'Query processing' diaporamas de présentation

Structure and Content Scoring for XML. Amélie Marian (Columbia University) Joint work with: Sihem Amer-Yahia (AT&T Research Labs) Nick Koudas (University of Toronto) Divesh Srivastava (AT&T Research Labs) David Toman (University of Waterloo). book. info. edition (paperback). author

Chapter 15: Query Processing. Chapter 15: Query Processing. Overview Measures of Query Cost Selection Operation Sorting Join Operation Other Operations Evaluation of Expressions. Basic Steps in Query Processing. 1. Parsing and translation 2. Optimization 3. Evaluation.

Physical Database Design & Performance. Optimizing for Query Performance. For DBs with high retrieval traffic as compared to maintenance traffic, optimizing the DB for query performance is the primary goal. The amount of work required to do so greatly depends on the type of DBMS.

The Future of MOCHA. Nick Roussopoulos October 5, 2001. The Problem. Distributed and heterogeneous data sources. Data Sources for an enterprise are : Distributed Internet, intranets, extranets Heterogeneous Web servers, relational databases, file systems Mission-critical

CS520 Web Programming Full Text Search. Chengyu Sun California State University, Los Angeles. Search Text. Web search Desktop search Applications Search posts in a bulletin board Search product descriptions at an online retailer …. Database Query.

Data Integration: The Teenage Years. Alon Halevy (Google) Anand Rajaraman (Kosmix) Joann Ordille (Avaya) VLDB 2006. Agenda. A few perspectives on the last 10 years Technical, commercial Perspectives from our personal paths Wild speculations about the future

Query Processing and Networking Infrastructures. Day 1 of 2 Joe Hellerstein UC Berkeley Septemer 20, 2002. Two Goals. Day 1: Primer on query processing Targeted to networking/OS folk Bias: systems issues Day 2: Seed some cross-fertilized research Especially with networking

Outline. Introduction Background Distributed DBMS Architecture Distributed Database Design (Briefly) Distributed Query Processing (Briefly) Distributed Transaction Management (Extensive) Building Distributed Database Systems (RAID) Mobile Database Systems

The Design of an Acquisitional Query Processor For Sensor Networks. Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei Hong Presentated By Muhammed Z. Miah May 02, 2006. Goals. Provide a query processor for data collection in sensor networks

Result presentation. Search Interface. Input and output functionality helping the user to formulate complex queries presenting the results in an intelligent manner Semantic Search brings improvements in Query formulation Snippet generation Adaptive and interactive presentation

ICS 214B: Transaction Processing and Distributed Data Management. Lecture 10: Distributed Query Optimization Professor Chen Li. Optimization Process Overview. Generate query plans Estimate size of intermediate results Estimate cost of plan ($,time,…). P 2. P 3. P n. P 1.

CS276 Information Retrieval and Web Search Pandu Nayak and Prabhakar Raghavan Lecture 1: Boolean retrieval. Information Retrieval.

Static Analysis and Verification. i n Databases. Victor Vianu U.C. San Diego. What is it?. Reasoning about queries and applications to guarantee. correctness. g ood performance. Important to experts . SQL queries. Expert user. Database Server. … but also to the public at large.

Query Processing of Massive Trajectory Data based on MapReduce. Qiang Ma, Bin Yang ( Fudan University) Weining Qian , Aoying Zhou (ECNU) Presented By: Xin Cao (Aalborg University). Outline. Introduction Preliminary Trajectory Processing Execution Overview Storage Indexing Methods

Massively Distributed Database Systems - Distributed DBS. Spring 2014 Ki- Joune Li http://isel.cs.pusan.ac.kr/~lik Pusan National University. Pros and Cons. Software Cost and Complexity Processing Overhead Data Integrity Slow Response Disadvantages. Reliability and Availability

Querying Encrypted Data using Fully Homomorphic Encryption. Murali Mani, UMFlint Talk given at CIDR, Jan 7, 2013. Scenario. Hand over data. Content-Owner (Client). Request content (Query). Limited resources (cannot host data). Cloud Service Provider (Content Host)

Lecture 1 : Full-text Indexing. 楊立偉教授 台灣科大資管系 wyang@ntu.edu.tw 本投影片修改自 Introduction to Information Retrieval 一書之 投影片 Ch 1 & 2. Definition of information retrieval. Information retrieval (IR) is finding material (usually documents) of

Online Filtering, Smoothing & Probabilistic Modeling of Streaming Data In short, Applying probabilistic models to Streams. Bhargav Kanagal & Amol Deshpande University of Maryland. Motivation.

Correlated Queries. A nested query that requires the subquery to be evaluated many times; once for each value in the outer query. Example: Find movies whose title appears more than once. SELECT title FROM Movie AS Old WHERE year < ANY ( SELECT year

Model-Based Mediation with Domain Maps . Bertram Ludäscher * Amarnath Gupta * Maryann E. Martone +. * San Diego Supercomputer Center (SDSC) + National Center for Microscopy and Imaging Research (NCMIR) University of California, San Diego (UCSD). Overview. Motivation