Supporting the Procedural Component of Query Languages over Time-Varying Data
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Author
Gao, Dengfeng
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As everything in the real world changes over time, the ability to model thistemporal dimension of the real world is essential to many computerapplications. Almost every database application involves the management oftemporal data. This applies not only to relational data but also to any datathat models the real world including XML data. Expressing queries ontime-varying (relational or XML) data by using standard query language (SQLor XQuery) is more difficult than writing queries on nontemporal data.In this dissertation, we present minimal valid-time extensions to XQueryand SQL/PSM, focusing on the procedural aspect of the two query languagesand efficient evaluation of sequenced queries.For XQuery, we add valid time support to it by minimally extendingthe syntax and semantics of XQuery. We adopt a stratum approach which maps a&tauXQuery query to a conventional XQuery. The first part of the dissertationfocuses on how to performthis mapping, in particular, on mapping sequenced queries, which are byfar the most challenging. The critical issue of supporting sequenced queries(in any query language) is time-slicing the input data while retaining periodtimestamping. Timestamps are distributed throughout anXML document, rather than uniformly in tuples, complicating the temporalslicing while also providing opportunities for optimization. We propose fiveoptimizations of our initial maximally-fragmented time-slicing approach:selected node slicing, copy-based per-expression slicing, in-placeper-expression slicing, and idiomatic slicing, each of which reducesthe number of constant periods over which the query is evaluated.We also extend a conventional XML query benchmark to effect a temporal XMLquery benchmark. Experiments on this benchmark show that in-place slicingis the best. We then apply the approaches used in &tauXQuery to temporal SQL/PSM.The stratum architecture and most of the time-slicing techniques work fortemporal SQL/PSM. Empirical comparison is performed by running a variety of temporalqueries.Publisher
The University of Arizona.Collections