Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system.
The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems. Database Management Systems provides comprehensive and up-to-date coverage of the fundamentals of database systems.
Coherent explanations and practical examples have made this one of the leading texts in the field. The third edition continues in this tradition, enhancing it with more practical material.
The new edition has been reorganized to allow more flexibi. Now, instructors can easily choose whether they would like to teach a course which emphasizes database application development or a course that emphasizes database systems issues.
New overview chapters at the beginning of parts make it possible to skip other chapters in the part if you don't want the detail. More applications and examples have been added throughout the book, including SQL and Oracle examples. The applied flavor is further enhanced by the two new database applications chapters.
Fundamentals of Database Systems has become the world-wide leading textbook because it combines clear explanations of theory and design, broad coverage of models and real systems, and excellent examples with up-to-date introductions and modern database technologies. These materials may not be fully covered in lectures. Our lectures are intended to motivate as well as provide a road map for your reading-- with the limited lecture time we may not be able to cover everything in the readings.
All course participants must adhere to the academic honor code of FSU which is available in the student handbook. All instances of academic dishonesty will be reported to the university.
Showing your code or homework solutions to others is a violation of academic honesty. It is your responsibility to ensure that others cannot access your code or homework solutions. Consulting related textbooks, papers and information available on Internet for your assignment and homework is fine. However, copying a large portion of such information will be considered as academic dishonesty. If you borrow a small piece of any such information, please acknowledge that in your assignment. Please see the following web site for a complete explanation of the Academic Honor Code.
Late assignments and paper summaries will not ordinarily be accepted. If, for some compelling reason, you cannot hand in an assignment on time, please contact the TA or instructor as far in advance as possible. Written assignments or project deliverables are due at the beginning of a class, you should hand them in at the beginning of the class; No credit will be given to late projects and presentations; No make-up exams except under extremely unusual circumstances. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques.
This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing.
Springer Professional. Back to the search result list. Table of Contents Frontmatter Chapter 1. Introduction Abstract. Distributed database system DDBS technology is the union of what appear to be two diametrically opposed approaches to data processing: database system and computer network technologies. Database systems have taken us from a paradigm of data processing in which each application defined and maintained its own data Figure 1. This new orientation results in data independence , whereby the application programs are immune to changes in the logical or physical organization of the data, and vice versa.
As indicated in the previous chapter, there are two technological bases for distributed database technology: database management and computer networks.
In this chapter, we provide an overview of the concepts in these two fields that are more important from the perspective of distributed database technology. The design of a distributed computer system involves making decisions on the placement of data and programs across the sites of a computer network, as well as possibly designing the network itself.
In the case of distributed DBMSs, the distribution of applications involves two things: the distribution of the distributed DBMS software and the distribution of the application programs that run on it.
Different architectural models discussed in Chapter 1 address the issue of application distribution. In this chapter we concentrate on distribution of data. In the previous chapter, we discussed top-down distributed database design, which is suitable for tightly integrated, homogeneous distributed DBMSs.
In this chapter, we focus on bottom-up design that is appropriate in multidatabase systems. In this case, a number of databases already exist, and the design task involves integrating them into one database. The starting point of bottom-up design is the individual local conceptual schemas. The process consists of integrating local databases with their local schemas into a global database with its global conceptual schema GCS also called the mediated schema.
An important requirement of a centralized or a distributed DBMS is the ability to support semantic data control, i. Semantic data control typically includes view management, security control, and semantic integrity control. Informally, these functions must ensure that authorized users perform correct operations on the database, contributing to the maintenance of database integrity. The functions necessary for maintaining the physical integrity of the database in the presence of concurrent accesses and failures are studied separately in Chapters 10 through 12 in the context of transaction management.
In the relational framework, semantic data control can be achieved in a uniform fashion.
Views, security constraints, and semantic integrity constraints can be defined as rules that the system automatically enforces. The violation of some rules by a user program a set of database operations generally implies the rejection of the effects of that program e.
The success of relational database technology in data processing is due, in part, to the availability of non-procedural languages i. By hiding the low-level details about the physical organization of the data, relational database languages allow the expression of complex queries in a concise and simple fashion. In particular, to construct the answer to the query, the user does not precisely specify the procedure to follow. This procedure is actually devised by a DBMS module, usually called a query processor.