By Jennifer Widom
Active database platforms increase conventional database performance with strong rule-processing features, offering a uniform and effective mechanism for lots of database process purposes. between those purposes are integrity constraints, perspectives, authorization, facts amassing, tracking and alerting, knowledge-based structures, professional structures, and workflow administration. this crucial assortment makes a speciality of the main famous learn initiatives in energetic database structures. The venture leaders for every prototype procedure supply distinct discussions in their initiatives and the relevance in their effects to the way forward for energetic database platforms. * A extensive evaluation of present energetic database structures and the way they are often prolonged and more suitable * A finished advent to the middle themes of the sphere, together with its motivation and background * assurance of lively database (trigger) features in advertisement items * dialogue of coming near near criteria
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Extra info for Active Database Systems: Triggers and Rules for Advanced Database Processing
Rules in RIF-PRD support actions as consequent in the (production) rules. , additions, removals, or replacements) of frames, executions of externally defined actions, or sequences of these actions, including the declaration of local variables and a mechanism to bind a local variable with a frame slot value or a new frame object. 9 Related Work 31 A typical scenario for the use of RIF with RDF/OWL is the exchange of rules that use RDF data and/or RDFS or OWL ontologies. An interchange partner A uses a rule language that is RDF/OWL-aware; that is, the input data of the rules are RDF data, an RDFS or OWL ontology defines the semantics of objects used in the rules, or the rules extend RDF(S)/OWL inference.
For range queries, the first value is searched with key equal to or larger than a and equal to or smaller than b, and afterward, all succeeding values are returned with keys smaller than b. 5 Inserting Indices do not contain only static data. Instead, data are often updated, that is, new data are inserted and old data deleted, to reflect changes in the real world like a new employee. When inserting a new key-value pair into the B+-tree, the insertion 3 External Sorting and B+-Trees 42 position in a leaf is first searched for using a search algorithm similar to the one for searching the value of a key.
The first approach is a variant of the external merge sort approach. The variant generates longer initial runs (and thus less number of runs) than external merge sort using main-memory sort algorithms, and thus the succeeding merge phase can be processed faster. Since the generation of the initial runs has a similar performance, our approach is faster than external merge sort using main-memory sort algorithms. In comparison to the approach of replacement selection, our approach generates slightly smaller initial runs, and thus the merging phase is slightly slower.