Recommending XML physical designs for XML databases

Recommending XML physical designs for XML databases Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures for a given database. XML database systems are increasingly being used to manage semi-structured data, and XML support has been added to commercial database systems. In this paper, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a database and a query workload. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system, and they rely on the optimizer for enumerating and evaluating physical designs. We have implemented our advisors in a prototype version of IBM DB2 V9, and we experimentally demonstrate the effectiveness of their recommendations using this implementation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Recommending XML physical designs for XML databases

Loading next page...
 
/lp/springer_journal/recommending-xml-physical-designs-for-xml-databases-JlfYrTOz9d
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2013 by Springer-Verlag Berlin Heidelberg
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-012-0298-2
Publisher site
See Article on Publisher Site

Abstract

Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures for a given database. XML database systems are increasingly being used to manage semi-structured data, and XML support has been added to commercial database systems. In this paper, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a database and a query workload. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system, and they rely on the optimizer for enumerating and evaluating physical designs. We have implemented our advisors in a prototype version of IBM DB2 V9, and we experimentally demonstrate the effectiveness of their recommendations using this implementation.

Journal

The VLDB JournalSpringer Journals

Published: Aug 1, 2013

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off