'Query evaluation' presentation slideshows

Cleaning Uncertain Data for Top-k Queries

Cleaning Uncertain Data for Top-k Queries. Luyi Mo , Reynold Cheng, Xiang Li, David Cheung, Xuan Yang The University of Hong Kong { lymo , ckcheng , xli, dcheung , xyang2}@ cs.hku.hk. Outline. Introduction Quality Metric for Top-k Queries Definition Efficient computation Results

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Web 2.0 Data Analysis

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Chip-Secured Data Access: Confidential Data on Untrusted Serves

625 views • 45 slides

Containment of Partially Specified Tree-Pattern Queries

Containment of Partially Specified Tree-Pattern Queries. Dimitri Theodoratos (NJIT, USA) Theodore Dalamagas (NTUA, GREECE) Pawel Placek (NJIT, USA) Stefanos Souldatos (NTUA, GREECE) Timos Sellis (NTUA, GREECE). Introduction. r. GREECE. USA. ATHENS. YAMAHA. BMW. HONDA. YAMAHA. BMW.

558 views • 44 slides

A distributed agent architecture and case-based approach for information system integration

A distributed agent architecture and case-based approach for information system integration. Computer Science Institute University of Ancona. Loris Penserini (pense@inform.unian.it). In collaboration with:. Maurizio Panti (panti@inform.unian.it) Luca Spalazzi (spalazzi@inform.unian.it).

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Efficient Keyword Search over Virtual XML Views

Efficient Keyword Search over Virtual XML Views. Feng Shao and Lin Guo and Chavdar Botev and Anand Bhaskar and Muthiah Chettiar and Fan Yang Cornell University Jayavel Shanmugasundaram Yahoo! Research 2008. 02. 14. Summarized by Dongmin Shin , IDS Lab., Seoul National University

398 views • 32 slides

Supporting Q ueries and Analyses of Large-Scale Social Media Data with Customizable and Scalable Indexing Techniques

Supporting Q ueries and Analyses of Large-Scale Social Media Data with Customizable and Scalable Indexing Techniques over NoSQL databases. Xiaoming Gao, Judy Qiu Indiana University CCGrid 2014. Outline. Motivation and research challenges

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A Course on Probabilistic Databases

A Course on Probabilistic Databases. Dan Suciu University of Washington. Outline. Part 1. Motivating Applications The Probabilistic Data Model Chapter 2 Extensional Query Plans Chapter 4.2 The Complexity of Query Evaluation Chapter 3 Extensional Evaluation Chapter 4.1

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Overview of Query Evaluation

Overview of Query Evaluation. R&G Chapter 12 Lecture 13. Administrivia. Exams graded HW2 due in a week No Office Hours Today. Query Optimization and Execution. Relational Operators. Files and Access Methods. Buffer Management. Disk Space Management. DB. Review: Storage.

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SKOS Ecoterm 2006 Alistair Miles CCLRC Rutherford Appleton Laboratory

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Query Evaluation

Query Evaluation. SQL to ERA. SQL queries are translated into extended relational algebra. Query evaluation plans are represented as trees of relational operators, with labels identifying the algorithm to use at each node.

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Sedna: A Native XML DBMS

Sedna: A Native XML DBMS. Andrey Fomichev Maxim Grinev Sergey Kuznetsov Institute for System Programming of RAS. SOFSEM 2006 23 January. Agenda. Sedna overview and goals Data organization Memory management Query evaluation Conclusion. Challenges.

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Dynamic Queries over Mobile Objects

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Database Design

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Database Design

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Using Partial Evaluation in Distributed Query Evaluation

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Relation Caching

Relation Caching. Ravindra N. Guravannavar. Introduction. Relation Caching is a logical caching technique Reduces the client-server data transfer by exploiting the client resources Can be employed in a query-shipping architecture. Applicability. Select-Project queries on a single relation

226 views • 9 slides