## Answering Queries: Tractable Cases and Optimizations (2001)

Citations: | 2 - 1 self |

### BibTeX

@TECHREPORT{Scarcello01answeringqueries:,

author = {Francesco Scarcello},

title = {Answering Queries: Tractable Cases and Optimizations},

institution = {},

year = {2001}

}

### OpenURL

### Abstract

Answering queries is computationally very expensive, and many approaches have been proposed in the literature to face this fundamental problem. Some of them are based on optimization modules that exploit quantitative information on the database instance, while other approaches exploit structural properties of the query hypergraph. For instance, acyclic queries can be answered in polynomial time, and also query containment is efficiently decidable for acyclic queries. In this report, we review both quantitative and structural methods for optimizing query answering and identifying tractable classes of queries. Moreover, we provide a formal comparison of structural methods.

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Citation Context ...ing induced widthsk can be also characterized as partial k-trees [21] or, equivalently, as graphs having treewidthsk [2]. It follows that, for fixed k, checking whether wsk is feasible in linear time =-=[8]-=-. The approach based on w is referred to as the w -Tractability method [13]. Note that this method is implicitly based on hypergraph acyclicity, given that the used triangulation methods enforce chord... |

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Citation Context ...algorithms have already been developed for query optimization in database systems. All algorithms proposed so far fall into one of three different classes or are combinations of such basic algorithms =-=[60]-=-. In the following, we will briefly discuss each class of algorithms; a more complete overview and comparison of many of the existing algorithms can be found in [59]. 3.1 Exhaustive search All publish... |

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Citation Context ...xpensive than an optimal plan. 3.4 Iterative Dynamic Programming This technique is based on iteratively applying dynamic programming and can be seen as a combination of dynamic and greedy programming =-=[44]-=-. The essence of this heuristic is that instead of fully enumerating all query processing plans, a resource limit is established (defined by a parameter k). During each dynamic programming stage, all ... |

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Citation Context ...this class have polynomial time and space complexity, but they they typically produce worse plans [59]. Representatives of this class of algorithms are minimum selectivity and other greedy algorithms =-=[60, 58, 59]-=-, the KBZ algorithm [45]; and the AB algorithm [62]. Basically, at each step, a partially determined order is extended by choosing the most promising relational operation to be executed, according to ... |

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Citation Context ...hey they typically produce worse plans [59]. Representatives of this class of algorithms are minimum selectivity and other greedy algorithms [60, 58, 59], the KBZ algorithm [45]; and the AB algorithm =-=[62]-=-. Basically, at each step, a partially determined order is extended by choosing the most promising relational operation to be executed, according to some preference criterion. Obviously, the quality o... |

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Citation Context ...[65]. Other representatives of this class are A* search [41] and transformation-based techniques (with top-down dynamic programming) such as those used in EXODUS, Volcano, and some commercial systems =-=[30, 31, 52]-=-. 3.2 Heuristics Typically, the algorithms of this class have polynomial time and space complexity, but they they typically produce worse plans [59]. Representatives of this class of algorithms are mi... |

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Citation Context ...[59], for a discussion about "left-deep vs. bushy" (see, e.g.,). Efficient ways to implement dynamic programming have been proposed in [49] and [65]. Other representatives of this class are =-=A* search [41]-=- and transformation-based techniques (with top-down dynamic programming) such as those used in EXODUS, Volcano, and some commercial systems [30, 31, 52]. 3.2 Heuristics Typically, the algorithms of th... |

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Citation Context ...ant and best studied class of tractable queries is the class of acyclic queries [7, 11, 12, 17, 18, 24, 42, 48, 50, 54, 55, 68, 70]. It was shown that acyclic queries coincide with 1 the tree queries =-=[4]-=-, see also [1, 47, 64]. The latter are queries which are representable by a join tree (or join forest) (see Section 4.2, for a formal definition). By well-known results of Yannakakis [68], acyclic con... |