Abstract:
In a transaction-time temporal object database management system (TODBMS), updating an object creates a new version of the object, but the old version is still accessible. A TODBMS will store large amounts of data, and in order to provide the necessary computing power and data bandwidth, a parallel system based on a shared-nothing architecture is necessary. In order to benefit from a parallel architecture, a suitable declustering of the objects over the nodes in the system is important. In this paper, we study three low-cost declustering algorithms: 1) declustering based on the hash value of the OID of the objects, 2) range partitioning, based on the timestamp of the objects, and 3) a new hybrid algorithm, where current object versions are declustered according to the hash value of the OID, and the historical versions are range partitioned based on timestamp. In contrast to many similar studies, we study the performance with a workload including both read and update operations. We show that strategy 1 and 3 are the most scalable strategies, and that the new hybrid declustering strategy is especially suitable for low update rates, for example in geographical information systems and decision support systems with support for temporal data. However, in general declustering based on the hash value of the OID of the objects has the most stable and predictable performance. Key words: object database systems, temporal database systems, parallel database systems, declustering 1
Citations
|
172
|
The Gamma database machine project
– DeWitt, Ghandeharizadeh, et al.
- 1990
|
|
85
|
Representing and querying changes in semistructured data
– Chawathe, Abiteboul, et al.
- 1998
|
|
76
|
On the performance of object clustering techniques
– Tsangaris, Naughton
- 1992
|
|
75
|
An Evaluation of Non-Equijoin Algorithms
– DeWitt, Naughton, et al.
- 1991
|
|
54
|
Change-Centric Management of Versions in an XML Warehouse
– Marian, Abiteboul, et al.
- 2001
|
|
43
|
Hybrid-Range Partitioning Strategy: A New Declustering Strategy for Multiprocessor Database Machines
– Ghandeharizadeh, DeWitt
- 1990
|
|
33
|
Temporal Database System Implementations
– Böhlen
- 1995
|
|
27
|
Temporal Query Processing and Optimization in Multiprocessor Database Machines
– Leung, Muntz
- 1992
|
|
24
|
Temporal database bibliography update
– Wu, Jajodia, et al.
- 1998
|
|
20
|
Development and performance analysis of a temporal persistent object store POST/C
– Suzuki, Kitagawa
- 1996
|
|
16
|
A Generalisation Approach to Temporal Data Models and their Implementations
– Steiner
- 1998
|
|
15
|
Managing historical semistructured data
– Chawathe, Abiteboul, et al.
- 1999
|
|
14
|
Algorithms for temporal query operators in XML databases
– Nørv˚ag
- 2002
|
|
11
|
A temporal object-oriented model for digital libraries of documents. Concurrency and Computation: Practice and Experience
– Aramburu-Cabo, Llavori
|
|
11
|
Implementation and Evaluation of Parallel Query Processing Algorithms and Data Partitioning Heuristics
– Chen, Su
- 1996
|
|
9
|
The Vagabond temporal OID index: An index structure for OID indexing in temporal object database systems
– Nørv˚ag
- 2000
|
|
7
|
Vagabond: The Design and Analysis of a Temporal Object Database Management System
– Nørv˚ag
- 2000
|
|
6
|
Scalable, parallel, scientific databases
– Pfaltz, Haddleton, et al.
- 1998
|
|
5
|
Object placement in parallel object-oriented database systems
– Ghandeharizadeh, Wilhite, et al.
- 1994
|
|
5
|
Declustering techniques for parallelizing temporal access structures
– Kouramajian, Elmasri, et al.
- 1994
|
|
3
|
LoT: Dynamic declustering of TSB-tree nodes for parallel access to temporal data
– Muth, Kraiß, et al.
- 1996
|
|
2
|
Parallel query processing strategies for object-oriented temporal databases
– Hyun, Su
- 1996
|
