'Continuous query' diaporamas de présentation

Location-aware Query Processing and Optimization: A Tutorial

Location-aware Query Processing and Optimization: A Tutorial. Mohamed F. Mokbel Walid G. Aref Department of Computer Science and Engineering, University of Minnesota Minneapolis, MN, USA mokbel@cs.umn.edu Department of Computer Science, Purdue University West Lafayette, Indiana, USA.

1.01k views • 86 slides

Location-aware Query Processing and Optimization: A Tutorial

Location-aware Query Processing and Optimization: A Tutorial. Mohamed F. Mokbel Walid G. Aref Department of Computer Science and Engineering, University of Minnesota Minneapolis, MN, USA mokbel@cs.umn.edu Department of Computer Science, Purdue University West Lafayette, Indiana, USA.

878 views • 86 slides

STREAM: The Stanford Data Stream Management System

STREAM: The Stanford Data Stream Management System. ST anfordst RE amdat AM anager http://infolab.stanford.edu/stream/ 69521001 ??? 69521038 ??? 69521040 ???. Outline. Introduction The Continuous Query Language Query Plan and Execution Performance Issue (for query plan)

1.04k views • 74 slides

CQL: A Language for Continuous Queries over Streams and Relations

CQL: A Language for Continuous Queries over Streams and Relations. Jennifer Widom Stanford University Joint work with Arvind Arasu & Shivnath Babu st anfordst re amdat am anager. Data Streams. Continuous, unbounded, rapid, time-varying streams of data elements

622 views • 62 slides

Query Processing, Resource Management, and Approximation in a Data Stream Management System

554 views • 55 slides

Query Processing, Resource Management, and Approximation in a Data Stream Management System

Query Processing, Resource Management, and Approximation in a Data Stream Management System. Selected subset of slides taken from talk by Jennifer Widom at NEDS. st anfordst re amdat am anager. Data Streams. Continuous, unbounded, rapid, time-varying streams of data elements

649 views • 53 slides

Stream Data Management System Prototypes

Stream Data Management System Prototypes. Ying Sheng, Richard Sia June 1, 2004 Professor Carlo Zaniolo CS 240B Spring 2004. Outline. Motivation of DSMS Aurora (Brown, Brandeis, MIT) Model Operator Scheduling Storage/Memory Management QoS issue STREAM (Stanford) System Architecture

485 views • 48 slides

NiagaraCQ: A Scalable Continuous Query System for Internet Databases

521 views • 42 slides

An overview of Data Streaming

ICT Support for Adaptiveness and (Cyber)Security in the Smart Grid DAT285B. An overview of Data Streaming. Vincenzo Gulisano vinmas@chalmers.se (room 5107). Chalmers University of technology. Agenda. Introduction Motivation and System Model Sample Data Streaming application

360 views • 36 slides

Bandwidth-Efficient Continuous Query Processing over DHTs

Bandwidth-Efficient Continuous Query Processing over DHTs. Yingwu Zhu. Background. Instantaneous Query Continuous Query. Instantaneous Query (1). Documents are indexed Node responsible for keyword t stores the IDs of documents containing that term (i.e., inverted lists)

414 views • 28 slides

An Abstract Semantics and Concrete Language for Continuous Queries over Streams and Relations

An Abstract Semantics and Concrete Language for Continuous Queries over Streams and Relations. Presenter: Liyan Zhang Presentation of ICS 224. outline. Introduction Related Work Running Example Streams and Relations Modeling the Running Example Mapping Operators

415 views • 27 slides

CompSci 296.2 Self-Managing Systems

231 views • 20 slides

Aurora: a new model and architecture for data stream management

Aurora: a new model and architecture for data stream management. Daniel J. Abadi 1 , Don Carney 2 , Ugur Cetintemel 2 , Mitch Cherniack 1 , Christian Convey 2 , Sangdon Lee 2 , Michael Stonebraker 3 , Nesime Tatbul 2 , Stan Zdonik 2. 1 Department of Computer Science, Brandeis University

195 views • 14 slides

CAPE: Continuous Query Engine with Heterogeneous-Grained Adaptivity

CAPE: Continuous Query Engine with Heterogeneous-Grained Adaptivity. Elke A. Rundensteiner, Luping Ding, Timothy Sutherland, Yali Zhu Brad Pielech, Nishant Mehta Natasha Bogdanova, Mariana Jbantova Department of Computer Science, Worcester Polytechnic Institute

199 views • 11 slides

How to find frequent items continuously in data streams

120 views • 11 slides