MiniCon: A scalable algorithm for answering queries using views

Pottinger, Rachel; Halevy, Alon

doi:10.1007/s007780100048

Cited by 214 publications

(99 citation statements)

References 29 publications

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“…In addition, the algorithm does not use the fact that if a view can be used to cover a query subgoal using a view variable that is not exported in the head of the view, then the view has to cover all the query subgoals that use the corresponding query variable. Based on these observations, a new algorithm, called MiniCon, was developed to make the rewriting process significantly more efficient [14]. A similar idea was used in the shared-bucket-variable (SVB) algorithm [13].…”

Section: Consider the Following Materialized Views Defined On The Basmentioning

confidence: 99%

Rewriting Queries Using Views

Li¹

2018

Encyclopedia of Database Systems

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DEFINITIONGiven a query on a database schema and a set of views over the same schema, the problem of query rewriting is to find a way to answer the query using only the answers to the views. Rewriting algorithms aim at finding such rewritings efficiently, dealing with possible limited query-answering capabilities on the views, and producing rewritings that are efficient to execute. HISTORICAL BACKGROUNDQuery rewriting is one of the oldest problems in data management. Earlier studies focused on improving performance of query evaluation [9], since using materialized views can save the execution cost of a query. In 1995, Levy et al. [10] formally studied the problem and developed complexity results. The problem became increasingly more important due to new applications such as data integration, in which views are used widely to describe the semantics of the data at different sources and queries posed on the global schema. Many algorithms have been developed, including the bucket algorithm [11] and the inverse-rules algorithm [15,7]. See [8] for an excellent survey. SCIENTIFIC FUNDAMENTALSFormally, a query Q 1 is contained in a query Q 2 if for each instance of their database, the answer to Q 1 is always a subset of that to Q 2 . The queries are equivalent if they are contained in each other. Let T be a database schema, and V be a set of views on T . The expansion of a query P using the views in V, denoted by P exp , is obtained from P by replacing all the views in P with their corresponding base relations. Given a query Q on T , a query P is called a contained rewriting of query Q using V if P uses only the views in V, and P exp is contained in Q as queries. P is called an equivalent rewriting of Q using V if P exp and Q are equivalent as queries.Examples: Consider a database with the following three relations about students, courses, and course enrollments:Student(sid, name, dept); Course(cid, title, quarter); Take(sid, cid, grade). Consider the following query on the database:Query Q1: SELECT C.title, T.grade

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Section: Consider the Following Materialized Views Defined On The Basmentioning

confidence: 99%

Rewriting Queries Using Views

Li¹

2018

Encyclopedia of Database Systems

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“…Our authorization model is similar to the view based authorization, and it is related to the area of answering queries using views [12], [10], [19]. These techniques are useful for query optimization, data integration and so on.…”

Section: Related Workmentioning

confidence: 99%

Access Rule Consistency in Cooperative Data Access Environment

Kant

Jajodia

2012

Proceedings of the 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

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In this paper we consider the situation where a set of enterprises need to collaborate to provide rich services to their clients. Such collaboration often requires controlled access to each other's data, which we assume is stored in standard relational form. The access control is provided by a set of access rules that may be defined over the joins of various relations. In this paper we introduce the notion of consistency of access rules and devise an algorithm to ensure consistency. We also consider the possibility of occasional changes in access rules and address the problem of maintaining consistency in the face of such changes. We propose algorithms for both changes with new privileges grants and revocations on existing privileges.

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“…We first describe the core of our algorithm which is based on query rewriting technique, namely MiniCon [8]. We propose an adaptation of this algorithm to the security context.…”

Section: Contributionmentioning

confidence: 99%

Authorization Policies for Materialized Views

Nait-Bahloul

Coquery

Hacid

2012

IFIP Advances in Information and Communication Technology

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Part 13: Short PapersInternational audienceIn this paper, we propose a novel approach to facilitate the administration of access control policies to ensure the confidentiality of data at the level of materialized views. A materialized view stores both the definition of the view and the rows resulting from the execution of the view. Several techniques and models have been proposed to control access to databases, but to our knowledge the problem of automatically generating from access control policies defined over base relations the access control policies that are needed to control materialized views is not investigated so far. We are dealing with this problem by resorting to an adaptation of query rewriting techniques. We choose to express fine-grained access control through authorization views

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MiniCon: A scalable algorithm for answering queries using views

Cited by 214 publications

References 29 publications

Rewriting Queries Using Views

Rewriting Queries Using Views

Access Rule Consistency in Cooperative Data Access Environment

Authorization Policies for Materialized Views

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