Database system architecture supporting coexisting query languages and data models

SIGLELD:D48239/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Validation of queries to a relational database

This thesis addresses the problem of preventing users of a data base system from interrogating it with query language expressions which are syntactically and semantically valid but which do not match the user's intentions. A method of assisting users of a relational data base to formulate query language expressions which are valid representations of the abstract query which the user wishes to put is developed. The central focus of the thesis is a method of communicating the critical aspects of the semantics of the relation which would be generated in response to a user's proposed operations on the data base. Certain classes of user error which can arise when using a relational algebra query system are identified, and a method of demonstrating their invalidity is demonstrated. This is achieved by representing via a graph the consequences of operations on relations. Also developed are techniques allowing the generation of pseudo-natural language text describing the relations which would be created as the result of the user's proposed query language operations. A method of allowing the creators of data base relations to incorporate informative semantic data about their relations is developed. A method of permitting this data to be modified by query language operations is specified. Pragmatic linguistic considerations which arise when this data is used to generate pseudo-natural language statements are addressed, and examples of the system's use are given

The Family of MapReduce and Large Scale Data Processing Systems

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data which has called for a paradigm shift in the computing architecture and large scale data processing mechanisms. MapReduce is a simple and powerful programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. It isolates the application from the details of running a distributed program such as issues on data distribution, scheduling and fault tolerance. However, the original implementation of the MapReduce framework had some limitations that have been tackled by many research efforts in several followup works after its introduction. This article provides a comprehensive survey for a family of approaches and mechanisms of large scale data processing mechanisms that have been implemented based on the original idea of the MapReduce framework and are currently gaining a lot of momentum in both research and industrial communities. We also cover a set of introduced systems that have been implemented to provide declarative programming interfaces on top of the MapReduce framework. In addition, we review several large scale data processing systems that resemble some of the ideas of the MapReduce framework for different purposes and application scenarios. Finally, we discuss some of the future research directions for implementing the next generation of MapReduce-like solutions.Comment: arXiv admin note: text overlap with arXiv:1105.4252 by other author

Data base management system analysis and performance testing with respect to NASA requirements

Several candidate Data Base Management Systems (DBM's) that could support the NASA End-to-End Data System's Integrated Data Base Management System (IDBMS) Project, later rescoped and renamed the Packet Management System (PMS) were evaluated. The candidate DBMS systems which had to run on the Digital Equipment Corporation VAX 11/780 computer system were ORACLE, SEED and RIM. Oracle and RIM are both based on the relational data base model while SEED employs a CODASYL network approach. A single data base application which managed stratospheric temperature profiles was studied. The primary reasons for using this application were an insufficient volume of available PMS-like data, a mandate to use actual rather than simulated data, and the abundance of available temperature profile data

The Query Cube: A Framework for Assessing User Productivity with Database Information Retrieval

Three key factors that affect user productivity on database information retrieval are representation realism, expressive ease, and task complexity. Representation realism is the level of abstraction used in formulating queries. Expressive ease is the syntactic flexibility of a query language. Task complexity is the level of difficulty of queries. These factors formed a three dimensional query cube. A laboratory experiment was conducted to evaluate user productivity on database information retrieval corresponding to different vertices of the query cube. The results show that the query cube is a viable framework for assessing user productivity, both on effectiveness and efficiency perspective

Usability evaluation of digital libraries: a tutorial

This one-day tutorial is an introduction to usability evaluation for Digital Libraries. In particular, we will introduce Claims Analysis. This approach focuses on the designers’ motivations and reasons for making particular design decisions and examines the effect on the user’s interaction with the system. The general approach, as presented by Carroll and Rosson(1992), has been tailored specifically to the design of digital libraries. Digital libraries are notoriously difficult to design well in terms of their eventual usability. In this tutorial, we will present an overview of usability issues and techniques for digital libraries, and a more detailed account of claims analysis, including two supporting techniques – simple cognitive analysis based on Norman’s ‘action cycle’ and Scenarios and personas. Through a graduated series of worked examples, participants will get hands-on experience of applying this approach to developing more usable digital libraries. This tutorial assumes no prior knowledge of usability evaluation, and is aimed at all those involved in the development and deployment of digital libraries