Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Ian Charlesworth

dblp:116/5143 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-0546-2856ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › query optimization
join enumeration
0.112012
Analyzing Query Optimization Process: Portraits of Join Enumeration Algorithms · ICDE 2012
Query processing and optimization
query optimization
0.112012
Analyzing Query Optimization Process: Portraits of Join Enumeration Algorithms · ICDE 2012

Methods — techniques the papers use, named apart from their topics

visualization · 0.1optimization log mining · 0.1
YearPublicationVenuePosition
2012 Analyzing Query Optimization Process: Portraits of Join Enumeration Algorithms
abstract
Search spaces generated by query optimizers during the optimization process encapsulate characteristics of the join enumeration algorithms, the cost models, as well as critical decisions made for pruning and choosing the best plan. We demonstrate the Join Enumeration Viewer which is a tool designed for visualizing, mining, and comparing plan search spaces generated by different join enumeration algorithms when optimizing same SQL statement. We have enhanced Sybase SQL Anywhere relational database management system to log, in a very compact format, its search space during an optimization process. Such optimization log can then be analyzed by the Join Enumeration Viewer which internally builds the logical and physical plan graphs representing complete and partial plans considered during the optimization process. The optimization logs also contain statistics of the resource consumption during the query optimization such as optimization time breakdown, for example, for logical join enumeration versus costing physical plans, and memory allocation for different optimization structures. The SQL Anywhere Optimizer implements a highly adaptable, self-managing, search space generation algorithm by having several join enumeration algorithms to choose from, each enhanced with different ordering and pruning techniques. The emphasis of the demonstration will be on comparing and contrasting these join enumeration algorithms by analyzing their optimization logs. The demonstration scenarios will include optimizing SQL statements under various conditions which will exercise different algorithms, pruning and ordering techniques. These search spaces will then be visualized and compared using the Join Enumeration Viewer.
Anisoara Nica, Ian Charlesworth
ICDE2