Extended conditions for answering an aggregate query using materialized views

An efficient query engine is certainly one of the most important components in data warehouses (also known as OLAP systems or multidimensional databases) and its efficiency is influenced by many other aspects, both logical (data model, policy of view materialization, etc.) and physical (multidimensional or relational storage, indexes, etc). As is evident, OLAP queries are often based on the usual metaphor of the data cube and the concepts of facts, measures and dimensions and, in contrast to conventional transactional environments, they require the classification and aggregation of enormous quantities of data. In spite of that, one of the fundamental requirements for these systems is the ability to perform multidimensional analyses in online response times. Since the evaluation from scratch of a typical OLAP aggregate query may require several hours of computation, this can only be achieved by pre-computing several queries, storing the answers permanently in the database and then reusing them in the query evaluation process. These pre-computed queries are commonly referred to as materialized views and the problem of evaluating a query by using (possibly only) these precomputed results is known as the problem of answering/rewriting queries using views. In this paper we briefly analyze the difference between query answering and query rewriting approach and why query rewriting is preferable in a data warehouse context. We also discuss the main techniques proposed in literature to rewrite aggregate multidimensional queries using materialized views.

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Materialized views and data warehouses

ACM SIGMOD Record ◽

10.1145/273244.273253 ◽

1998 ◽

Vol 27 (1) ◽

pp. 21-26 ◽

Cited By ~ 48

Author(s):

Nick Roussopoulos

Keyword(s):

Materialized Views ◽

Data Warehouses

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Query Games in Databases

ACM SIGMOD Record ◽

10.1145/3471485.3471504 ◽

2021 ◽

Vol 50 (1) ◽

pp. 78-85

Author(s):

Ester Livshits ◽

Leopoldo Bertossi ◽

Benny Kimelfeld ◽

Moshe Sebag

Keyword(s):

Game Theory ◽

Cooperative Game ◽

Shapley Value ◽

Cooperative Game Theory ◽

The Shapley Value ◽

Computational Aspects ◽

Aggregate Query ◽

Boolean Query

Database tuples can be seen as players in the game of jointly realizing the answer to a query. Some tuples may contribute more than others to the outcome, which can be a binary value in the case of a Boolean query, a number for a numerical aggregate query, and so on. To quantify the contributions of tuples, we use the Shapley value that was introduced in cooperative game theory and has found applications in a plethora of domains. Specifically, the Shapley value of an individual tuple quantifies its contribution to the query. We investigate the applicability of the Shapley value in this setting, as well as the computational aspects of its calculation in terms of complexity, algorithms, and approximation.

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Universal Data Warehousing Based on a Meta-Data Modeling Approach

International Journal of Cooperative Information Systems ◽

10.1142/s0218843003000772 ◽

2003 ◽

Vol 12 (03) ◽

pp. 325-363 ◽

Cited By ~ 2

Author(s):

Joseph Fong ◽

Qing Li ◽

Shi-Ming Huang

Keyword(s):

Data Warehouse ◽

Data Warehousing ◽

Object Oriented ◽

Data Models ◽

Heterogeneous Databases ◽

Materialized Views ◽

Prototype System ◽

Relational View ◽

Metadata Model ◽

Star Schema

Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.

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Materialized View Selection in the Data Warehouse

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.29-32.1133 ◽

2010 ◽

Vol 29-32 ◽

pp. 1133-1138 ◽

Cited By ~ 1

Author(s):

Li Juan Zhou ◽

Hai Jun Geng ◽

Ming Sheng Xu

Keyword(s):

Decision Support ◽

Data Warehouse ◽

Materialized Views ◽

Storage Space ◽

View Selection ◽

Materialized View ◽

Query Response Time ◽

Materialized View Selection ◽

Optimal Efficiency ◽

The Cost

A data warehouse stores materialized views of data from one or more sources, with the purpose of efficiently implementing decision-support or OLAP queries. Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. The goal is to select an appropriate set of views that minimizes sum of the query response time and the cost of maintaining the selected views, given a limited amount of resource, e.g., materialization time, storage space, etc. In this article, we present an improved PGA algorithm to accomplish the view selection problem; the experiments show that our proposed algorithm shows it’s superior.

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On Object-Oriented Databases, Materialized Views, and Concurrent Engineering

ASME 1991 5th Annual Database Symposium: Engineering Databases — An Enterprise Resource ◽

10.1115/edm1991-0187 ◽

1991 ◽

Author(s):

Martin Hardwick ◽

Blair R. Downie

Keyword(s):

Concurrent Engineering ◽

Object Oriented ◽

Materialized Views ◽

Design Tools ◽

Design Data ◽

Multiple Inheritance ◽

File Formats ◽

Definition Of ◽

Application Specific ◽

Object Oriented Database

Abstract Concurrent engineering seeks to reduce the length of the design life cycle by allowing multiple engineers to work on a design concurrently using their different design tools. A major stumbling block in achieving this goal is that most design tools use different file formats. Emerging standards such as STEP/PDES/EXPRESS reduce this barrier, but conformance to standards is not enough. One reason design tools have different file formats is because each tool requires a different perspective or view of the design. Engineering databases must provide designers with the ability to define application specific views of design data, and the ability to propagate changes among those related views. In this paper, we examine how an object-oriented database system can support the definition of application views using a class hierarchy and multiple inheritance.

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