Maintenance of Data Cubes and Summary Tables in a Warehouse.
Inderpal Singh Mumick, Dallan Quass, Barinderpal Singh Mumick:
Maintenance of Data Cubes and Summary Tables in a Warehouse.
SIGMOD Conference 1997: 100-111@inproceedings{DBLP:conf/sigmod/MumickQM97,
author = {Inderpal Singh Mumick and
Dallan Quass and
Barinderpal Singh Mumick},
editor = {Joan Peckham},
title = {Maintenance of Data Cubes and Summary Tables in a Warehouse},
booktitle = {SIGMOD 1997, Proceedings ACM SIGMOD International Conference
on Management of Data, May 13-15, 1997, Tucson, Arizona, USA},
publisher = {ACM Press},
year = {1997},
pages = {100-111},
ee = {http://doi.acm.org/10.1145/253260.253277, db/conf/sigmod/MumickQM97.html},
crossref = {DBLP:conf/sigmod/97},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
Data warehouses contain large amounts of information, often
collected from a variety of independent sources. Decision-support
functions in a warehouse, such as on-line analytical
processing (OLAP), involve hundreds of complex aggregate
queries over large volumes of data. It is not feasible to
compute these queries by scanning the data sets each time.
Warehouse applications therefore build a large number of
summary tables, or materialized aggregate views, to help
them increase the system performance.
As changes, most notably new transactional data, are
collected at the data sources, all summary tables at the
warehouse that depend upon this data need to be updated.
Usually, source changes are loaded into the warehouse at
regular intervals, usually once a day, in a batch window,
and the warehouse is made unavailable for querying while it
is updated. Since the number of summary tables that need
to be maintained is often large, a critical issue for data warehousing
is how to maintain the summary tables efficiently.
In this paper we propose a method of maintaining aggregate
views (the summary-delta table method), and use it
to solve two problems in maintaining summary tables in a
warehouse: (1) how to efficiently maintain a summary table
while minimizing the batch window needed for maintenance,
and (2) how to maintain a large set of summary tables defined
over the same base tables.
While several papers have addressed the issues relating
to choosing and materializing a set of summary tables, this
is the first paper to address maintaining summary tables efficiently.
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Joan Peckham (Ed.):
SIGMOD 1997, Proceedings ACM SIGMOD International Conference on Management of Data, May 13-15, 1997, Tucson, Arizona, USA.
ACM Press 1997
,
SIGMOD Record 26(2),
June 1997
Contents
[Index Terms]
[Full Text in PDF Format, 1542 KB]
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Referenced by
- Themistoklis Palpanas:
Knowledge Discovery in Data Warehouses.
SIGMOD Record 29(3): 88-100(2000)
- Markos Zaharioudakis, Roberta Cochrane, George Lapis, Hamid Pirahesh, Monica Urata:
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SIGMOD Conference 2000: 105-116
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How To Roll a Join: Asynchronous Incremental View Maintenance.
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- Wolfgang Lehner, Richard Sidle, Hamid Pirahesh, Roberta Cochrane:
Maintenance of Automatic Summary Tables.
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- Stéphane Grumbach, Leonardo Tininini:
On the Content of Materialized Aggregate Views.
PODS 2000: 47-57
- Torben Bach Pedersen, Christian S. Jensen, Curtis E. Dyreson:
Extending Practical Pre-Aggregation in On-Line Analytical Processing.
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Hierarchical Prefix Cubes for Range-Sum Queries.
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- Himanshu Gupta, Inderpal Singh Mumick:
Selection of Views to Materialize Under a Maintenance Cost Constraint.
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- Dominique Laurent, Jens Lechtenbörger, Nicolas Spyratos, Gottfried Vossen:
Complements for Data Warehouses.
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- Carlos A. Hurtado, Alberto O. Mendelzon, Alejandro A. Vaisman:
Maintaining Data Cubes under Dimension Updates.
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- Martin Ester, Hans-Peter Kriegel, Jörg Sander, Michael Wimmer, Xiaowei Xu:
Incremental Clustering for Mining in a Data Warehousing Environment.
VLDB 1998: 323-333
- Randall G. Bello, Karl Dias, Alan Downing, James J. Feenan Jr., James L. Finnerty, William D. Norcott, Harry Sun, Andrew Witkowski, Mohamed Ziauddin:
Materialized Views in Oracle.
VLDB 1998: 659-664
- Yannis Kotidis, Nick Roussopoulos:
An Alternative Storage Organization for ROLAP Aggregate Views Based on Cubetrees.
SIGMOD Conference 1998: 249-258
- Dimitra Vista:
Integration of Incremental View Maintenance into Query Optimizers.
EDBT 1998: 374-388
- Shin-Chung Shao:
Multivariate and Multidimensional OLAP.
EDBT 1998: 120-134
- Martin Ester, Rüdiger Wittmann:
Incremental Generalization for Mining in a Data Warehousing Environment.
EDBT 1998: 135-149
- Michael O. Akinde, Ole Guttorm Jensen, Michael H. Böhlen:
Minimizing Detail Data in Data Warehouses.
EDBT 1998: 293-307
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