Database-19-QueryProcessing.pptx

Query processing and optimization 34 using heuristics

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Query Processing and Optimization 34
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Using Heuristics in Query Optimization Query tree : A tree data structure that corresponds to a relational algebra expression. It represents the input relations of the query as leaf nodes of the tree , and represents the relational algebra operations as internal nodes. An execution of the query tree consists of executing an internal node operation whenever its operands are available and then replacing that internal node by the relation that results from executing the operation. Query graph : A graph data structure that corresponds to a relational calculus expression. It does not indicate an order on which operations to perform first. There is only a single graph corresponding to each query. Query Processing and Optimization 35
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Using Heuristics in Query Optimization Example: For every project located in ‘Stafford’, retrieve the project number, the controlling department number and the department manager’s last name, address and birthdate. Relation algebra: PNUMBER, DNUM, LNAME, ADDRESS, BDATE ((( PLOCATION=‘STAFFORD’ (PROJECT)) DNUM=DNUMBER (DEPARTMENT)) MGRSSN=SSN (EMPLOYEE)) SQL query: Q2: SELECT P.NUMBER,P.DNUM,E.LNAME, E.ADDRESS, E.BDATE FROM PROJECT AS P,DEPARTMENT AS D, EMPLOYEE AS E WHERE P.DNUM=D.DNUMBER AND D.MGRSSN=E.SSN AND P.PLOCATION=‘STAFFORD’; Query Processing and Optimization 36
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Using Heuristics in Query Optimization Query Processing and Optimization 37
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Using Heuristics in Query Optimization Heuristic Optimization of Query Trees: The same query could correspond to many different relational algebra expressions — and hence many different query trees. The task of heuristic optimization of query trees is to find a final query tree that is efficient to execute. Example: Q: SELECT LNAME FROM EMPLOYEE, WORKS_ON, PROJECT WHERE PNAME = ‘AQUARIUS’ AND PNUMBER=PNO AND ESSN=SSN AND BDATE > ‘1957-12-31’; Query Processing and Optimization 38
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Query Processing and Optimization 39
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Query Processing and Optimization 40
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Query Processing and Optimization 41
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Using Heuristics in Query Optimization General Transformation Rules for Relational Algebra Operations: 1. Cascade of : A conjunctive selection condition can be broken up into a cascade (sequence) of individual operations: c1 AND c2 AND ... AND cn (R) = c1 ( c2 (...( cn (R))...) ) 2. Commutativity of : The operation is commutative: c1 ( c2 (R)) = c2 ( c1 (R)) 3. Cascade of : In a cascade (sequence) of operations, all but the last one can be ignored: List1 ( List2 (...( Listn (R))...) ) = List1 (R) 4. Commuting with : If the selection condition c involves only the attributes A1, ..., An in the projection list, the two operations can be commuted: A1, A2, ..., An ( c (R)) = c ( A1, A2, ..., An (R)) Query Processing and Optimization 42
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Using Heuristics in Query Optimization General Transformation Rules for Relational Algebra Operations (contd.): 5. Commutativity of ( and x ): The operation is commutative as is the x operation: R C S = S C R; R x S = S x R 6. Commuting with (or x ): If all the attributes in the selection condition c involve only the attributes of one of the relations being joined—say, R—
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  • Fall '09
  • SUNANHAN
  • Query optimizer, JOIN Operations

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