The Picasso database query optimizer visualizer
Author(s) -
Jayant R. Haritsa
Publication year - 2010
Publication title -
proceedings of the vldb endowment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 134
ISSN - 2150-8097
DOI - 10.14778/1920841.1921027
Subject(s) - query optimization , computer science , sargable , query plan , sql , query expansion , online aggregation , query language , query by example , database , web query classification , view , spatial query , web search query , data mining , information retrieval , database design , search engine
Modern database systems employ a query optimizer module to automatically identify the most efficient strategies for executing the declarative SQL queries submitted by users. The efficiency of these strategies, called "plans", is measured in terms of "costs" that are indicative of query response times. Optimization is a mandatory exercise since the difference between the costs of the best execution plan, and a random choice, could be in orders of magnitude. The role of query optimizers has become especially critical during this decade due to the high degree of processing complexity characterizing current data warehousing and mining applications, as exemplified by the TPC-H and TPC-DS decision support benchmarks [20, 21].
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