A Comparative Study of View Update Problem

Chen, Haitao; Liao, Husheng

doi:10.1109/dsde.2010.42

Cited by 7 publications

(7 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Keller's [27] thesis is motivation the view update problem. There is a lot of papers on the view update problem (for example, the recent survey paper on view updating by Chen and Liao [14] and the survey paper on view updating algorithms by Mayol and Teniente [41] and current survey paper on view selection ( [49,3,5]). More similar to our work is the paper presented by Bessant et al [7], which introduces a local search-based heuristic technique that empirically proves to be often viable, even in the context of very large propositional applications.…”

Section: Related Workmentioning

confidence: 99%

A new rational algorithm for view updating in relational databases

Delhibabu

Behrend

2014

Appl Intell

View full text Add to dashboard Cite

Abstract. The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In order to apply the rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with stratified negation). We show that knowledge base dynamics has an interesting connection with kernel change via hitting set and abduction. In this paper, we show how techniques from disjunctive logic programming can be used for efficient (deductive) database updates. The key idea is to transform the given database together with the update request into a disjunctive (datalog) logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the original update problem. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of a hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality.

show abstract

Section: Related Workmentioning

confidence: 99%

A new rational algorithm for view updating in relational databases

Delhibabu

Behrend

2014

Appl Intell

View full text Add to dashboard Cite

show abstract

“…The view update problem is one of the classical problems in databases [15], [18], [19]. In addition, view updates are involved in recent research and applications, such as [5], [11], [20], [36]. Due to space constraints, this section only presents certain non-exhaustive representative works relevant to our approach.…”

Section: Related Workmentioning

confidence: 99%

“…Due to space constraints, this section only presents certain non-exhaustive representative works relevant to our approach. One may consult the literature for more complete reviews of the problem (e.g., [11], [30]). Previous researchers [15], [19], [29] studied the view update problem under various view definition syntaxes (e.g., select, project, acyclic join) and constraints (special forms of primary and foreign key constraints and functional dependencies) of source databases.…”

Section: Related Workmentioning

confidence: 99%

“…This is equivalent to picking the tuple segments that are most probable to form a view tuple. Minor details include (i) extending the path of maximum flow into a partial embedding, which is one set of candidate tuples (Line 12) and iteratively selecting the embeddings from the negative graph until k embeddings are selected (Lines [10][11][12][13][14], where k is a user-defined parameter.…”

Section: Candidate Tuples Selectionmentioning

confidence: 99%

See 1 more Smart Citation

Side-Effect Estimation: A Filtering Approach to the View Update Problem

Peng

Choi

et al. 2014

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

Views and their updates have long been a fundamental technology required in a wide range of applications. However, it has been known that updates through views is a classical intractable problem. In this paper, we propose a novel, data-oriented approach to this problem that provides a practical support for view updates. In particular, we propose a summarization of the source database of views, which serves as an update filter. The update filter aims to efficiently reject untranslatable view updates by estimating the side effects of the updates, thereby avoiding costly translation analysis. For applications where estimation errors are not preferred, our update filter can be tuned to be exact. In this paper, we present our approach with SPJ views, an important class of view definitions. We first revise the notion of estimation errors to quantify the filter's qualities. We then propose a novel join cardinality summary (JCard) derived from cardinality equivalence. An estimation algorithm is proposed. Finally, we present optimizations enabling the construction of an accurate JCard through heuristics and sampling. Our extensive experiments show that update filters are efficient and can be easily tuned to produce accurate estimations on TPC-H and DBLP.

show abstract

“…Keller's [62] thesis is motivation for view update problem. There is a lot of papers on view update problem (for example, recent survey paper on view update by Chen and Liao [24], survey paper on view algorithm by Mayol and Teniente [83] and current survey paper on view selection ( [38,53,73,69,79,105]). More similar to our work is paper presented by Bessant et al [16] , local search-based heuristic technique that empirically proves to be often viable, even in the context of very large propositional applications.…”

Section: Related Workmentioning

confidence: 99%

Comparative study of view update algorithms in rational choice theory

Delhibabu¹

2014

Appl Intell

View full text Add to dashboard Cite

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. We show that knowledge base dynamics has interesting connection with kernel change via hitting set and abduction. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality. Many different view update algorithms have been proposed in the literature to address this problem. The present paper provides a comparative study of view update algorithms in rational approach. ⋆ This paper extends work from Delhibabu [34] and Mayol [83] Our knowledge base dynamics is defined in two parts: an immutable part (formulae) and updatable part (literals) (for definition and properties see works of Nebel [88] and Segerberg [98]). Knowledge bases have a set of integrity constraints (see the definitions in later section). In the case of finite knowledge bases, it is sometimes hard to see how the update relations should be modified to accomplish certain knowledge base updates.Example 1. Consider a database with an (immutable) rule that a staff member is a person who is currently working in a research group under a chair. Additional (updatable) facts are that matthias and gerhard are group chairs, and delhibabu and aravindan are staff members in group info1. Our first integrity constraint (IC) is that each research group has only one chair ie. ∀x, y, z (y=x) ← group chair(x,y) ∧ group chair(x,z). Second integrity constraint is that a person can be a chair for only one research group ie. ∀x, y, z (y=z)← group chair(y,x) ∧ group chair(z,x).Immutable part: staff chair(X,Y)← staff group(X,Z),group chair(Z,Y). Updatable part: group chair(infor1,matthias)← group chair(infor2,gerhard)← staff group(delhibabu,infor1)← staff group(aravindan,infor1)← Suppose we want to update this database with the information, staff chair(aravindan,gerhard); From the immutable part, we can deduce that this can be achieved by asserting staff group(aravindan,Z) group chair(Z,gerhard)If we are restricted to definite clauses, there are three plausible ways to do this: first case is, aravindan and gerhard belong to infor1, i.e, staff group(aravindan,-info1) group chair(info1,gerhard). We need to delete both base facts group chair-(infor1,matthias)← and group chair(infor2,gerhard)←, because our first IC as well as second IC would be violated otherwise. In order to change the view, we need to insert group chair(infor1,gerhard)← as a base fact. Assume that we have an algorithm that deletes the base facts staff group(delhibabu,infor1)← from the database. But, no rational person will agree with such an algorithm, because the fact staff group(delhibabu,infor1)← is not "relevant" to the view atom.Second case, aravindan and gerhard belong to infor2, that is staff group(aravindan,info2) group chair(info2,gerhard). Simply, insert the new fact ...

show abstract

A Comparative Study of View Update Problem

Cited by 7 publications

References 28 publications

A new rational algorithm for view updating in relational databases

A new rational algorithm for view updating in relational databases

Side-Effect Estimation: A Filtering Approach to the View Update Problem

Comparative study of view update algorithms in rational choice theory

Contact Info

Product

Resources

About