Algebraic Optimization of RDF Graph Pattern Queries on MapReduce - Large Scale and Big Data: Processing and Management - page 198

(& V 1, label ,
(& V 1, country ,
(& V 1, homepage ,

Vendor1),
US),
www.vendors.org/V1)

nt =

(& V 1, label , Vendor1, & V 1, country , US, & V 1, homepage , www.vendors.org/V1)

tg =

t 1 t 2 t 3

(a) Subject TripleGroup tg (b) n-tuple after tg. flatten()

(& Off 1, price ,
(& Off 1, product ,
(& Off 1, validFrom ,
(& Off 1, vendor ,
(& V 1, label ,
(& V 1, country ,
(& V 1, homepage ,

1008),
& Pr 1)
07/11/2012)
& V 1)
Vendor1),
US),
www.vendors.org/V1)

(& Off 1, price ,
(& Off 1, product ,
(& Off 1, validFrom ,
(& Off 1, vendor ,

1008),
& Pr 1)
07/11/2012)
{(& V 1, label ,
(& V 1, country ,

untg =

ntg =

Vendor1),
US),
(& V 1, homepage , www.vendors.org/V1)

(c) Nested TripleGroup ntg (d) ntg.unnest()

FIGURE 6.6 Examples of (a) Subject TripleGroup tg , (b) corresponding lattened n-tuple, (c) Nested TripleGroup ntg , and (d) corresponding unnested

TripleGroup.