Support LDF endpoint?

With this we could encourage people writing queries to offload to LDF when possible and do more computing locally now that WDQS expensive SPARQL endpoint receives >100.000 queries a second.

see https://github.com/pchampin/hydra-py for a Triple Patterns Fragments client
example code:

"""
Use TPFStore and performs a SPARQL query on top of it.
Note that this is very (very!) slow as soon as the query becomes slightly complex... :-/
"""
import logging
from rdflib import Graph
import sys
logging.basicConfig(level=logging.INFO)

import hydra.tpf # required to register TPFStore plugin

URL = 'http://data.linkeddatafragments.org/dbpedia2014'
if len(sys.argv) > 1:
    URL = sys.argv[1]

g = Graph("TPFStore")
g.open(URL)

QUERY = """
    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
    PREFIX dbr: <http://dbpedia.org/resource/>
    PREFIX dbo: <http://dbpedia.org/ontology/>

    SELECT * {
        ?p a dbo:Person; dbo:birthPlace ?bp .
    }
    LIMIT 10
"""

print len(g)

results = g.query(QUERY)
for i in results:
    print i

Start by reviewing the hydra-py TPFStore example and the repository's existing Wikibase SPARQL endpoint integration. Determine the intended LDF endpoint configuration and query behavior from the issue discussion. Done means the module supports querying through an LDF endpoint, with coverage for the intended usage.