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The Physical data layer and Presentation layer or Web interface codes are all written in PL/SQL server pages and java scripts to generate dynamic queries and present them to the front end dynamically generated HTML pages.
In many Web systems, however, untrusted users are allowed to run dynamic queries.
It implements and extends Dynamic Queries (Ahlberg et al. 1992) and Visual Information Seeking principles (Ahlberg and Shneiderman 1994).
MongoDB is good for the dynamic queries, which the other document-oriented databases lack, such as CouchDB or Couchbase [95].
We also build upon two novel interface metaphors originally developed for navigating databases: the Guides metaphor and Dynamic Queries.
Systems such as dynamic queries use a collection of independent filters to interactively query by restricting attribute values.
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To illustrate the last point, take for example how Borealis handles dynamic query modification.
By employing dynamic query filters, visualizations can be narrowed down to specific ranges and regions.
We have constructed a tool, Quiver, which constructs Dynamic Query interfaces on-the-fly as the result of queries to knowledge models stored on the Alice server.
In particular, we present a P2P search algorithm, named DQ-DHT (Dynamic Querying over a Distributed Hash Table), to perform DQ-like searches over DHT-based overlays.
Web users are usually very reactive to worldwide events which cause highly dynamic query traffic patterns leading to load imbalance across peers.
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