A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. VLDB, 1994.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....expressions, it requires a simple cost model that can predict the cardinalities of intermediate results. Such a cardinality estimate draws heavily on a selectivity model. As such, selectivity estimation has been subject to extensive research [9, 66, 42, 30, 39, 11, 32, 20, 45, 10] 9 In [25, 38] predicate reordering techniques have been proposed that are even more sophisticated. NF databases require a more sophisticated optimizer in general since the NF paradigm allows nesting of relations [52] This also holds for OO databases. As mentioned in Section 2 the modern day DBMS ....

A.Y. Levy, I.S. Mumick, and Y. Sagiv. Query Optimization by Predicate Move-Around. In Proceedings of the 20th VLDB Conference, 1994. 12

....performance improvements for queries with selective conditions. Related work on datacube computation is described in Section 3.2. Work on reasoning with aggregation constraints is described in [LM96, RSSS98] The idea of moving predicates for query optimization has been investigated in [LMS94] The monotonic properties of aggregations has been studied in [RS97a] 72 Chapter 4 Serving Datacube Tuples from Main Memory 4.1 Introduction Most OLAP systems precompute some or all of these aggregates to answer queries as quickly as possible. To answer all possible queries over the ....

A. Levy, I. Mumick, and Y. Sagiv. Query optimization by predicate movearound. In Proceedings of the 20th International Conference on Very Large Databases, Santiago, September 1994.

....or by applying heuristics to the semantics of queries. 4.2.1 Database query optimization Many authors have explored the eld of database query optimization and come up with di erent techniques for evaluating queries as eciently as possible. We will highlight a few of these methods here. In [LMS94], an optimization called Predicate Move Around is presented. This method works by moving predicates across query blocks that cannot be merged into one block. As such, it is an extension of the more traditional predicate pushdown technique, in which selection predicates are pushed down the query ....

....pushdown technique, in which selection predicates are pushed down the query graph, in order to evaluate theese selections as early as possible during evalution. This early selection narrows the search space for the rest of the query evaluation, thus reducing cost. The technique presented in [LMS94] is a generalization of predicate pushdown that is capable of pushing predicates down, up and sideways in the query graph. As a result predicates that appear in one part of the graph can be moved around and applied in other parts of the graph. For the full algoritm we recommend reading the ....

A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proceedings of the 20th VLDB Conference, Santiago, Chile, 1994.

....is unlike injectivity in that it holds of two predicates rather than of individual functions. As with the previous example, the transformations discussed here are not new many are implemented in commercial database systems and some were proposed in the context of relations by Levy et al. in [19]. What is new is their expression with declarative rules that simplifies their verification and extension. A predicate is stronger than a predicate , is stronger( if always implies , More formally, for any predicates and over objects of type , is stronger(p, ....

....to st u . Example 2: Whereas the previous example used predicate strength to avoid invoking predicates unnecessarily, the following examples add predicates to queries to make them more efficient to evaluate. These examples evoke the spirit of the predicate move around transformations of [19]. The OQL query below joins senators from collections and A who have served the same number of terms such that the senator from has served more than 5 terms. As this query stands, it likely would be evaluated by first filtering senators in to include only those who have served more than 5 ....

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A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proceedings of the 20th VLDB Conference, pages 96--107, Santiago, Chile, September 1994.

....set of types belonging to the set SourceSchema, denoting all the types found in the data sources, are treated as source nodes of a graph. For the rest of the types, we can derive an SQL expression by using existing view reduction algorithms, such as [33] corrected with the results of [19, 44, 45] [14, 11, 41, 48, 36]. Our algorithm is applicable to graphs of activities that do not involve updates. In most cases, an update operation can be considered as the combination of insertions and deletions or as the application of the appropriate function to the relevant attributes. The results of the application of ....

A. Levy, I. Mumick, Y. Sagiv. Query Optimization by Predicate Move-Around. In Proc. 20 th Intl. Conf. on Very Large Data Bases (VLDB), pp. 96-107, Chile (1994).

....physical algebra at the physical layer. Most systems do not use a cost function at this level but just (simple) heuristics that usually produce better expressions than the initial input. Commonly known heuristics are: push select project down or the more sophisticated predicate move around [HS93, LMS94, Hel98] most restrictive join rst. Logical algebra to physical algebra translator This stage aims at translating the logical algebra expression into the most ecient program at the physical level. It is usually at this stage that a cost model of the physical layer is used to nd the cheapest ....

Alon Y. Levy, Inderpal Singh Mumick, and Yehoshua Sagiv, Query Optimization by Predicate Move-Around, 20th VLDB Conference, Santiago, Chile, 1994, VLDB, 1994.

....Dayal [Day87] ffl Magic Sets [MP92, SPL96, SHP 96b] ffl Cluet and Moerkotte [CM95, CM93] ffl Steenhagen [SABd94] 7. 4 Semantic Optimization and Handling Foreign Functions ffl Zdonik [HZ80] ffl Aberer [AF95] ffl Chaudhuri and Kim [CS96, CS93] ffl Conjunctive Predicates [HS93, Hel94, LMS94] ffl Avoiding sorting [SSM96] ffl Semantics and Cost Estimation [NCN97] 7.5 Plan Languages, Partial Evaluation and Dynamic Optimization ffl Exodus Volcano [CDG 90, GM93] ffl OPA [DGK 91, Gra95] ffl Opt [KD] ffl Graefe Cole Ward [GW89, CG94] ffl Ioannidis [INSS92] ffl Adaptive ....

Alon Y. Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate move-around. In Proceedings of the 20th VLDB Conference, pages 96--107, Santiago, Chile, September 1994.

....Thus, if there are no joins in a query, then the only improvement introduced by query unnesting would come from moving predicates between the inner and outer query, which may result in more selective unnest operations. Since predicate move around has already been shown to be e ective by others [Levy et al. 1994; Mumick et al. 1990] we decided to do benchmarks over queries with joins, by translating outer joins into outerblock nested loops. This modi cation was accomplished mainly by mapping path expressions, such as e.dept.instructors in Query 2, into pointer joins between class extents. This ....

....algorithms that perform better than the default nested loop evaluation of embedded queries. Examples of such methods include magic decorrelation [Mumick et al. 1990] which promotes predicates in the inner loop of the nested loop evaluation of correlated queries, and predicate move around [Levy et al. 1994], which moves predicates around the query graph. Our decorrelation algorithm not only moves predicates to the right place, it also intermixes operators between outer and inner queries, thus supporting more possibilities for join permutations, which may lead to better plans. Our query unnesting ....

Levy, A., Mumick, I., and Sagiv, Y. 1994. Query Optimization by Predicate MoveAround. In Proceedings of the 20th VLDB Conference, Santiago, Chile (Sept. 1994), pp. 96-107.

....to deciding view relevance [5] However, so far as we are aware, such logics have not yet been used to reason about duplicate elimination in query plans. Conversely, many proposals have utilized functional dependencies and foreign key constraints to optimize queries, e.g. for predicate movement [16], as a supplement to Magic Set optimization for bag semantics [18] for optimization of joins and semi joins [19] or for decorelation of complex queries [22] and other more general integrity constraints to optimize queries [12] This paper links the e orts seeking ecient decision procedures for ....

Alon Y. Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query Optimization by Predicate Move-Around. In 20th International Conference on Very Large Data Bases, pages 96-107, 1994.

....new evaluation algorithms that perform better than the default nested loop evaluation of embedded queries. Examples of such methods include magic decorrelation [MFPR90] which promotes predicates in the inner loop of the nested 41 loop evaluation of correlated queries, and predicate move around [LMS94] which moves predicates around the query graph. Our decorrelation algorithm not only moves predicates to the right place, it also intermixes operators between outer and inner queries, thus supporting more possibilities for join permutations, which may lead to better plans. Our query unnesting ....

A. Levy, I. Mumick, and Y. Sagiv. Query Optimization by Predicate Move-Around. In Proceedings of the 20th VLDB Conference, Santiago, Chile, pages 96-107, September 1994.

.... our optimizations for range queries and hierarchies are discussed in [16] Other algorithms for computation of the datacube are described in [1] Work on reasoning with aggregation constraints is described in [10, 12] The idea of moving predicates for query optimization has been investigated in [11]. The monotonic properties of aggregations has been studied in [13] ....

A. Levy, I. Mumick, and Y. Sagiv. Query optimization by predicate movearound. In Proceedings of the 20th International VLDB Conference, Santiago, 1994.

....the rest of the types, we can derive an SQL expression by using existing view reduction algorithms. Several complementary proposals exist such as [Kim82 corrected with the results of GaWo87, Mura89, Mura92 (which we will mention as Kim82 in the sequel) Daya87] ChSh96] MFPR90] PiHH92] [LeMS94]. The proposed algorithm is applicable to graphs of activities that do not involve updates. In most cases, an update operation can be considered as the combination of insertions and deletions or as the application of the appropriate function to the relevant attributes. Vassiliadis, Quix, ....

....MINUS P[i] out.d expr End for End Where Reduce(expr) 1. Use the technique of [MFPR90] to represent SQL queries; if self references exist (e.g. in the case of DEL statements) discriminate between multiple occurrences of the same table. 2. Use the reduction techniques of [PiHH92] Kim82 ] [LeMS94] wherever applicable to reduce the query definition to a compact form. Fig. 11. Algorithm for extracting the definition of a type in the repository We have not implemented this algorithm in ConceptBase yet, although external programs could easily do this. Suppose that we apply the algorithm to ....

A. Levy, I. Mumick, Y. Sagiv. Query Optimization by Predicate MoveAround. In 20 th VLDB Conference, Chile, 1994.

....early on. One line of research has concentrated on extending the traditional selection propagation techniques to nested queries. In these approaches, traditional optimizers are enhanced with additional execution plans, where selection and join predicates are applied as early as possible [MFPR90a, MFPR90b, MPR90, LMS94]. Another line of work has proceeded in an orthogonal direction, introducing execution plans which correspond to alternative structures of nesting. In particular, these approaches consider the possibilities of merging query blocks, denesting queries, and commuting aggregation blocks with joins ....

....joins [Day87, GW87, Kim82, Mur92, PHH92, YL94, HG94] In this paper we propose an approach which unifies and generalizes the approaches mentioned above. We apply the selection propagation idea to certain data dependencies that are implicit in aggregation blocks. Propagation of SQL predicates [MFPR90a, MFPR90b, MPR90, LMS94] is a special case of propagation of these dependencies. At the same time, propagating these 1 dependencies can produce execution plans with alternative nesting structure, as in [Day87, GW87, Kim82, Mur92, PHH92, YL94, HG94] In addition to expressing in a common framework previously proposed ....

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A. Levy, I. Mumick, Y. Sagiv. Query optimization by predicate move-around. In VLDB 1994.

....that use exists, in, and more involved SQL constructs. ffl Carry out experimental performance studies. ffl Explore how to eliminate preexisting aggregations. It is different from eliminating the optional GPs introduced by GP pushdown. ffl Integrate our technique with predicate move around [LMS94] to see if the tighter constraints derived by their algorithms can be used by our algorithm. ffl It appears that GPs can be used for doing constraint checking and data warehousing [Z 94] efficiently. We are investigating this relationship currently. Acknowledgements We would like to thank ....

Alon Levy and Inderpal Singh Mumick and Yehoshua Sagiv. Query Optimization by Predicate Movearound. In VLDB 1994, pp: 96-107.

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A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. VLDB, 1994.

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A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. of VLDB, pages 96--107, 1994.

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Alon Y. Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate move-around. In Proceedings of the 20th VLDB Conference, Santiago, Chile, pages 96--107, 1994.

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Alon Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate movearound. In Bocca et al. VLDB, pages 96--107, 1994.

....flat relations. In particular, we show that containment is decidable for queries with arbitrary nesting of aggregation with uninterpreted aggregate functions as long as we do not perform joins or selections on aggregated columns. Previous work on optimization of queries with aggregation (e.g. [Day87, CS94, LMS94, RSSS94, LM96]) has focussed on providing transformation rules that can be applied to queries and conserve equivalence. However, equivalence and containment tests were not considered. Finite Model Theory Our containment algorithm for complex objects is based on a procedure for checking simulation on ....

Alon Y. Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate move-around. In Proceedings of the 20th VLDB Conference, Santiago, Chile, pages 96--107, 1994.

No context found.

Alon Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate movearound. In Bocca et al. VLDB, pages 96--107, 1994.

.... predicates, one of which is MAX(B) 10, and MAX(B) is the only aggregation column appearing in Sel(Q) then the predicate B 10 can be conjoined to the predicates in Conds(Q) In these two examples, the predicates A 5 and MAX(B) 10 can also be removed from GConds(Q) Several authors (e.g. [LMS94, RSSS95, LMS96]) have considered the problem of inferring conditions that can be conjoined to Conds(Q) given the conditions in GConds(Q) and removing redundant conditions in GConds(Q) These techniques can be applied to rewrite the query Q, as a pre processing step yielding possibly modified conditions Conds(Q) ....

Alon Y. Levy, Inderpal S. Mumick, and Yehoshua Sagiv. Query optimization by predicate move-around. In Proceedings of the International Conference on Very Large Databases, Santiago, Chile, September 1994.

No context found.

Alon Levy, Inderpal Singh Mumick, and Yehoshua Sagiv. Query optimization by predicate movearound. In Bocca et al. VLDB, pages 96--107, 1994.

No context found.

A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. of VLDB, pages 96--107, 1994.

No context found.

A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In VLDB, 1994.

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A. Y. Levy, I. S. Mumick, and Y. Sagiv. Query optimization by predicate move-around. In Proc. of VLDB, pages 96--107, Santiago, Chile, 1994.

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