Datacube queries compute aggregates over database relations at a variety of granularities, and they constitute an important class of decision support queries. In this thesis we study problems pertaining to the computation of datacubes and frameworks for querying them. Often one wants only datacube output tuples whose aggregate value satises a certain condition, such as exceeding a given threshold. For example, one might ask for all combinations of model, color, and year of cars (including the special value \ALL " for each of the dimensions) for which the total sales exceeded a given amount of money. Computing a selection over a datacube can naively be done by computing the entire datacube and checking if the selection condition holds for each tuple in the result. However, it is often the case that selections are relatively restrictive, meaning that a lot of work computing datacube tuples is \wasted " since those tuples don't satisfy the selection condition.
|
1643
|
Fast algorithms for mining association rules
– Agrawal, Srikant
- 1994
|
|
527
|
Query Evaluation Techniques for Large Databases
– Graefe
- 1993
|
|
211
|
Exploratory mining and pruning optimization of constrained association rules
– Ng, Lakshmanan, et al.
- 1998
|
|
188
|
On the Computation of Multidimensional Aggregates
– Agrawal, Agrawal, et al.
- 1996
|
|
149
|
An Array-Based Algorithm for Simultaneous Multidimensional Aggregates
– Zhao, DeshPande, et al.
- 1997
|
|
140
|
Index selection for olap
– Gupta, Harinarayan, et al.
- 1997
|
|
131
|
Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets
– Vitter, Wang
- 1999
|
|
128
|
Predicate migration: Optimizing queries with expensive predicates
– Hellerstein, Stonebraker
- 1993
|
|
101
|
Various Optimizers for Single-Stage Production
– Smith
- 1956
|
|
100
|
Bottom-up computation of sparse and iceberg cubes
– Beyer, Ramakrishnan
- 1999
|
|
86
|
Fast Computation of Sparse Datacubes
– Ross, Srivastava
- 1996
|
|
71
|
On computing the data cube
– Sarawagi, Agrawal, et al.
- 1996
|
|
67
|
Optimization of constrained frequent set queries: 2-var constraints
– Lakshmanan, Ng, et al.
- 1998
|
|
64
|
Ramaswamy: “Storage Estimation for Multidimensional Aggregates
– Shukla, Deshpande, et al.
- 1996
|
|
58
|
Caching multidimensional queries using chunks
– Deshpande, Ramasamy, et al.
- 1998
|
|
58
|
Discovery-driven exploration of OLAP data cubes
– Sarawagi, Agrawal, et al.
- 1998
|
|
57
|
An overview of query optimization in relational systems
– CHAUDHURI
- 1998
|
|
56
|
Monotonic aggregation in deductive databases
– Ross, Sagiv
- 1992
|
|
55
|
Selection of Views to Materialize Under a Maintenance Cost Constraint
– Gupta, Mumick
|
|
49
|
Range queries in OLAP data cubes
– Ho, Agrawal, et al.
- 1997
|
|
47
|
Materialized View Selection for Multidimensional Datasets
– Shukla, Deshpande, et al.
- 1998
|
|
46
|
DynaMat: A Dynamic View Management System for Data Warehouses
– Kotidis, Roussopoulos
- 1999
|
|
41
|
Foundations of aggregation constraints
– Ross, Srivastava, et al.
- 1994
|
|
39
|
Query optimization by predicate move-around
– Levy, Mumick, et al.
- 1994
|
|
34
|
Optimizing disjunctive queries with expensive predicates
– Kemper, Moerkotte, et al.
- 1994
|
|
32
|
An Alternative Storage Organization for ROLAP Aggregation Views Based on Cubtrees
– Kotidis, Roussopoulos
- 1998
|
|
31
|
Datacube : A Relational Aggregation Operator Generalizing Group-by, Cross-Tab, and Sub-Totals
– Gray, Bosworth, et al.
- 1996
|
|
28
|
Implementing data cubes eciently
– Harinarayan, Rajaraman, et al.
- 1996
|
|
27
|
Hierarchical Cubes for Range-Sum Queries
– Chan, Ioannidis
- 1999
|
|
27
|
Edited synoptic cloud reports fromships and land stations over the globe
– Hahn, Warren, et al.
- 1996
|
|
23
|
High performance multidimensional analysis of large datasets
– Goil, Choudhary
- 1998
|
|
20
|
Reasoning with Aggregation Constraints
– Levy, Mumick
- 1996
|
|
19
|
Some approaches to index design for cube forests
– Johnson, Shasha
- 1997
|
|
10
|
Aggregate aware caching for multi-dimensional queries
– Deshpande, Naughton
- 2000
|
|
8
|
Dynamic assembly of views in data cubes
– Smith, Li, et al.
- 1998
|
|
6
|
Optimizing selections over data cubes
– Ross, Zaman
- 1998
|
|
6
|
Materialized view selection for multi-cube data models
– Shukla, Deshpande, et al.
- 2000
|
|
5
|
Relative Pre Sums: An Ecient Approach for Querying Dynamic OLAP Data Cubes
– Gener, Agrawal, et al.
- 1999
|
|
4
|
Explaining dierences in multidimensional aggregates
– Sarawagi
- 1999
|
|
3
|
Fast computation of sparse datacubes. Full Version
– Ross, Srivastava
- 1998
|
|
3
|
Optimizing selections over datacubes
– Ross, Zaman
- 2000
|
|
3
|
Serving datacube tuples from main memory
– Ross, Zaman
- 2000
|
|
2
|
Optimization of queries with user-de predicates
– Chaudhuri, Shim
- 1996
|
|
2
|
Fast approxiamte answers to aggregate queries on a data cube
– Poosala, Ganti
- 1999
|
|
2
|
Partial-match retrieval using hashing and descriptors
– Ramamohanrao, Lloyd, et al.
- 1983
|
|
1
|
Optimal partial-match retrieval where are independently speci ACM Transactions on Database Systems
– Aho, Ullman
- 1979
|
|
1
|
Selection of views to materialize under a maintenance cost constraint
– Dehne, Hambrusch, et al.
- 2001
|
|
1
|
hashing: a new tool for and table addressing
– Linear
- 1980
|
|
1
|
materialized aggregates: A light weight index structure for data warehousing
– Small
- 1998
|
|
