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This paper studies the generic location-aware rank query (GLRQ) over a set of location-aware objects. A GLRQ is composed of a spatial location, a set of keywords, a query predicate, and a ranking function formulated on location, text and other attributes. The result consists of $k$ objects satisfying the predicate ranked according to the ranking function. An example is a query searching for the restaurants that 1) are nearby, 2) offer “American” food, and 3) have high ratings (rating $>$ 4.0). Such queries can not be processed efficiently using existing techniques. In this work, we propose a novel framework called LINQ for efficient processing of GLRQs. To handle the predicate and the attribute-based scoring, we devise a new index structure called synopses tree , which contains the synopses of different subsets of the dataset. The synopses tree enables pruning of search space according to the satisfiability of the predicate. To process the query constraints over the location and keywords, the framework integrates the synopses tree with the spatio-textual index such as IR-tree. The framework therefore is capable of processing the GLRQs efficiently and holistically. We conduct extensive experiments to demonstrate that our solution provides excellent query performance.

We propose a logical framework to analyze complex predicates (those involving a subquery) in SQL. We propose a new operator in the relational algebra for handling such predicates, and study its properties and how it combines with traditional relational operator. We focus on predicates of the form att θ MOD S, where att is an attribute, θ a comparison operator, MOD is one of SOME or ALL, and S is a (correlated or non-correlated) subquery. We provide a formal characterization of these predicate, as well as an implementation and optimization strategies for it. We show that our approach is extendible, so we can support the expression and optimization of other, similar predicates. Finally, we describe experimental evidence that the proposed approach is more efficient than the traditional approach across a variety of conditions.

An important trend of current GIS development is to provide easy and effective access to spatial analysis functionalities for supporting decision making based on geo-referenced data. Within the framework of the ongoing SQL standards for spatial extensions, a spatial query language, called SQV/SDA, has been designed to meet such a requirement. Since the language needs to incorporate the important derivation functions (e.g., map-overlay and feature-fusion) as well as the spatial relationship and metric functions, the functionality of the FROM clause in SQL is developed in addition to the SELECT and WHERE clauses. By restructuring the FROM clause via a subquery, SQL/SDA is well-adapted to the general spatial analysis procedures using current GIS packages. Such an extended SQL, therefore, stretches the capabilities of previous ones. The implementation of SQL/SDA on the Internet adopts a hybrid model, which takes advantage of the Web GIS design methods in both the client side and server side. The client side of SQL/SDA, programmed in the Java language, provides a query interface by introducing visual constructs such as icons, listboxes, and comboboxes to assist in the composition of queries, thereby enhancing the usability of the language. The server side of SQL/SDA, which is composed of a query processor and Spatial Database Engine (SDE), carries out query processing on spatial databases after receiving user requests.

Statistics play a key role in influencing the quality of plans chosen by a database query optimizer. In this paper, we identify the statistics that are essential for an optimizer. We introduce novel techniques that help significantly reduce the set of statistics that need to be created without sacrificing the quality of query plans generated. We discuss how these techniques can be leveraged to automate statistics management in databases. We have implemented and experimentally evaluated our approach on Microsoft SQL Server 7.0.

Recently, attention has been focused on spatial databases, which combine conventional and spatially related data, such as geographic information systems, CAD/CAM, or VLSI. A language has been developed to query such spatial databases. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. The spatial query language has been designed as a minimal extension to the interrogative part of SQL and distinguishes from previously designed SQL extensions by: the preservation of SQL concepts; the high-level treatment of spatial objects; and the incorporation of spatial operations and relationships. It consists of two components, a query language to describe what information to retrieve and a presentation language to specify how to display query results. Users can ask standard SQL queries to retrieve nonspatial data based on nonspatial constraints, use Spatial SQL commands to inquire about situations involving spatial data, and give instructions in the Graphical Presentation Language, GPL to manipulate or examine the graphical presentation. >