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by: Trace Mante MD


Trace Mante MD

GPA 3.61

Lm Stephens

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Lm Stephens
Class Notes
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This 29 page Class Notes was uploaded by Trace Mante MD on Monday October 26, 2015. The Class Notes belongs to CSCE 520 at University of South Carolina - Columbia taught by Lm Stephens in Fall. Since its upload, it has received 31 views. For similar materials see /class/229578/csce-520-university-of-south-carolina-columbia in Computer Science and Engineering at University of South Carolina - Columbia.

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Date Created: 10/26/15
Information Integration Mediators Warehousing Answering Queries Using Views Example Applications 1 Enterprise Information Integration making separate DB s all owned by one company work together 2 Scientific DB s eg genome DB s 3 Catalog integration combining product information from all your suppliers ChaHenges J Legacy databases DB s get used for many applications 9 You can t change its structure for the sake of one application because it will cause others to break 2 Incompatibiltes Two supposedly similar databases will mismatch in many ways Examples Incompatibilities OLeXcal addr in one DB is address in another 9 Value mismatches is a red car the same color in each DB Is 20 degrees Fahrenheit or Centigrade OSemantc are employees in each database the same What about consultants Retirees Contractors What Do You Do About It OGrubby handwritten translation at each interface 0 Some research on automatic inference of relationships 9 Wrapper aka adapter translates incoming queries and outgoing answers J 2 Integration Architectures Federation everybody talks directly to everyone else Warehouse Sources are translated from their local schema to a global schema and copied to a central DB Mediator Virtual warehouse turns a user query into a sequence of source queries Federations Warehouse Diagram A Mediator User query Result Two Mediation Approaches J Global as View Mediator processes queries into steps executed at sources 2 Local as View Sources are defined in terms of global relations mediator finds all ways to build query from views 10 Example Catalog Integration OSuppose Dell wants to buy a bus and a disk that share the same protocol OGlobal schema Busesmanfmodelprotocol Disksmanfmodelprotocol OLocal schemas each bus or disk manufacturer has a modelprotocol relation manf is implied 11 Example GIobaIasView OMediator might start by querying each bus manufacturer for modelprotocol pairs o The wrapper would turn them into triples by adding the manf component OThen for each protocol returned mediator queries disk manufacturers for disks with that protocol o Again wrapper adds manf component 12 Example LocalasView OSources capabilities are defined in terms of the global predicates o EgQuantum s disk database could be defined by QuantumViewMP Disks Quantum MP OMediator discovers all combinations of a bus and disk view equijoined on the protocol components 13 A Harder LAV Case OThe mediator supports a parcp relation which doesn t really exist but can be queried OSources can support views that are complex expressions of par 9A logic is needed to work with queries and view definitions o Datalog is a good choice 14 Example Some Local Views OSource 1 provides some parent facts V1cp lt parcp OSource 2 run by the Society of Grandparents supports only grandparent facts V2cg lt parcp AND parpg 15 Example 2 OQuery greatgrandparents ggpcx lt parcu AND paruv AND parvX OHow can the sources provide solutions that provide all available answers 16 Example 3 So1cX lt V1cu AND V1uv AND V1uX So2cX lt V1cu AND V2uX So3cX lt V2cv AND V1vX 9N0 other queries involving the views can provide more ggp facts ODeep theory needed to explain 17 Comparison LAV Vs GAV OGAV is simpler to implement o Lets you control what the mediator does OLAV is more extensible o Add a new source simply by defining what it contributes as a view of the global schema 0 Can get some use from grandparent info even if parcp is the only mediator data 18 Course Plug OIn the Spring 0708 Alon Halevy Google is teaching CS345C Information Integration OIt will cover this technology and many others 19 Datalog Logical Rules Recursion Logic As a Query Language OIf then logical rules have been used in many systems 0 Important example EII Enterprise Information Integration ONonrecursive rules are equivalent to the core relational algebra ORecursive rules extend relational algebra and appear in SQL99 Example Enterprise Integration OGoal integrated view of the menus at many bars Sellsbar beer price OJoe has data JoeMenubeer price OApproach 1 Describe Sells in terms of JoeMenu and other local data sources Sells Joe s Bar b p lt JoeMenub P EII 2 OApproach 2 Describe how JoeMenu can be used as a view to help answer queries about Sells and other relations JoeMenub p lt Sells Joe s Bar b p OMore about information integration later A Logical Rule OOur first example of a rule uses the relations Frequentsdrinker bar Likesdrinker beer and Sellsbar beer price OThe rule is a query asking for happy drinkers those that frequent a bar that serves a beer that they like Anatomy of a Rule Head consequent Body antecedent a smgle subgoal AN D of subgoas Read this symbol if Subgoals Are Atoms OAn atom is a predicate or relation name with variables or constants as arguments OThe head is an atom the body is the AND of one or more atoms OConvention Predicates begin with a capital variables begin with lowercase Example Atom The predicate Arguments are name of a variables or constants relation Interpreting Rules 9A variable appearing in the head is distinguished otherwise it is nondistinguished ORule meaning The head is true for given values of the distinguished variables if there exist values of the nondistinguished variables that make all subgoals of the body true


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