In order to handle spatial data efficiently, as required in computer aided design and geo-data applications, a database system needs an index mechanism that will help it retrieve data items quickly according to their spatial locations However, traditional indexing methods are not well suited to data objects of non-zero size located m multi-dimensional spaces In this paper we describe a dynamic index structure called an R-tree which meets this need, and give algorithms for searching and updating it. We present the results of a series of tests which indicate that the structure performs well, and conclude that it is useful for current database systems in spatial applications

R-trees: a dynamic index structure for spatial searching

A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent objects using known techniques from the sequential domain. Linearizability provides the illusion that each operation applied by concurrent processes takes effect instantaneously at some point between its invocation and its response, implying that the meaning of a concurrent object's operations can be given by pre- and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.

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Linearizability: a correctness condition for concurrent objects

Generative communication is the basis of a new distributed programming langauge that is intended for systems programming in distributed settings generally and on integrated network computers in particular. It differs from previous interprocess communication models in specifying that messages be added in tuple-structured form to the computation environment, where they exist as named, independent entities until some process chooses to receive them. Generative communication results in a number of distinguishing properties in the new language, Linda, that is built around it. Linda is fully distributed in space and distributed in time; it allows distributed sharing, continuation passing, and structured naming. We discuss these properties and their implications, then give a series of examples. Linda presents novel implementation problems that we discuss in Part II. We are particularly concerned with implementation of the dynamic global name space that the generative communication model requires.

Generative communication in Linda

For single databases, primary hindrances for end-user access are the volume of data that is becoming available, the lack of abstraction, and the need to understand the representation of the data. When information is combined from multiple databases, the major concern is the mismatch encountered in information representation and structure. Intelligent and active use of information requires a class of software modules that mediate between the workstation applications and the databases. It is shown that mediation simplifies, abstracts, reduces, merges, and explains data. A mediator is a software module that exploits encoded knowledge about certain sets or subsets of data to create information for a higher layer of applications. A model of information processing and information system components is described. The mediator architecture, including mediator interfaces, sharing of mediator modules, distribution of mediators, and triggers for knowledge maintenance, are discussed. >

Mediators in the architecture of future information systems

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 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. New in this Edition: New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. Coverage of emerging topics such as data streams and cloud computing Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.

Principles of Distributed Database Systems

In database systems, users access shared data under the assumption that the data satisfies certain consistency constraints. This paper defines the concepts of transaction, consistency and schedule and shows that consistency requires that a transaction cannot request new locks after releasing a lock. Then it is argued that a transaction needs to lock a logical rather than a physical subset of the database. These subsets may be specified by predicates. An implementation of predicate locks which satisfies the consistency condition is suggested.

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The notions of consistency and predicate locks in a database system

System R is a database management system which provides a high level relational data interface. The systems provides a high level of data independence by isolating the end user as much as possible from underlying storage structures. The system permits definition of a variety of relational views on common underlying data. Data control features are provided, including authorization, integrity assertions, triggered transactions, a logging and recovery subsystem, and facilities for maintaining data consistency in a shared-update environment.This paper contains a description of the overall architecture and design of the system. At the present time the system is being implemented and the design evaluated. We emphasize that System R is a vehicle for research in database architecture, and is not planned as a product.

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System R: relational approach to database management

The recovery subsystem of an experimental data management system is described and evaluated. The transactmn concept allows application programs to commit, abort, or partially undo their effects. The DO-UNDO-REDO protocol allows new recoverable types and operations to be added to the recovery system Apphcation programs can record data m the transaction log to facilitate application-specific recovery. Transaction undo and redo are based on records kept in a transaction log. The checkpoint mechanism is based on differential fries (shadows). The recovery log is recorded on disk rather than tape.

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The Recovery Manager of the System R Database Manager

The problem of choosing the appropriate Hranularit~ (size) of lockable objects is introduced and the tradeoff between concurrency and overhead is discusseS. A locking protocol which allows simultaneous locking at various granularities by different transactions is presented. It is based on the introduction of additional lock modes besides the conventional share mode an5 exclusive mode. A proof is given of the equivalence of this protocol to a conventional one.

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Granularity of locks and degrees of consistency in a shared data base

System R, an experimental database system, was constructed to demonstrate that the usability advantages of the relational data model can be realized in a system with the complete function and high performance required for everyday production use. This paper describes the three principal phases of the System R project and discusses some of the lessons learned from System R about the design of relational systems and database systems in general.

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Irving L. Traiger

Papers

The notions of consistency and predicate locks in a database system

System R: relational approach to database management

The Recovery Manager of the System R Database Manager

Granularity of locks and degrees of consistency in a shared data base

A history and evaluation of System R