'Range queries' diaporamas de présentation

In-Network Query Processing

679 views • 56 slides

Multidimensional Indexing: Spatial Data Management & High Dimensional Indexing

Multidimensional Indexing: Spatial Data Management & High Dimensional Indexing. Types of Spatial Data. Point Data Points in a multidimensional space E.g., Raster data such as satellite imagery, where each pixel stores a measured value E.g., Feature vectors extracted from text Region Data

803 views • 55 slides

OS Support / Indexing

OS Support / Indexing. Lecture 3. Query Execution. Query or update. User/ Application. Query compiler. Query execution plan. Execution engine. Record, index requests. Index/record mgr. Page commands. Buffer manager. Read/write pages. Storage manager.

633 views • 50 slides

Chapter 20: Parallel Databases

Introduction I/O Parallelism Interquery Parallelism Intraquery Parallelism Intraoperation Parallelism Interoperation Parallelism Design of Parallel Systems. Chapter 20: Parallel Databases. Parallel machines are becoming quite common and affordable

626 views • 42 slides

Database scalability and indexes

708 views • 42 slides

Indexing

Indexing. Extract specific information from data and access data through it attributes, attribute vectors Two step retrieval: hypothesis : search through the index returns all qualifying documents plus some false alarms verification : the answer is examined to eliminate false alarms.

563 views • 41 slides

Chapter 9 of DBMS

Chapter 9 of DBMS. First we look at a simple (strawman) approach (ISAM). We will see why it is unsatisfactory. This will motivate the B+Tree Read 9.1 to 9.5 Glance at 9.6 and 9.8.2

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579 views • 32 slides

Lecture 5: Indexing: R-Trees

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Supporting Spatial Semantics with SPARQL

Supporting Spatial Semantics with SPARQL. Dave Kolas, BBN Technologies Terra Cognita 08 Karlsruhe, Germany 10/26/08. Presentation Outline. Background Information What is SPARQL, anyway? Why does anyone care about spatial semantics? Related Work Object-Relational + Spatial XML + Spatial

427 views • 27 slides

Multi-dimensional Indexes

Multi-dimensional Indexes. 198:541. Types of Spatial Data. Point Data Points in a multidimensional space E.g., Raster data such as satellite imagery, where each pixel stores a measured value E.g., Feature vectors extracted from text Region Data

358 views • 26 slides

External Memory Hashing

External Memory Hashing. Model of Computation. CPU. Memory. Data stored on disk(s) Minimum transfer unit: a page = b bytes or B records (or block) N records -> N/B = n pages I/O complexity: in number of pages. Disk. I/O complexity.

313 views • 22 slides

Spatial Data Management

Spatial Data Management. Chapter 28. Types of Spatial Data. Point Data Points in a multidimensional space E.g., Raster data such as satellite imagery, where each pixel stores a measured value E.g., Feature vectors extracted from text Region Data

1.22k views • 21 slides

Introduction to NoSQL databases and CS554 projects based on ZHT

Overview on ZHT. Introduction to NoSQL databases and CS554 projects based on ZHT. Outlines. General terms Overview to NoSQL dabases and key-value stores Introduction to ZHT CS554 projects . Databases/ datastores. Relational databases Query with SQL DB2, MySQL, Oracle, SQL Server

388 views • 20 slides

Introduction to Hashing & Hashing Techniques

Introduction to Hashing & Hashing Techniques. Review of Searching Techniques Introduction to Hashing Hash Tables Types of Hashing Hash Functions Applications of Hash Tables Problems for which Hash Tables are not suitable. Review of Searching Techniques.

1.09k views • 19 slides

MISTRAL Processing Relational Queries Using the Multidimensional Access Method UB-Tree

MISTRAL Processing Relational Queries Using the Multidimensional Access Method UB-Tree. Prof. R. Bayer, Ph.D. Dr. Volker Markl Dept. of Computer Science, Technical University Munich and Bavarian Research Center for Knowledgebased Systems (FORWISS). Agenda. 1. Concept of the UB-Tree

383 views • 19 slides

Supporting Range Queries on Web Data Using k -Nearest Neighbor Search

Supporting Range Queries on Web Data Using k -Nearest Neighbor Search. Wan D. Bae, Shayma Alkobaisi, Seon Ho Kim, Sada Narayanappa Computer Science, University of Denver and Cyrus Shahabi Computer Science, University of Southern California. W2GIS 2007. Outline. Introduction

283 views • 19 slides

253 views • 18 slides

SELF-CHORD

SELF-CHORD. a Bio-Inspired P2P Framework for Self-Organizing Distributed Systems Agostino Forestiero Emilio Leonardi Carlo Mastroianni Michela Meo Sonal Srivastava. P2P Models. Unstructured. Structured. Better network management L ow efficiency

437 views • 17 slides

R-Trees

R-Trees. Presented By N Jaggan 2001A4A7223. Spatial Data Objects. Cover Multi-Dimensional Spaces Not Represented well by Points Examples include Maps objects like countries, Data elements like gears etc in a machine drawing etc. Why indexing?. Queries should take least possible time

317 views • 11 slides