Local as View: Some refinements

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Local as View Some refinements

• IM Filtering irrelevant sources
• Views with restricted access patterns
• A summary of IM

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IM Filtering irrelevant sources

• When there are many sources, it is important to
  weed out those that are irrelevant to a query
• Comparison constraints can help (e.g., qu gt w98)
• What more can be done?
• The IM system suggests to introduce
• classes with a class hierarchy
• into source descriptions

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• Example
• -- disjoint classes
• Additionally, the global schema contains a
  relation
• details(car, year, mileage, price, sellerContact)
• c, y, mi, p,
  s
• (we will also abbreviate class names)

car
usedCar
AmericanCar
EurpoeanCar
JapaneseCar
carForSale
newCar
GermanCar
ItalianCar
FrenchCar
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• The views
• v1(c, y, mi, p, s) - details(c,y,mi,p,s),
  cFSale(c), uCar(c), ,y gt 1990
• v2(c, y, p, s) - details(c,y,mi,p,s) ,
  cFSale(c), EurCar(c)
• v3(c, y, p, s) - details(c,y,mi,p,s),
  cFSale(c), uCar(c), pgt 25000 // luxury cars
• v4(c, y, p)- details(c,y,mi,p,s), cFSale(c),
  uCar(c), ylt 1980 //vintage cars
• v5(c, y, p, s) - details(c, mc, y, p, s),
  cFSale(c), nCar(c), cToyota
• Assume a query
• Q q(c, mc, y, p, s) - details(c, y, mi, p, s)
  , cFSale(c), Jcar(c),
  ygt 1992 , plt 12000
• Some candidate rewritings will be rejected, since
  they are inconsistent with Q

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• When a view is considered for consistency with
  Q,
• v4 will be discarded ylt1980, ygt1992 is
  inconsistent
• v3 will be discarded pgt25000, plt12000 is
  inconsistent
• v2 will be discarded EurCar(c), JCar(c) is
  inconsistent
• v5 depends on what is known about the
  relationship between Toyota and the various car
  classes
• Reasoning about disjoint-ness of classes (given a
  hierarchy as above) is easy and efficient

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The true story (a side trip) IM uses a (PTIME)
Description Logic for source description A DL is
a formalism that describes
classes binary relationships
intentionally. For example, a
class can be given by a name (e.g. JCar) or by an
expression that describes its properties
cheapJCar - uCar and JCar and price lt 9000 A DL
also contains containment and disjoint-ness
axioms for class expressions (containment is
called subsumption in DL jargon) To be useful, a
DL needs to support containment and disjoint-ness
queries on classes and membership queries on
individuals this is an inference problem
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Many DLs are known Complexity (for subsumption)
ranges from polynomial (rare), to NP-complete,
to exptime-complete, to undecidable Recent
interest focuses on using DLs for the Semantic
Web The W3C OWL standard is essentially a
DL (this use is essentially the same as in IM)
That is it on DLs
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Views with restricted access patterns

• Many sources do not support full SQL
• They are legacy systems, e.g.
• finger on UNIX accepts email, returns other
  attributes
• A bibliography source requires author, or title,
  or but does not accept a year as input
• They do not want to disclose all their data,
  e.g.,
• a carSale source will not present all the cars it
  has for sale
• An airline requires from and destination as input
  for flight info
• The questions
• How do we describe such sources?
• What are good rewritings and do we find them?

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• Restricted sources can be described by binding
  patterns
• Two equivalent styles (there are more
  sophisticated schemes)
• Example assume global relations
• email(F, L, E), office(F, L, O), phone(O, P)
  
• (F-first, L-last, E-email,
  O-office, P-phone)
• The views are finger, userId, described as
  follows
• Adding to attributes that can be given as input
• finger(F, L, E, O, P) - email(F, L, E),
  office(F, L, O), phone(O, P)
• userId(O, E) - office(F, L, O),
  email(F, L, E)
• Using b, f strings on predicates, where b means
  bound (i.e., in)
• fingerffbff(F, L, E, O, P) - email(F, L,
  E), office(F, L, O), phone(O, P)
• userIdbf(O, E) - office(F, L, O),
  email(F, L, E)

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• Example, contd
• Q qbf(O, F) - office(F, L, O) (or q(O, F)
  - office(F, L, O) )
• Cannot be answered by using finger it requires
  E as input
• Cannot be answered by using userId it does not
  return F
• The following is a good rewriting
• q(O, F)- userId(O, E), finger(F, L, E, O,
  P) jump
• For two reasons
  
• It is executable with respect to the sources
  executing the body left-to-right respects the
  access restrictions
• O for userId from the query, E for finger
  from userId
• Its expansion is contained in the query (check!)

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• These two reasons are a characterization of a
  good rewriting
• It is executable with respect to the sources
  executing the body left-to-right respects the
  access restrictions
• Its expansion is contained in the query (check!)
• Indeed
• If it is not a contained rewriting, then being
  executable is no good
• Being contained but not executable is also no
  good

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The IM approach After a rewriting is found to be
consistent and contained, it is checked for being
executable can the sub-goals in the body be
ordered so that the input required for each is
supplied from the query or the sub-goals to its
left
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A summary of IM

• Introduced (with other concurrent systems) the
  notion of LAV and query rewriting using views
• Also, detailed source descriptions using DLs
• An efficient algorithm for finding contained and
  executable rewritings
• Worked well, for about 100 sources

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Here is a graph from the paper
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• But
• The fact that a contained rewriting needs a
  number of views at most the number of atoms in
  the query has been proved only for CQs , without
  
• comparisons,
• access restrictions
• constraints on the global db
• Does it hold for these cases? (see example in p.
  10)
• For access restricted sources, it has been proved
  that for equivalent rewritings one needs at most
  nm views, where n is the number of atoms in the
  query, m is the number of different variables in
  it
• The proof does not hold for contained rewritings

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• Even for pure CQs, is the bucket algorithm
  guaranteed to find all rewritings?
• The answers to all these questions are negative!
• The bucket algorithm does not find all rewritings
• For the more general cases, longer rewritings are
  needed actually, there may be an infinite number
  of them, with no bound on length
• There is a need for another approach