A survey of logical models for OLAP databases (original) (raw)
Related papers
Lecture Notes in Computer Science, 1999
We present a new model for OLAP, called the nested data cube (NDC) model. Nested data cubes are a generalization of other OLAP models such as f-tables [3], and hypercubes [2], but also of classical structures such as sets, bags, and relations. The model we propose adds to the previous models mainly flexibility in viewing the data, in that it allows for the assignment of priorities to the different dimensions of the multidimensional OLAP data. We also present an algebra in which all typical OLAP analysis and navigation operations can be formulated. We present a number of algebraic operators that work on nested data cubes and that preserve the functional dependency between the dimensional coordinates of the data cube and the factual data in it. These operations include nesting, unnesting, summary, roll-up, and aggregation operations. We show how these operations can be applied to sub-NDC's at any depth, and also show that the NDC algebra can express the SPJR algebra [1] of the relational model. A major motivation for defining an algebra rather than a calculus, is that an algebra naturally leads to an implementation strategy. Importantly, we show that the NDC algebra primitives can be implemented by linear time algorithms.
Modeling multidimensional databases, cubes and cube operations
1998
On-Line Analytical Processing (OLAP) is a trend in database technology, which was recently introduced and has attracted the interest of a lot of research work. OLAP is based on the multidimensional view of data, supported either by multidimensional databases (MOLAP) or relational engines (ROLAP).
Modelling and Optimisation Issues for Multidimensional Databases
Lecture Notes in Computer Science, 2000
It is commonly agreed that multidimensional data cubes form the basic logical data model for OLAP applications. Still, there seems to be no agreement on a common model for cubes. In this paper we propose a logical model for cubes based on the key observation that a cube is not a self-existing entity, but rather a view over an underlying data set. We accompany our model with syntactic characterisations for the problem of cube usability. To this end, we have developed algorithms to check whether (a) the marginal conditions of two cubes are appropriate for a rewriting, in the presence of aggregation hierarchies and (b) an implication exists between two selection conditions that involve different levels of aggregation of the same dimension hierarchy. Finally, we present a rewriting algorithm for the cube usability problem.
A new way of optimizing OLAP queries
2004
For around 10 years, the academic research in database has attempted to define a commonly agreed logical modeling for the multidimensional and hierarchical nature of data manipulated with OLAP treatments (called datacube, or cube for short). But only recently has the concept of representation of a cube on a screen, or the optimization of OLAP queries at a logical level, been taken into account in this study. As many others, we believe that these two concepts are essential for the definition of a multidimensional query language. In this article, we propose to consider representations of cubes as first class citizens for query optimisation at the logical level. To reach this goal, we formally define the concept of representation by using the model of complex values [ABI 95]. This allows to have a single model for manipulating both cubes and their representations through typical OLAP operations. These typical operations are studied to propose rewrite rules in order to optimize OLAP queries. RÉSUMÉ. Depuis environ 10 ans, la définition d'un modèle concensuel englobant la nature multidimensionnelle et hiérarchisée des données manipulées par les traitements OLAP (appelées cube de données) est à l'étude. Mais c'est seulement récemment que les concepts de représentation d'un cube à l'écran et d'optimisation de requêtes OLAP à un niveau logique ont été pris en compte dans cette étude. Nous pensons, comme beaucoup, que ces concepts sont essentiels à la définition d'un langage de requêtes pour OLAP. Dans cet article, nous proposons de considérer les représentations de cubes de données comme une base pour l'optimisation de requêtes au niveau logique. Pour ce faire, nous définissons formellement le concept de représentation en utilisant le modèle des valeurs complexes [ABI 95]. Cela permet d'avoir un modèle unique pour manipuler un cube et ses représentations via les opérations OLAP usuelles. L'étude de ces opérations nous permet de donner des règles de réécriture pour optimiser les requêtes OLAP. KEYWORDS: OLAP, query language, logical modeling, optimisation MOTS-CLÉS : OLAP, langage de requêtes, modélisation logique, optimisation 1. For the sake of space we refer the reader to [ABI 95] for a presentation of this model.
ERATOSTHENES: Design and Architecture of an OLAP System
2001
On-Line Analytical Processing (OLAP) is a trend in database technology, based on the multidimensional view of data. The aim of this paper is twofold: (a) to list general problems and solutions applicable to the design of any OLAP system and (b) to present the specific design decisions that we made for a prototype under development at NTUA, which we call ERATOSTHENES. The paper addresses requirements and design issues for all three models involved in an OLAP system: the presentational, logical and physical model. It also discusses in detail the architecture and the major components of ERATOSTHENES. * This research has been partially funded by the European Union's Information Society Technologies Programme (IST) under project EDITH (IST-1999-20722).
The Composite OLAP-Object Data Model: Removing an Unnecessary Barrier
2006
OLAP and object data models represent different logical concepts and structures, and therefore separate database systems with different query languages were developed based on these models. We show in this paper that it is desirable and possible to combine these models to represent realistic modeling requirements. We define in this paper an OLAP-Object data model that combines the main characteristics of OLAP and Object data models in order to represent their functionalities in a common framework. We use three different types of object classes: primitive, regular and composite. In the OLAP-Object data model, primitive and regular classes which represent object structures can be used for form composite classes that represent OLAP structures. We define a query language that uses path structures to facilitate data navigation and data manipulation. The proposed language uses the concept of an anchor. An anchor is an object class (primitive, regular or composite) that is selected as a starting node from which paths structures can be formed to express queries. The power of the proposed query language is illustrated through numerous examples. The syntax and semantics of the proposed language are developed.
Constructing OLAP cubes based on queries
Proceedings of the 4th ACM international workshop on Data warehousing and OLAP - DOLAP '01, 2001
An On-Line Analytical Processing (OLAP) user often follows a train of thought, posing a sequence of related queries against the data warehouse. Although their details are not known in advance, the general form of those queries is apparent beforehand. Thus, the user can outline the relevant portion of the data posing generalised queries against a cube representing the data warehouse.
Proceedings of the 1st ACM international workshop on Data warehousing and OLAP - DOLAP '98, 1998
The paper introduces the concept of quotient relations to model and query OL,AP data The use of quotient relation inherits the advantages of the original relational model as it was introduced by Goad. Drilldown and roll-up operations can be pelformed by the powerful partitioning and de-partitioning operators on quotient relations. The proposed approach fulfills the requirements for a formal data model, namely the existence of an implementation independent formalism, the separation of structure and content and the existence of a declarative query language.
Decision Support Systems, 1999
. Data warehousing and On-Line Analytical Processing OLAP are two of the most significant new technologies in the business data processing arena. A data warehouse can be defined as a '' very large'' repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions offered by many vendors of OLAP products. In this paper, we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries. q