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The seminal work of Selinger et al [1979] describes access-path selection in the System R optimizer, which was one of the earliest relational-query optimizers Graefe and McKenna [1993] describe Volcano, an equivalence-rule based query optimizer Query processing in Starburst is described in Haas et al [1989] Query optimization in Oracle is brie y outlined in Oracle [1997] Estimation of statistics of query results, such as result size, is addressed by Ioannidis and Poosala [1995], Poosala et al [1996], and Ganguly et al [1996], among others Nonuniform distributions of values causes problems for estimation of query size and cost Cost-estimation techniques that use histograms of value distributions have been proposed to tackle the problem Ioannidis and Christodoulakis [1993], Ioannidis and Poosala [1995], and Poosala et al [1996] present results in this area Exhaustive searching of all query plans is impractical for optimization of joins involving many relations, and techniques based on randomized searching, which do not examine all alternatives, have been proposed Ioannidis and Wong [1987], Swami and Gupta [1988], and Ioannidis and Kang [1990] present results in this area Parametric query-optimization techniques have been proposed by Ioannidis et al [1992] and Ganguly [1998], to handle query processing when the selectivity of query
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parameters is not known at optimization time A set of plans one for each of several different query selectivities is computed, and is stored by the optimizer, at compile time One of these plans is chosen at run time, on the basis of the actual selectivities, avoiding the cost of full optimization at run time Klug [1982] was an early work on optimization of relational-algebra expressions with aggregate functions More recent work in this area includes Yan and Larson [1995] and Chaudhuri and Shim [1994] Optimization of queries containing outer joins is described in Rosenthal and Reiner [1984], Galindo-Legaria and Rosenthal [1992], and Galindo-Legaria [1994] The SQL language poses several challenges for query optimization, including the presence of duplicates and nulls, and the semantics of nested subqueries Extension of relational algebra to duplicates is described in Dayal et al [1982] Optimization of nested subqueries is discussed in Kim [1982], Ganski and Wong [1987], Dayal [1987], and more recently, in Seshadri et al [1996] When queries are generated through views, more relations often are joined than is necessary for computation of the query A collection of techniques for join minimization has been grouped under the name tableau optimization The notion of a tableau was introduced by Aho et al [1979b] and Aho et al [1979a], and was further extended by Sagiv and Yannakakis [1981] Ullman [1988] andMaier [1983] provide a textbook coverage of tableaux Sellis [1988] and Roy et al [2000] describe multiquery optimization, which is the problem of optimizing the execution of several queries as a group If an entire group of queries is considered, it is possible to discover common subexpressions that can be evaluated once for the entire group Finkelstein [1982] and Hall [1976] consider optimization of a group of queries and the use of common subexpressions Dalvi et al [2001] discuss optimization issues in pipelining with limited buffer space combined with sharing of common subexpressions Query optimization can make use of semantic information, such as functional dependencies and other integrity constraints Semantic query-optimization in relational databases is covered by King [1981], Chakravarthy et al [1990], and in the context of aggregation, by Sudarshan and Ramakrishnan [1991] Query-processing and optimization techniques for Datalog, in particular techniques to handle queries on recursive views, are described in Bancilhon and Ramakrishnan [1986], Beeri and Ramakrishnan [1991], Ramakrishnan et al [1992c], Srivastava et al [1995] and Mumick et al [1996] Query processing and optimization techniques for object-oriented databases are discussed in Maier and Stein [1986], Beech [1988], Bertino and Kim [1989], and Blakeley et al [1993] Blakeley et al [1986], Blakeley et al [1989], and Grif n and Libkin [1995] describe techniques for maintenance of materialized views Gupta and Mumick [1995] provides a survey of materialized view maintenance Optimization of materialized view maintenance plans is described by Vista [1998] and Mistry et al [2001] Query optimization in the presence of materialized views is addressed by Larson and Yang [1985], Chaudhuri et al [1995], Dar et al [1996], and Roy et al [2000] Index selection and materialized view selection are addressed by Ross et al [1996], Labio et al [1997], Gupta [1997], Chaudhuri and Narasayya [1997], and Roy et al [2000]
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