PRINCIPLES OF DISTRIBUTED DATABASE SYSTEMS EBOOK
systems have become an important and interesting architectural alternative to classical distributed database systems. Although the early distributed database. This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories. Contribute to krushnaarengarajan/EBOOKS development by creating an account on GitHub.
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Principles Of Distributed Database Systems (3rd Edition) (M. Tamer Özsu, Patrick Valduriez). Topics Database, قواعد البيانات. Principles of Distributed Database Systems M. Tamer Özsu • Patrick Valduriez Principles of Distributed Database Systems Third Edition M. Tamer Özsu Patrick. Principles of Distributed Database Systems, Third Edition. M. Tamer Özsu · Patrick Valduriez. Springer ISBN
Overview of Query Processing Abstract 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.
This relieves the user from query optimization, a time-consuming task that is best handled by the query processor, since it can exploit a large amount of useful information about the data. Query Decomposition and Data Localization Abstract In Chapter 6 we discussed a generic layering scheme for distributed query processing in which the first two layers are responsible for query decomposition and data localization.
These two functions are applied successively to transform a calculus query specified on distributed relations i. In this chapter we present the techniques for query decomposition and data localization. Optimization of Distributed Queries Abstract Chapter 7 shows how a calculus query expressed on global relations can be mapped into a query on relation fragments by decomposition and data localization.
This mapping uses the global and fragment schemas. During this process, the application of transformation rules permits the simplification of the query by eliminating common subexpressions and useless expressions.
This type of optimization is independent of fragment characteristics such as cardinalities. The query resulting from decomposition and localization can be executed in that form simply by adding communication primitives in a systematic way. However, the permutation of the ordering of operations within the query can provide many equivalent strategies to execute it.
Multidatabase Query Processing Abstract In the previous three chapters, we have considered query processing in tighly-coupled homogeneous distributed database systems. As we discussed in Chapter 1, these systems are logically integrated and provide a single image of the database, even though they are physically distributed.
In this chapter, we concentrate on query processing in multidatabase systems that provide interoperability among a set of DBMSs. This is only one part of the more general interoperability problem.
Principles of Distributed Database Systems (3rd Edition)
Distributed applications pose major requirements regarding the databases they access, in particular, the ability to access legacy data as well as newly developed databases. Thus, providing integrated access to multiple, distributed databases and other heterogeneous data sources has become a topic of increasing interest and focus.
Introduction to Transaction Management Abstract Up to this point the basic access primitive that we have considered has been a query. Our focus has been on retrieve-only or read-only queries that read data from a distributed database. We have not yet considered what happens if, for example, two queries attempt to update the same data item, or if a system failure occurs during execution of a query.
For retrieve-only queries, neither of these conditions is a problem. One can have two queries reading the value of the same data item concurrently.
Principles of Distributed Database Systems
Similarly, a read-only query can simply be restarted after a system failure is handled. On the other hand, it is not difficult to see that for update queries, these conditions can have disastrous effects on the database. We cannot, for example, simply restart the execution of an update query following a system failure since certain data item values may already have been updated prior to the failure and should not be updated again when the query is restarted.
Otherwise, the database would contain incorrect data. Distributed Concurrency Control Abstract As we discussed in Chapter 10, concurrency control deals with the isolation and consistency properties of transactions. The distributed concurrency control mechanism of a distributed DBMS ensures that the consistency of the database, as defined in Section If transactions are internally consistent i.
It is obvious that such an alternative is only of theoretical interest and would not be implemented in any practical system, since it minimizes the system throughput. The level of concurrency i. Therefore, the concurrency control mechanism attempts to find a suitable trade-off between maintaining the consistency of the database and maintaining a high level of concurrency.
Specifically, we mentioned these terms in conjunction with data replication, because the principle method of building a reliable system is to provide redundancy in system components.
We also claimed in Chapter 1 that the distribution of data enhances system reliability. However, the distribution of the database or the replication of data items is not sufficient to make the distributed DBMS reliable. A number of protocols need to be implemented within the DBMS to exploit this distribution and replication in order to make operations more reliable. Data Replication Abstract As we discussed in previous chapters, distributed databases are typically replicated.
The purposes of replication are multiple: 1. System availability. As discussed in Chapter 1, distributed DBMSs may remove single points of failure by replicating data, so that data items are accessible from multiple sites.
Consequently, even when some sites are down, data may be accessible from other sites. As we have seen previously, one of the major contributors to response time is the communication overhead.
Replication enables us to locate the data closer to their access points, thereby localizing most of the access that contributes to a reduction in response time. 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. It has been almost twenty years since the first edition of this book appeared, and ten years since we released the second edition. As one can imagine, in a fast changing area such as this, there have been significant changes in the intervening period.
Distributed data management went from a potentially significant technology to one that is common place. The advent of the Internet and the World Wide Web have certainly changed the way we typically look at distribution. The emergence in recent years of different forms of distributed computing, exemplified by data streams and cloud computing, has regenerated interest in distributed data management.
ISBN 13: 9780130412126
Thus, it was time for a major revision of the material. We started to work on this edition five years ago, and it has taken quite a while to complete the work. The end result, however, is a book that has been heavily revised -- while we maintained and updated the core chapters, we have also added new ones. The major changes are the following: Database integration and querying is now treated in much more detail, reflecting the attention these topics have received in the community in the past decade.
Chapter 4 focuses on the integration process, while Chapter 9 discusses querying over multidatabase systems. The previous editions had only brief discussion of data replication protocols.
This topic is now covered in a separate chapter Chapter 13 where we provide an in-depth discussion of the protocols and how they can be integrated with transaction management.
Peer-to-peer data management is discussed in depth in Chapter These systems have become an important and interesting architectural alternative to classical distributed database systems. Although the early distributed database systems architectures followed the peer-to-peer paradigm, the modern incarnation of these systems have fundamentally different characteristics, so they deserve in-depth discussion in a chapter of their own.
Web data management is discussed in Chapter This is a difficult topic to cover since there is no unifying framework. We discuss various aspects of the topic ranging from web models to search engines to distributed XML processing. In this edition, we again have a similar chapter Chapter 18 where we cover stream data management and cloud computing.
These topics are still in a flux and are subjects of considerable ongoing research. We highlight the issues and the potential research directions. The resulting manuscript strikes a balance between our two objectives, namely to address new and emerging issues, and maintain the main characteristics of the book in addressing the principles of distributed data management.This mapping uses the global and fragment schemas.
Buy Softcover. Chapter 2 in this part covers the background and can be skipped if the students already have sufficient knowledge of the relational database concepts and the computer network technology. We discuss various aspects of the topic ranging from web models to search engines to distributed XML processing.
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. Buy options. This book covers the breadth and depth of this re-emerging field. Web Data Management.
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