Distributed Database Principles Systems Stefano Ceri Giuseppe Pelagatti Mcgraw Hill

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A Review of Distributed Databases: Principles and Systems by Stefano Ceri and Giuseppe Pelagatti

Distributed databases are databases that are stored and accessed by multiple nodes in a network. They offer advantages such as scalability, availability, fault-tolerance, and data locality. However, they also pose challenges such as concurrency control, data consistency, query optimization, and transaction management. How can these challenges be addressed by distributed database systems?

In their book Distributed Databases: Principles and Systems, Stefano Ceri and Giuseppe Pelagatti provide a comprehensive and rigorous introduction to the theory and practice of distributed database systems. The book covers topics such as distributed database architectures, data fragmentation and replication, distributed query processing and optimization, distributed transaction processing and recovery, distributed concurrency control and deadlock detection, distributed reliability and security, and distributed database design. The book also includes case studies of real-world distributed database systems such as Ingres, Oracle, R*, SDD-1, and XPRS.

The book is intended for advanced undergraduate and graduate students in computer science and engineering, as well as for researchers and practitioners in the field of distributed databases. The book assumes some background knowledge of database systems and computer networks. The book is well-organized, well-written, and well-illustrated with examples and exercises. The book is also accompanied by a set of slides and solutions to selected exercises.

Distributed Databases: Principles and Systems is a classic textbook that has been widely used and cited in the field of distributed databases. It is a valuable resource for anyone who wants to learn about the principles and systems of distributed databases.

The book was published by McGraw-Hill in 1984 as part of the McGraw-Hill Computer Science Series. It has 393 pages and an ISBN of 0070108293. The book can be found on Google Books[^1^] or Internet Archive[^2^].Here is a possible continuation of the article:

In this section, we will briefly review some of the main concepts and techniques discussed in the book.

Distributed Database Architectures

A distributed database system consists of a collection of sites, each of which hosts a local database and communicates with other sites through a network. The sites may be homogeneous or heterogeneous, depending on whether they use the same or different data models, query languages, and software. The sites may also be autonomous or cooperative, depending on whether they have independent or shared control over their data and operations.

The book introduces three types of distributed database architectures: client-server, peer-to-peer, and multidatabase. In a client-server architecture, one or more clients request services from one or more servers, which provide access to the data. In a peer-to-peer architecture, each site acts as both a client and a server, and can initiate or respond to requests from other sites. In a multidatabase architecture, each site maintains its own local database, but also participates in a global database that integrates data from multiple sources.

Data Fragmentation and Replication

Data fragmentation is the process of dividing a relation into smaller subsets called fragments. Data replication is the process of storing copies of a fragment at multiple sites. Data fragmentation and replication can improve the performance, availability, and reliability of distributed database systems. However, they also introduce complexity and overhead in maintaining data consistency and integrity.

The book discusses different types of data fragmentation: horizontal, vertical, and hybrid. Horizontal fragmentation partitions a relation by rows, based on some selection condition. Vertical fragmentation partitions a relation by columns, based on some projection attributes. Hybrid fragmentation combines both horizontal and vertical fragmentation. The book also discusses different types of data replication: full, partial, and no replication. Full replication stores a copy of the entire relation at every site. Partial replication stores a copy of some fragments at some sites. No replication stores each fragment at only one site.

Distributed Query Processing and Optimization

Distributed query processing is the process of executing a query over a distributed database system. Distributed query optimization is the process of finding the best execution plan for a query over a distributed database system. Distributed query processing and optimization involve several steps such as query decomposition, data localization, global optimization, local optimization, and query execution.

The book presents various algorithms and techniques for distributed query processing and optimization. For example, the book introduces the semi-join method for reducing the amount of data transferred between sites by applying local selections and projections before joining relations. The book also introduces the SDD-1 algorithm for generating optimal execution plans for queries involving joins of multiple relations by using dynamic programming and cost estimation. 66dfd1ed39

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