Computer
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Bibliography on temporal databases
ACM SIGMOD Record
Temporal databases: theory, design, and implementation
Temporal databases: theory, design, and implementation
Fundamentals of database systems (2nd ed.)
Fundamentals of database systems (2nd ed.)
An update of the temporal database bibliography
ACM SIGMOD Record
A consensus glossary of temporal database concepts
ACM SIGMOD Record
Indexing a transaction-decision time database
SAC '96 Proceedings of the 1996 ACM symposium on Applied Computing
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Efficient Indexing Methods for Temporal Relations
IEEE Transactions on Knowledge and Data Engineering
Coalescing in Temporal Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Access Methods for Bi-Temporal Databases
Proceedings of the International Workshop on Temporal Databases: Recent Advances in Temporal Databases
Modeling Time: Adequacy of Three Distinct Time Concepts for Temporal Databases
ER '93 Proceedings of the 12th International Conference on the Entity-Relationship Approach: Entity-Relationship Approach
M-IVTT: An Index for Bitemporal Databases
DEXA '96 Proceedings of the 7th International Conference on Database and Expert Systems Applications
| Hi-index | 0.00 |
In this paper we propose an indexing structure for bitemporal databases. Such structure is based on two trees, one indexing valid time and another indexing transaction time. The trees share pointers to the actual data records, which are thus not duplicated. Bitemporal queries are processed by dividing the query in two parts, a valid time part and a transaction time part. Each tree is searched according to these partial queries, and the answer is determined by the correct composition of the partial answers. We show how simple coordination of the tree searching, along with a simple assumption on the temporal data, improves query processing performance. The proposed structure also allows querying either time dimension, separately from the other one.