Filtering search: a new approach to query answering
SIAM Journal on Computing
The input/output complexity of sorting and related problems
Communications of the ACM
Efficient dynamic algorithms for some geometric intersection problems
Information Processing Letters
On two-dimensional indexability and optimal range search indexing
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Towards Optimal Indexing for Segment Databases
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
An asymptotically optimal multiversion B-tree
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic rectangular intersection with priorities
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Optimal External Memory Interval Management
SIAM Journal on Computing
Efficiently processing queries on interval-and-value tuples in relational databases
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Space-efficient dynamic orthogonal point location, segment intersection, and range reporting
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
External-memory computational geometry
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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We consider maintaining a dynamic set S of N horizontal segments in R2 such that, given a vertical ray Q in R2, the segments in S intersecting Q can be reported efficiently. In the external memory model, we give a structure that consumes O(N/B) space, answers a query in O(logB N + K/B) time (where K is the number of reported segments), and can be updated in O(logB N) amortized time per insertion and deletion. With B set to a constant, the structure also works in internal memory, consuming space O(N), answering a query in O(log N + K) time, and supporting an update in O(log N) amortized time.