& CEO
OpenLink Software
Web: http://www.openlinksw.com
Weblog: http://www.openlinksw.com/blog/~kidehen
Twitter/Identi.ca: kidehen
