Translation with optimization from relational calculus to relational algebra having aggregate functions

1990 ◽  
Vol 15 (4) ◽  
pp. 518-557 ◽  
Author(s):  
Ryohei Nakano
Keyword(s):  
Relational Algebra ◽  
Relational Calculus ◽  
Aggregate Functions

Operators for Multidimensional Aggregate Data

2003 ◽  
pp. 116-165 ◽  
Author(s):  
Maurizio Rafanelli
Keyword(s):  
Aggregate Data ◽  
Basic Algebra ◽  
Relational Algebra ◽  
Relational Model ◽  
Statistical Databases ◽  
Formal Definitions ◽  
Relational Calculus

In this chapter the author proposes the different approaches for defining operators able to manipulate this multidimensional structure. In particular, he initially considers operators for multidimensional aggregate data which extend relational algebra and relational calculus (the so-called enlarged relational model). Then he discusses operators for multidimensional aggregate data defined in a tabular environment. In both the cases the author defines such data as statistical (aggregate) data. Subsequently he introduces the operators for OLAP applications, giving a terminology correspondence between the multidimensional aggregate (statistical) databases and OLAP areas. Then he defines the fundamental operators deduced from the previous ones, which form the basic algebra for the manipulation of multidimensional aggregate data, giving their formal definitions and some explanatory examples.

scholarly journals A Simpler and Semantic Multidimensional Database Query Language to Facilitate Access to Information in Decision-making

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Fredi Edgardo Palominos ◽  
Felisa Córdova ◽  
Claudia Durán ◽  
Bryan Nuñez
Keyword(s):  
Decision Making ◽  
Query Language ◽  
Database Systems ◽  
Relational Algebra ◽  
Multidimensional Database ◽  
Management Indicators ◽  
Relational Calculus ◽  
Database Technology ◽  
Sql Language ◽  
Relational Database Systems

OLAP and multidimensional database technology have contributed significantly to speed up and build confidence in the effectiveness of methodologies based on the use of management indicators in decision-making, industry, production, and services. Although there are a wide variety of tools related to the OLAP approach, many implementations are performed in relational database systems (R-OLAP). So, all interrogation actions are performed through queries that must be reinterpreted in the SQL language. This translation has several consequences because SQL language is based on a mixture of relational algebra and tuple relational calculus, which conceptually responds to the logic of the relational data model, very different from the needs of the multidimensional databases. This paper presents a multidimensional query language that allows expressing multidimensional queries directly over ROLAP databases. The implementation of the multidimensional query language will be done through a middleware that is responsible for mapping the queries, hiding the translation to a layer of software not noticeable to the end-user. Currently, progress has been made in the definition of a language where through a key statement, called aggregate, it is possible to execute the typical multidimensional operators which represent an important part of the most frequent operations in this type of database.

Set Comparison in Relational Query Languages

2005 ◽  
pp. 624-631
Author(s):  
Mohammad Dadashzadeh
Keyword(s):  
Relational Database ◽  
Database Management ◽  
Query Languages ◽  
Relational Algebra ◽  
Management Systems ◽  
Relational Data Model ◽  
Network Database ◽  
Relational Calculus ◽  
Relational Form ◽  
Time Loop

Today’s de facto database standard, the relational database, was conceived in the late 1960’s by Edgar F. Codd at IBM. The relational data model offered the user a logical view of the data that was shielded from consideration of how the data would, in fact, be physically organized in storage. This feat was accomplished in large part by the introduction of relational query languages that would specify the desired set of records in a non-procedural fashion. In contrast to the prevailing record-at-a-time, loop-oriented, procedural query languages of the hierarchical and network database management systems, relational query languages were set-oriented in that they would operate on sets of records (i.e., relations or tables) at-a-time in order to produce the desired set of output records. Codd introduced both a relational algebra and a relational calculus as a basis for dealing with data in relational form. Indeed, he defined what the first relational language was: Data Sublanguage Alpha (Codd, 1971).

Extending the Relational Algebra for Relations with Maybe Tuples and Existential and Universal Null Values

1984 ◽  
Vol 7 (1) ◽  
pp. 129-150
Author(s):  
Joachim Biskup
Keyword(s):  
Relational Algebra ◽  
Null Value ◽  
Null Values ◽  
A Minor

We study operations on generalized database relations which possibly contain maybe tuples and two types of null values. The existential null value has the meaning “value at present unknown” whereas the universal null value has the meaning “value arbitrary”. For extending a usual relational operation to generalized relations we develop three requirements: adequacy, restrictedness, and feasibility. As demonstrated for the natural join as an example, we can essetially meet these requirements although we are faced with a minor tradeoff between restrictedness and feasibility.

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