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Dynamic optimization of query execut...

Ng, Kenneth Wenghang.

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Dynamic optimization of query execution plans.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dynamic optimization of query execution plans./
作者:	Ng, Kenneth Wenghang.
面頁冊數:	103 p.
附註:	Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3374.
Contained By:	Dissertation Abstracts International60-07B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9939079
ISBN:	0599404132

Dynamic optimization of query execution plans.
Ng, Kenneth Wenghang.

Dynamic optimization of query execution plans. - 103 p.

Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3374.

Thesis (Ph.D.)--University of California, Los Angeles, 1999.

Massive database sizes and growing demands for decision support and data mining result in long-running queries in extensible object relational database systems, particularly in non-traditional application domains such as geo-scientific computing, image processing and data warehousing analysis. Full support of parallelism in query evaluation is desired for acceptable performance. However, queries are frequently processed sub-optimally due to (1) only coarse or inaccurate estimates of the query characteristics and database statistics available prior to query evaluation; (2) changes in system configuration and resource availability during query evaluation. In a distributed environment, dynamically reconfiguring query execution plans (QEPs), which adapts QEPs to the environment as well as the query characteristics, is a promising means to significantly improve query evaluation performance. By introducing the concepts of windows and abstract data type orderings, we have developed a novel approach for classifying operators in a distributed query processing environment. Based on such a classification, we have designed triggered run-time optimization mechanisms to re-optimize suboptimal query plan configurations on-the-fly. In addition, we have implemented an algorithm to coordinate the steps in a reconfiguration and introduce alternatives for execution context check-pointing and restoring. Experimental results are reported and discussed.

ISBN: 0599404132Subjects--Topical Terms:

626642
Computer Science.

Dynamic optimization of query execution plans.
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500 $a Source: Dissertation Abstracts International, Volume: 60-07, Section: B, page: 3374.
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502 $a Thesis (Ph.D.)--University of California, Los Angeles, 1999.
520 $a Massive database sizes and growing demands for decision support and data mining result in long-running queries in extensible object relational database systems, particularly in non-traditional application domains such as geo-scientific computing, image processing and data warehousing analysis. Full support of parallelism in query evaluation is desired for acceptable performance. However, queries are frequently processed sub-optimally due to (1) only coarse or inaccurate estimates of the query characteristics and database statistics available prior to query evaluation; (2) changes in system configuration and resource availability during query evaluation. In a distributed environment, dynamically reconfiguring query execution plans (QEPs), which adapts QEPs to the environment as well as the query characteristics, is a promising means to significantly improve query evaluation performance. By introducing the concepts of windows and abstract data type orderings, we have developed a novel approach for classifying operators in a distributed query processing environment. Based on such a classification, we have designed triggered run-time optimization mechanisms to re-optimize suboptimal query plan configurations on-the-fly. In addition, we have implemented an algorithm to coordinate the steps in a reconfiguration and introduce alternatives for execution context check-pointing and restoring. Experimental results are reported and discussed.
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