Download Fundamentals of Physical Design and Query Compilation by David Toman, Grant Weddell PDF

April 4, 2017 | Storage Retrieval | By admin | 0 Comments

By David Toman, Grant Weddell

Question compilation is the matter of translating consumer requests formulated over in basic terms conceptual and area particular methods of knowing facts, ordinarily known as logical designs, to effective executable courses known as question plans. Such plans entry a number of concrete facts assets via their low-level usually iterator-based interfaces. An appreciation of the concrete info resources, their interfaces and the way such functions relate to logical layout is often known as a actual layout. This publication is an creation to the basic tools underlying database know-how that solves the matter of question compilation. The equipment are provided when it comes to first-order common sense which serves because the automobile for specifying actual layout, expressing person requests and question plans, and knowing how question plans enforce person requests. desk of Contents: advent / Logical layout and person Queries / uncomplicated actual layout and question Plans / On sensible actual layout / question Compilation and Plan Synthesis / Updating information

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Extra resources for Fundamentals of Physical Design and Query Compilation (Synthesis Lectures on Data Management)

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3). Notably, such logics underlie recent efforts on developing ontology languages for web-based data [OWL 2 Web Ontology Language: New Features and Rational, 2009]. 5 EXERCISES WITH TOPICS FOR DISCUSSION Explore how our user queries and query semantics might be embellished to enable users to express ordering and ranking criteria. One complication with the current semantics is a consequence of not imposing any conditions on an interpretation beyond the fact that it satisfies a logical design. This make it possible for the number of n-tuples comprising the evaluation of a query to not be finite.

Ql , where each Qi is a conjunctive query for which Fv(Qi ) = Fv(Q). Finally, we write Q{x1 , . . , xn } as shorthand to indicate that Param(Q) = {x1 , . . , xn }, or more simply just Q if Param(Q) = ∅. (query semantics) Let I denote an interpretation of S. The evaluation of Q with respect to I , written Q(I ), is given by { V (x1 ), . . , V (xn ) ∈ ( I )n | I , V |= Q}, where (x1 , . . , xn ) where is the lexicographic ordering of Fv(Q). ✷ Thus, a given n-tuple e1 , . . , en ∈ ( I )n occurs in the evaluation of a user query Q with respect to an interpretation I if and only if there exists a valuation V over I such that I , V [x1 → e1 ] · · · [xn → en ] |= Q, where (x1 , .

The next section more carefully defines what it means to execute a query plan and what it means for a query plan to implement a user query. The final section 22 3. BASIC PHYSICAL DESIGN AND QUERY PLANS introduces the remaining operators for our plan language in an incremental fashion, starting with the introduction of operations that can express conjunctive query plans. 1 ACCESS PATHS AND SIMPLE SCANNING Assume that ACME’s DBA department has settled on a very simple physical design for payroll in which all employee information is recorded in a main-memory array.

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