A Simple Approach to SQL Joins in a Relational Algebraic Notation (original) (raw)

Information Systems, 1992

When SQL is used to formulate queries for a relational database, many conditions in the WHERE clause appear to be very predictable. These are the so-called join conditions which indicate how the tables of a database are related. It seems that a system should be able to generate these conditions to a great extent automatically from the knowledge of the database structure. To this end the notion of the structure of a join is introduced and mathematically described as a graph morphism. It turns out to be a generalization of the notion of a natural join. It is claimed that this approach is theoretically elegant and provides in practice a good basis for the development of query generators.

Mapping Relational Algebra Operators into SQL Queries: A Database Case Study

2015

Relational algebra operators and mapping to resulting structured query language (SQL) queries are among the most important concepts and skills for students taking a course in database design and implementation, especially those majoring in IS/IT. The most typical relational algebra operators mapped to foundational SQL include unions and intersections, as well as other relational operators applied to these operators, including differences and various joins. Unfortunately, few textbooks or external resources provide ample opportunity for students to apply the full set of most common relational algebra operators mapped to resulting SQL over a single unified case. Most database textbooks exemplify each separate relational algebra construct to a single, sparse (although visually-stimulating) example, wherein the full set of operators is not near fully exemplified. This paper presents an overview of a case example that exemplifies and maps a more complete set of relational algebra operato...

Query processing techniques in the summary-table-by-example database query language

ACM Transactions on Database Systems, 1989

Summary-Table-by-Example (STBE) is a graphical language suitable for statistical database applications. STBE queries have a hierarchical subquery structure and manipulate summary tables and relations with set-valued attributes. The hierarchical arrangement of STBE queries naturally implies a tuple-by-tuple subquery evaluation strategy (similar to the nested loops join implementation technique) which may not be the best query processing strategy. In this paper we discuss the query processing techniques used in STBE. We first convert an STBE query into an “extended” relational algebra (ERA) expression. Two transformations are introduced to remove the hierarchical arrangement of subqueries so that query optimization is possible. To solve the “empty partition” problem of aggregate function evaluation, directional join (one-sided outer-join) is utilized. We give the algebraic properties of the ERA operators to obtain an “improved” ERA expression. Finally we briefly discuss the generation...

A System to Support Teaching and Learning Relational Database Query Languages and Query Processing

The importance of relational algebra in a database course is widely recognized to facilitate teaching and learning of SQL. From our experience we have also found it very useful for the students to understand the basics of query processing in terms of execution plans. However currently there are no specific tools to make the process of learning relational algebra and execution plans an interesting and stimulating activity. The features of the JRS (Java Relational System) graphical editors of query plans are presented. The graphical editors are used to define and execute queries on a database represented by two kinds of trees: A logical plan of relational algebra, and a physical plan that describes an algorithm to execute a query using the physical operators of the relational DBMS developed in Java as a teaching tool.

Relational queries in a domain based DBMS

ACM SIGMOD Record, 1983

This paper addresses the problem of relational queries processing in the domain based database machine DBMAC. A brief description of the storage organisation of the domain based DBMS is first given. Then the operating principles of the domain based data-model, called D-model, is described through some examples. The central part of the paper deals with the translation of relational queries into operations on objects of the D-model. Objects of the D-model and a set of operations on these objects are first defined : this set S of operations is shown to be complete in that any relational query can be translated into D-model operations belonging to S .Finally we give a method for processing relation queries using D-model operations.The basic advantages to be expected from a domain based physical organization of data are :1. fast equi-join execution,2. a compact representation of intermediate results.The latter should lead to efficient processing of complex queries, provided a powerful pa...

Algebraic Query Language (AQL): An Implementation of Relational Algebra

Algebraic Query Language (AQL): An Im, 2025

This white paper presents the Algebraic Query Language (AQL), a database query language developed as an alternative to SQL for data analysis at Caltech's Jet Propulsion Laboratory (JPL). Created by Marc Kidwell Pestana for the GPS Earth Observatory Group, AQL diverges from E. F. Codd's relational model in several key ways; In AQL, data types are assigned to entire relations rather than to individual attributes, and its syntax is algebraic, unlike SQL's quasi-English structure. AQL also includes assignment operators similar to those found in programming languages like C, C++, and Python. Further, it introduces a novel approach to operator type sensitivity and data independence. Despite these differences, AQL retains a strong foundation in Codd's relational model. This paper examines which elements of Codd's model are preserved in AQL and describes the key modifications made. We provide an overview of AQL's core components, along with examples of their usage, and demonstrate how data types are created and assigned to relations in AQL. Additionally, we discuss AQL's development and use at JPL, from early versions to the current, fully operational AQL 5.0. 1 Potential applications of AQL are also explored, including its relevance to Relational Matrices. For further details, a formal definition of AQL is found in Appendix A. Also, [1] and [4] provide an overview of Codd's relational model, [1] and [3] cover Codd's relation, and Appendix B presents the main features of Codd's relational algebra.

Design of an integrated query and manipulation notation for database languages

1992

A common task in data intensive applications is to locate a group of items and then manipulate them, e.g. to give a bonus to all of the employees in a department. Conventional relational query languages like SQL provide facilities for such manipulation-queries, but are not smoothly integrated with a programming language and lack computational power. It has been argued that comprehensions, a construct found in some languages, are a good query notation for database programming languages. An extension to comprehensions is proposed that permits the data to be manipulated by side-effect in addition to being queried. These side-effecting queries are computationally powerful and smoothly integrated into a database programming language, unlike conventional relational query languages. Furthermore side-effecting comprehensions are concise and some may be automatically optimized

The Expressiveness of Query Languages for Nested Relations

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Relational Algebra Interpreter in Context of Query Languages

International Journal of Computer Theory and Engineering, 2011

Relational database systems have succeeded commercially because of their openness and sturdy theoretical groundwork. The contribution of this title "Relational Algebra Interpreter in context of query languages" is presentation of new implementation in such a way so that queries written in relational algebra can be compiled into SQL and executed on a relational database system. It takes a relational algebra statement as key, does syntactic and lexical parsing on it. In the event of an error in the syntax of the expression it will forward the error to user. If the syntax is correct the relational algebra expression is converted into a SQL statement and executed on an RDBMS. This work can serve up as a basis learning Relational Algebra for different class of users, as they will be given immediate feedbacks about their queries.