Hello Paul,

These are the informtion i have

1) R2RML mapping for existing DB

2) I have some fedreated queries which hit the triple store containg the data 
which has been loaded from the DB

The Loading  data from DB (100 tables, millions of rows) to TS takes a long 
time. I need a framework to convert Sparql to SQL which will hit the table and 
return RDF result set.

D2RQ is in version .81 and hasn’t changed much. Not sure whether D2RQ is the 
right approach.

Thanks
Kamalraj




--
Kjairam
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On 31 March 2014 at 6:59:20 am, Paul Tyson 
([email protected]<mailto:[email protected]>) wrote:

On Sun, 2014-03-30 at 09:37 +0000, Kamalraj Jairam wrote:
> Hello All,
>
> Whats the best way to convert sparql to SQL using R2RML mappings
>
> and convert resultset from DB to RDF?
>

What are the givens? Do you have existing SPARQL text written against
some RDF produced by some existing R2RML mappings? Or do you have some
SPARQL and some SQL and you want to fill in the R2RML and produce some
RDF?

In any case, it is an interesting scenario that will arise more often as
companies expand their use of RDF while relying mostly on SQL.

There is a higher abstraction that should be explored and possibly
exploited to provide a general pattern for working through these
situations. Since SQL, SPARQL, and R2RML are rule languages compatible
with relational algebra (RA), it should be possible to derive a common
set of RA predicates and classes to create an RDF vocabulary. This
vocabulary can then be used to write queries as production rules in a
generic standard rule language, such as RIF (Rule Interchange Format).
The RIF source can be translated to SQL, SPARQL, or R2RML for execution
in the target system.

Going from RIF to SQL, SPARQL, or R2RML is always going to be easier
than starting from SQL or SPARQL and going to some other format.
Theoretically you should be able to partially translate R2RML to RIF
automatically (SQL embedded in the R2RML will still be opaque). But I
don't know what tools could be used to translate SQL and SPARQL texts to
generic production rules using an RA vocabulary.

The ultimate payoff from this approach is that it will be possible to
link all of your data relations and operations with meaningful business
terminology and processes. It will enable greater visibility and control
of all data operations, and put important elements of business logic in
transparent rules (e.g. RIF) instead of arcane notations such as SQL
SPARQL (or worse, procedural code).

Regards,
--Paul

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