skip to content
Probabilistic diagnosis of hot spots Preview this item
ClosePreview this item
Checking...

Probabilistic diagnosis of hot spots

Author: Kenneth Salem; Daniel Barbara; Richard J Lipton
Publisher: Princeton, N.J. : Princeton University, Dept. of Computer Science, [1991]
Series: Princeton University.; Department of Computer Science.; Technical report
Edition/Format:   Book : EnglishView all editions and formats
Database:WorldCat
Summary:
Abstract: "Commonly, a few objects in a database account for a large share of all database accesses. These objects are called hot spots. The ability to determine which objects are hot spots opens the door to a variety of performance improvements. Data reorganization, migration, and replication techniques can take advantage of knowledge of hot spots to improve performance at low cost. In this paper we present some
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

 

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Document Type: Book
All Authors / Contributors: Kenneth Salem; Daniel Barbara; Richard J Lipton
OCLC Number: 24771521
Notes: "June 1991."
Description: 22, [6] pages : illustrations ; 28 cm.
Series Title: Princeton University.; Department of Computer Science.; Technical report
Responsibility: Kenneth Salem, Daniel Barbara, Richard J. Lipton.

Abstract:

Abstract: "Commonly, a few objects in a database account for a large share of all database accesses. These objects are called hot spots. The ability to determine which objects are hot spots opens the door to a variety of performance improvements. Data reorganization, migration, and replication techniques can take advantage of knowledge of hot spots to improve performance at low cost. In this paper we present some techniques that can be used to identify those objects in the database that account for more than a specified percentage of database accesses. Identification is accomplished by analyzing a string of database references and collecting statistics.

Depending on the length of the reference string and the amount of space available for the analysis, each technique will have a non-zero probability of false diagnosis, i.e., mistaking 'cold' items for hot spots and vice versa. We compare the techniques analytically and show the tradeoffs among time, space and the probability of false diagnoses."

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.

Similar Items

Related Subjects:(1)

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


<http://www.worldcat.org/oclc/24771521>
library:oclcnum"24771521"
library:placeOfPublication
library:placeOfPublication
owl:sameAs<info:oclcnum/24771521>
rdf:typeschema:Book
schema:about
schema:about
schema:contributor
schema:contributor
schema:creator
schema:datePublished"1991"
schema:description"Depending on the length of the reference string and the amount of space available for the analysis, each technique will have a non-zero probability of false diagnosis, i.e., mistaking 'cold' items for hot spots and vice versa. We compare the techniques analytically and show the tradeoffs among time, space and the probability of false diagnoses.""@en
schema:description"Abstract: "Commonly, a few objects in a database account for a large share of all database accesses. These objects are called hot spots. The ability to determine which objects are hot spots opens the door to a variety of performance improvements. Data reorganization, migration, and replication techniques can take advantage of knowledge of hot spots to improve performance at low cost. In this paper we present some techniques that can be used to identify those objects in the database that account for more than a specified percentage of database accesses. Identification is accomplished by analyzing a string of database references and collecting statistics."@en
schema:exampleOfWork<http://worldcat.org/entity/work/id/26781936>
schema:inLanguage"en"
schema:name"Probabilistic diagnosis of hot spots"@en
schema:publisher
schema:url

Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.