Efficient View Maintenance at Data Warehouses

D. Agrawal, A. El Abbadi, A. Singh, T. Yurek

Research output: Contribution to journalArticle

163 Citations (Scopus)

Abstract

We present incremental view maintenance algorithms for a data warehouse derived from multiple distributed autonomous data sources. We begin with a detailed framework for analyzing view maintenance algorithms for multiple data sources with concurrent updates. Earlier approaches for view maintenance in the presence of concurrent updates typically require two types of messages: one to compute the view change due to the initial update and the other to compensate the view change due to interfering concurrent updates. The algorithms developed in this paper instead perform the compensation locally by using the information that is already available at the data warehouse. The first algorithm, termed SWEEP, ensures complete consistency of the view at the data warehouse in the presence of concurrent updates. Previous algorithms for incremental view maintenance either required a quiescent state at the data warehouse or required an exponential number of messages in terms of the data sources. In contrast, this algorithm does not require that the data warehouse be in a quiescent state for incorporating the new views and also the message complexity is linear in the number of data sources. The second algorithm, termed Nested SWEEP, attempts to compute a composite view change for multiple updates that occur concurrenlty while maintaining strong consistency.

Original languageEnglish
Pages (from-to)417-427
Number of pages11
JournalSIGMOD Record (ACM Special Interest Group on Management of Data)
Volume26
Issue number2
Publication statusPublished - 1 Jun 1997
Externally publishedYes

Fingerprint

Data warehouses
Composite materials

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Information Systems
  • Software

Cite this

Agrawal, D., El Abbadi, A., Singh, A., & Yurek, T. (1997). Efficient View Maintenance at Data Warehouses. SIGMOD Record (ACM Special Interest Group on Management of Data), 26(2), 417-427.

Efficient View Maintenance at Data Warehouses. / Agrawal, D.; El Abbadi, A.; Singh, A.; Yurek, T.

In: SIGMOD Record (ACM Special Interest Group on Management of Data), Vol. 26, No. 2, 01.06.1997, p. 417-427.

Research output: Contribution to journalArticle

Agrawal, D, El Abbadi, A, Singh, A & Yurek, T 1997, 'Efficient View Maintenance at Data Warehouses', SIGMOD Record (ACM Special Interest Group on Management of Data), vol. 26, no. 2, pp. 417-427.
Agrawal, D. ; El Abbadi, A. ; Singh, A. ; Yurek, T. / Efficient View Maintenance at Data Warehouses. In: SIGMOD Record (ACM Special Interest Group on Management of Data). 1997 ; Vol. 26, No. 2. pp. 417-427.
@article{a354c07f43144a06962e6a4a9fd969a8,
title = "Efficient View Maintenance at Data Warehouses",
abstract = "We present incremental view maintenance algorithms for a data warehouse derived from multiple distributed autonomous data sources. We begin with a detailed framework for analyzing view maintenance algorithms for multiple data sources with concurrent updates. Earlier approaches for view maintenance in the presence of concurrent updates typically require two types of messages: one to compute the view change due to the initial update and the other to compensate the view change due to interfering concurrent updates. The algorithms developed in this paper instead perform the compensation locally by using the information that is already available at the data warehouse. The first algorithm, termed SWEEP, ensures complete consistency of the view at the data warehouse in the presence of concurrent updates. Previous algorithms for incremental view maintenance either required a quiescent state at the data warehouse or required an exponential number of messages in terms of the data sources. In contrast, this algorithm does not require that the data warehouse be in a quiescent state for incorporating the new views and also the message complexity is linear in the number of data sources. The second algorithm, termed Nested SWEEP, attempts to compute a composite view change for multiple updates that occur concurrenlty while maintaining strong consistency.",
author = "D. Agrawal and {El Abbadi}, A. and A. Singh and T. Yurek",
year = "1997",
month = "6",
day = "1",
language = "English",
volume = "26",
pages = "417--427",
journal = "SIGMOD Record",
issn = "0163-5808",
publisher = "Association for Computing Machinery (ACM)",
number = "2",

}

TY - JOUR

T1 - Efficient View Maintenance at Data Warehouses

AU - Agrawal, D.

AU - El Abbadi, A.

AU - Singh, A.

AU - Yurek, T.

PY - 1997/6/1

Y1 - 1997/6/1

N2 - We present incremental view maintenance algorithms for a data warehouse derived from multiple distributed autonomous data sources. We begin with a detailed framework for analyzing view maintenance algorithms for multiple data sources with concurrent updates. Earlier approaches for view maintenance in the presence of concurrent updates typically require two types of messages: one to compute the view change due to the initial update and the other to compensate the view change due to interfering concurrent updates. The algorithms developed in this paper instead perform the compensation locally by using the information that is already available at the data warehouse. The first algorithm, termed SWEEP, ensures complete consistency of the view at the data warehouse in the presence of concurrent updates. Previous algorithms for incremental view maintenance either required a quiescent state at the data warehouse or required an exponential number of messages in terms of the data sources. In contrast, this algorithm does not require that the data warehouse be in a quiescent state for incorporating the new views and also the message complexity is linear in the number of data sources. The second algorithm, termed Nested SWEEP, attempts to compute a composite view change for multiple updates that occur concurrenlty while maintaining strong consistency.

AB - We present incremental view maintenance algorithms for a data warehouse derived from multiple distributed autonomous data sources. We begin with a detailed framework for analyzing view maintenance algorithms for multiple data sources with concurrent updates. Earlier approaches for view maintenance in the presence of concurrent updates typically require two types of messages: one to compute the view change due to the initial update and the other to compensate the view change due to interfering concurrent updates. The algorithms developed in this paper instead perform the compensation locally by using the information that is already available at the data warehouse. The first algorithm, termed SWEEP, ensures complete consistency of the view at the data warehouse in the presence of concurrent updates. Previous algorithms for incremental view maintenance either required a quiescent state at the data warehouse or required an exponential number of messages in terms of the data sources. In contrast, this algorithm does not require that the data warehouse be in a quiescent state for incorporating the new views and also the message complexity is linear in the number of data sources. The second algorithm, termed Nested SWEEP, attempts to compute a composite view change for multiple updates that occur concurrenlty while maintaining strong consistency.

UR - http://www.scopus.com/inward/record.url?scp=0031165872&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031165872&partnerID=8YFLogxK

M3 - Article

VL - 26

SP - 417

EP - 427

JO - SIGMOD Record

JF - SIGMOD Record

SN - 0163-5808

IS - 2

ER -