Data Stream Management

This book PDF is perfect for those who love Computers genre, written by Lukasz Golab and published by Morgan & Claypool Publishers which was released on 19 May 2024 with total hardcover pages 65. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Data Stream Management books below.

Data Stream Management
Data Stream Management
Author : Lukasz Golab
File Size : 42,9 Mb
Publisher : Morgan & Claypool Publishers
Language : English
Release Date : 19 May 2024
ISBN : 9781608452729
Pages : 65 pages
Get Book

Data Stream Management by Lukasz Golab Book PDF Summary

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

Data Stream Management

Data Stream Management by Lukasz Golab,M. Tamer Özsu

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

Get Book
Stream Data Management

Stream Data Management by Nauman Chaudhry,Kevin Shaw,Mahdi Abdelguerfi

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

Get Book
Data Stream Management

Data Stream Management by Minos Garofalakis,Johannes Gehrke,Rajeev Rastogi

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

Get Book
Stream Data Processing A Quality of Service Perspective

Stream Data Processing A Quality of Service Perspective by Sharma Chakravarthy,Qingchun Jiang

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 (

Get Book
Stream Data Management

Stream Data Management by Nauman Chaudhry,Kevin Shaw

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

Get Book
Data Management and Query Processing in Semantic Web Databases

Data Management and Query Processing in Semantic Web Databases by Sven Groppe

The Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (

Get Book
Real Time Stream Data Management

Real Time Stream Data Management by Wolfram Wingerath,Norbert Ritter,Felix Gessert

While traditional databases excel at complex queries over historical data, they are inherently pull-based and therefore ill-equipped to push new information to clients. Systems for data stream management and processing, on the other hand, are natively pushoriented and thus facilitate reactive behavior. However, they do not retain data indefinitely and

Get Book
Spatio Temporal Data Streams

Spatio Temporal Data Streams by Zdravko Galić

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques.

Get Book