Download or read book Adaptive Query Processing in Data Stream Management Systems written by Shivnath Babu and published by . This book was released on 2005 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Query Processing written by Amol Deshpande and published by Now Publishers Inc. This book was released on 2007 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Query Processing surveys the fundamental issues, techniques, costs, and benefits of adaptive query processing. It begins with a broad overview of the field, identifying the dimensions of adaptive techniques. It then looks at the spectrum of approaches available to adapt query execution at runtime - primarily in a non-streaming context. The emphasis is on simplifying and abstracting the key concepts of each technique, rather than reproducing the full details available in the papers. The authors identify the strengths and limitations of the different techniques, demonstrate when they are most useful, and suggest possible avenues of future research. Adaptive Query Processing serves as a valuable reference for students of databases, providing a thorough survey of the area. Database researchers will benefit from a more complete point of view, including a number of approaches which they may not have focused on within the scope of their own research.
Download or read book Data Stream Management written by Lukasz Golab and published by Springer Nature. This book was released on 2022-06-01 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Data Stream Management written by Minos Garofalakis and published by Springer. This book was released on 2016-07-11 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.
Download or read book Shared Query Processing in Data Streaming Systems written by Saileshwar Krishnamurthy and published by . This book was released on 2006 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stream Data Management written by Nauman Chaudhry and published by Springer Science & Business Media. This book was released on 2005-09-19 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.
Download or read book Data Stream Management written by Lukasz Golab and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Efficient adaptive query processing on large database systems available in the cloud environment written by Clayton Maciel Costa and published by Simplíssimo. This book was released on 2020-09-15 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, many companies are migrating their applications and data to cloud service providers, mainly because of their ability to answer quickly to business requirements. Thereby, the performance is an important requirement for most customers when they wish to migrate their applications to the cloud. Therefore, in cloud environments, resources should be acquired and released automatically and quickly at runtime. Moreover, the users and service providers expect to get answers in time to ensure the service SLA (Service Level Agreement). Consequently, ensuring the QoS (Quality of Service) is a great challenge and it increases when we have large amounts of data to be manipulated in this environment. To resolve this kind of problems, several researches have been focused on shorter execution time using adaptive query processing and/or prediction of resources based on current system status. However, they present important limitations. For example, most of these works does not use monitoring during query execution and/or presents intrusive solutions, i.e. applied to the particular context. The aim of this book is to present the development of new solutions/strategies to efficient adaptive query processing on large databases available in a cloud environment. It must integrate adaptive re-optimization at query runtime and their costs are based on the SRT (Service Response Time – SLA QoS performance parameter). Finally, the proposed solution will be evaluated on large scale with large volume of data, machines and queries in a cloud computing infrastructure. Finally, this work also proposes a new model to estimate the SRT for different request types (database access requests). This model will allow the cloud service provider and its customers to establish an appropriate SLA relative to the expected performance of the services available in the cloud.
Download or read book Advanced Query Processing written by Barbara Catania and published by Springer Science & Business Media. This book was released on 2012-07-28 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research book presents key developments, directions, and challenges concerning advanced query processing for both traditional and non-traditional data. A special emphasis is devoted to approximation and adaptivity issues as well as to the integration of heterogeneous data sources. The book will prove useful as a reference book for senior undergraduate or graduate courses on advanced data management issues, which have a special focus on query processing and data integration. It is aimed for technologists, managers, and developers who want to know more about emerging trends in advanced query processing.
Download or read book Scalable and Robust Stream Processing written by Vladislav Shkapenyuk and published by . This book was released on 2007 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-rate data streams in real-time. An effective query optimization mechanism is a critical component that allows DSMS to deal with extreme data rates and large numbers of long-running concurrent queries. This dissertation investigates how to utilize semantic query analysis to perform query optimizations that enable scalable and robust data stream processing. We address three technical challenges faced by streaming system: (1) monitoring and correlating large number of diverse data streams with significant variations in data rates; (2) the ability to remain stable and produce correct answers even under overload conditions, and (3) supporting efficient distributed query processing to easily scale with increases in the number of processing nodes and stream data rates. First, we propose a heartbeat mechanism to prevent the DSMS from blocking when some of the monitored streams temporarily stall or slow down. By generating special punctuation messages at low-level query nodes and propagating them throughout the entire query execution plan, our heartbeat mechanism effectively unblocks all stalled query nodes. The second contribution of this dissertation addresses the problem of DSMS robustness when a load on a system increases by orders of magnitude. We introduce a query-aware sampling mechanism for guaranteeing the system's stability and the correctness of its query output under overload conditions. The mechanism is generic and supports arbitrary complex query sets. Finally, we address the problem of scalable distributed evaluation of streaming queries. The key contribution of the dissertation is a query-aware partitioning mechanism that allows us to scale the performance of the streaming queries in a close to linear fashion. We propose a query analysis framework for determining the optimal partitioning and a partition-aware distributed query optimizer that takes advantage of existing partitions. In summary, the contributions made by this dissertation in the area of streaming query optimization enable Data Stream Management Systems to scale to extreme data rates, gracefully handle overload conditions and support a large number of diverse input streams, enabling industrial-scale applications of DSMS technology.
Download or read book Adaptive Query Processing written by Pedro G. Bizarro and published by . This book was released on 2006 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Data and Web Management written by Guozhu Dong and published by Springer. This book was released on 2007-06-26 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joint 9th Asia-Pacific Web Conference, APWeb 2007, and the 8th International Conference on Web-Age Information Management, WAIM 2007, held in Huang Shan, China, June 2007. Coverage includes data mining and knowledge discovery, P2P systems, sensor networks, spatial and temporal databases, Web mining, XML and semi-structured data, privacy and security, as well as data mining and data streams.
Download or read book Data Streams written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2007-04-03 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.
Download or read book Data Management in Pervasive Systems written by Francesco Colace and published by Springer. This book was released on 2015-10-17 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to illustrating the methodological and technological issues of data management in Pervasive Systems by using the DataBenc project as the running case study for a variety of research contributions: sensor data management, user-originated data operation and reasoning, multimedia data management, data analytics and reasoning for event detection and decision making, context modelling and control, automatic data and service tailoring for personalization and recommendation. The book is organized into the following main parts: i) multimedia information management; ii) sensor data streams and storage; iii) social networks as information sources; iv) context awareness and personalization. The case study is used throughout the book as a reference example.
Download or read book Stream Data Processing A Quality of Service Perspective written by Sharma Chakravarthy and published by Springer Science & Business Media. This book was released on 2009-04-09 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.
Download or read book The Semantic Web ISWC 2011 written by Lora Aroyo and published by Springer Science & Business Media. This book was released on 2011-10-26 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 7031 and LNCS 7032 constitutes the proceedings of the 10th International Semantic Web Conference, ISWC 2011, held in Bonn, Germany, in October 2011. Part I, LNCS 7031, contains 50 research papers which were carefully reviewed and selected from 264 submissions. The 17 semantic Web in-use track papers contained in part II, LNCS 7032, were selected from 75 submissions. This volume also contains 15 doctoral consortium papers, selected from 31 submissions. The topics covered are: ontologies and semantics; database, IR, and AI technologies for the semantic Web; management of semantic Web data; reasoning over semantic Web data; search, query, integration, and analysis on the semantic Web; robust and scalable knowledge management and reasoning on the Web; interacting with semantic Web data; ontology modularity, mapping, merging and alignment; languages, tools, and methodologies for representing and managing semantic Web data; ontology, methodology, evaluation, reuse, extraction and evolution; evaluation of semantic Web technologies or data; specific ontologies and ontology pattern for the semantic Web; new formalisms for semantic Web; user interfaces to the semantic Web; cleaning, assurance, and provenance of semantic Web data; services, and processes; social semantic Web, evaluation of semantic Web technology; semantic Web population from the human Web.
Download or read book Encyclopedia of Information Science and Technology First Edition written by Khosrow-Pour, D.B.A., Mehdi and published by IGI Global. This book was released on 2005-01-31 with total page 3807 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive coverage of critical issues related to information science and technology.
