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Small Materialized Aggregates: A Light Weight Index Structure for Data Warehousing |
Full Paper (PDF)
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Small Materialized Aggregates (SMAs for short) are considered a highly flexible and versatile alternative for materialized data cubes.
The basic idea is to compute many aggregate values for small to medium-sized buckets of tuples.
These aggregates are then used to speed up query processing.
We present the general idea and present an application of SMAs to the TPC-D benchmark.
We show that exploiting SMAs for TPC-D Query 1 results in a speed up of two orders of magnitude.
Then, we investigate the problem of query processing in the presence of SMAs.
Last, we briefly discuss some further tuning possibilities for SMAs.
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References, where available, link to the DBLP on the World Wide Web.
[1]Rudolf Bayer, Edward M. McCreight:
Organization and Maintenance of Large Ordered Indices.
Acta Informatica 1: 173-189(1972)[2]Surajit Chaudhuri, Umeshwar Dayal:
An Overview of Data Warehousing and OLAP Technology.
SIGMOD Record 26(1): 65-74(1997)[3]Douglas Comer:
The Ubiquitous B-Tree.
Computing Surveys 11(2): 121-137(1979)[4]Umeshwar Dayal:
Of Nests and Trees: A Unified Approach to Processing Queries That Contain Nested Subqueries, Aggregates, and Quantifiers.
VLDB 1987: 197-208[5]Prasad Deshpande, Jeffrey F. Naughton, Karthikeyan Ramasamy, Amit Shukla, Kristin Tufte, Yihong Zhao:
Cubing Algorithms, Storage Estimation, and Storage and Processing Alternatives for OLAP.
Data Engineering Bulletin 20(1): 3-11(1997)[6]Ronald Fagin, Jürg Nievergelt, Nicholas Pippenger, H. Raymond Strong:
Extendible Hashing - A Fast Access Method for Dynamic Files.
TODS 4(3): 315-344(1979)[7]Goetz Graefe:
Query Evaluation Techniques for Large Databases.
Computing Surveys 25(2): 73-170(1993)[8]Jim Gray, Adam Bosworth, Andrew Layman, Hamid Pirahesh:
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total.
ICDE 1996: 152-159[9]Antonin Guttman:
R-Trees: A Dynamic Index Structure for Spatial Searching.
SIGMOD Conference 1984: 47-57[10]Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ullman:
Implementing Data Cubes Efficiently.
SIGMOD Conf. 1996: 205-216[11]...
[12]Theodore Johnson, Dennis Shasha:
Some Approaches to Index Design for Cube Forest.
Data Engineering Bulletin 20(1): 27-35(1997)[13]Ralph Kimball:
The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses.
John Wiley 1996, ISBN 0-471-15337-0
[14]Vincent Y. Lum:
Multi-Attribute Retrieval with combined Indexes.
CACM 13(11): 660-665(1970)[15]Patrick E. O'Neil:
Model 204 Architecture and Performance.
HPTS 1987: 40-59[16]Patrick E. O'Neil, Dallan Quass:
Improved Query Performance with Variant Indexes.
SIGMOD Conference 1997: 38-49[17]Sunita Sarawagi:
Indexing OLAP Data.
Data Engineering Bulletin 20(1): 36-43(1997)[18]Amit Shukla, Prasad Deshpande, Jeffrey F. Naughton, Karthikeyan Ramasamy:
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies.
VLDB 1996: 522-531[19]...
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@inproceedings{DBLP:conf/vldb/Moerkotte98,
author = {Guido Moerkotte},
editor = {Ashish Gupta and
Oded Shmueli and
Jennifer Widom},
title = {Small Materialized Aggregates: A Light Weight Index Structure
for Data Warehousing},
booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
Large Data Bases, August 24-27, 1998, New York City, New York,
USA},
publisher = {Morgan Kaufmann},
year = {1998},
isbn = {1-55860-566-5},
pages = {476-487},
crossref = {DBLP:conf/vldb/98},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
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DBLP: Copyright ©1999 by Michael Ley (ley@uni-trier.de).
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