2026-07-23T00:29:32Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:19103 2024-03-06T11:03:12Z ddc:004 open_access

Optimization of Nonsequenced Queries Using Log-Segmented Timestamps Dyreson, Curtis E. Temporal databases nonsequenced semantics query evaluation query performance In a period-timestamped, relational temporal database, each tuple is timestamped with a period. The timestamp records when the tuple is "alive" in some temporal dimension. Nonsequenced semantics is a query evaluation semantics that involves adding temporal predicates and constructors to a query. We show how to use log-segmented timestamps to improve the efficiency of temporal, nonsequenced queries evaluated using a non-temporal DBMS, i.e., a DBMS that has no special temporal indexes or query evaluation operators. A log-segmented timestamp divides the time-line into segments of known length. Any temporal period can be represented by a small number of such segments. The segments can be appended to a relation as additional columns. The advantage of log-segmented timestamps is that each segment can be indexed using standard database indexes, e.g., a B^+-tree. A query optimizer can use the indexes to generate a lower cost query evaluation plan. This paper shows how to rewrite a query to use the additional columns and evaluates the time cost benefits and space cost disadvantages. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Curtis E. Dyreson 2023 Is Part Of LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.TIME.2023.13 urn:nbn:de:0030-drops-191036 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.13 eng https://creativecommons.org/licenses/by/4.0/legalcode