Author:
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 316
Book Description
Proceedings of the Twentieth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems
Author:
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 316
Book Description
Publisher:
ISBN:
Category : Computer science
Languages : en
Pages : 316
Book Description
Sigmod/pods '18
Author: Christopher Jermaine
Publisher:
ISBN: 9781450347037
Category :
Languages : en
Pages :
Book Description
SIGMOD/PODS '18: International Conference on Management of Data Jun 03, 2018-Jun 08, 2018 Houston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Publisher:
ISBN: 9781450347037
Category :
Languages : en
Pages :
Book Description
SIGMOD/PODS '18: International Conference on Management of Data Jun 03, 2018-Jun 08, 2018 Houston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data
Author: Peter Buneman
Publisher: Assn for Computing Machinery
ISBN: 9780897915922
Category : Computer science
Languages : en
Pages : 566
Book Description
Publisher: Assn for Computing Machinery
ISBN: 9780897915922
Category : Computer science
Languages : en
Pages : 566
Book Description
Principles of Distributed Database Systems
Author: M. Tamer Özsu
Publisher: Springer Science & Business Media
ISBN: 1441988343
Category : Computers
Languages : en
Pages : 856
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 1441988343
Category : Computers
Languages : en
Pages : 856
Book Description
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.
Probabilistic Databases
Author: Dan Suciu
Publisher: Morgan & Claypool Publishers
ISBN: 1608456803
Category : Computers
Languages : en
Pages : 183
Book Description
Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced Techniques
Publisher: Morgan & Claypool Publishers
ISBN: 1608456803
Category : Computers
Languages : en
Pages : 183
Book Description
Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced Techniques
Data Stream Management
Author: Lukasz Golab
Publisher: Morgan & Claypool Publishers
ISBN: 1608452727
Category : Computers
Languages : en
Pages : 65
Book Description
In this lecture many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs). A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization. The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage. Table of Contents: Introduction / Data Stream Management Systems / Streaming Data Warehouses / Conclusions
Publisher: Morgan & Claypool Publishers
ISBN: 1608452727
Category : Computers
Languages : en
Pages : 65
Book Description
In this lecture many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs). A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization. The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage. Table of Contents: Introduction / Data Stream Management Systems / Streaming Data Warehouses / Conclusions
Database System Implementation
Author: Garcia-Molina
Publisher: Pearson Education India
ISBN: 9788131704134
Category :
Languages : en
Pages : 676
Book Description
Publisher: Pearson Education India
ISBN: 9788131704134
Category :
Languages : en
Pages : 676
Book Description
Data Models, Database Languages and Database Management Systems
Author: Gottfried Vossen
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 616
Book Description
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 616
Book Description
Foundations of Deductive Databases and Logic Programming
Author: Jack Minker
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 760
Book Description
Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming. The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs. The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 760
Book Description
Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming. The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs. The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.
Principles of Database Systems
Author: Jeffrey D. Ullman
Publisher: Galgotia Publications
ISBN: 9788175155459
Category : Database management
Languages : en
Pages : 670
Book Description
Publisher: Galgotia Publications
ISBN: 9788175155459
Category : Database management
Languages : en
Pages : 670
Book Description