SQL/SDA: a query language for supporting spatial data analysis andits Web-based implementation

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     

Spatial SQL: a query and presentation language

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     

S2CX: From relational data via SQL/XML to (Un-)Compressed XML

The gap between storing data in relational databases and transferring data in form of XML has been closed e.g. by SQL/XML queries that generate XML data out of relational data sources. However, only few relational database systems support the evaluation of SQL/XML queries. And even in those systems supporting SQL/XML, the evaluation of such queries is quite slow compared to the evaluation of SQL queries. In this paper, we present S2CX, an approach that allows to efficiently evaluate SQL/XML queries on any relational database system, no matter whether it supports SQL/XML or not. As a result to an SQL/XML query, S2CX supports different output formats ranging from plain XML to different compressed XML representations including a succinct encoding of XML data, schema-aware compressed XML to grammar compressed XML. In many cases, S2CX produces compressed XML as a result to an SQL/XML query even faster than the evaluation of SQL/XML queries into non-compressed XML as provided by Oracle 11 g and by DB2. Furthermore, our approach to query evaluation scales better, i.e., the larger the dataset, the faster is our approach compared to SQL/XML query evaluation in Oracle 11 g and in DB2.     

区间约束数据库查询语言:ISQL

区间约束数据库可以统一处理空间和非空间数据,它基于关系数据库,增加了对区间约束数据的支持。为了管理区间约束数据,在这个模型基础上,提出一个区间约束数据语言ＩＳＱＬ．ＩＳＱＬ完全保留了数据库中非空间数据的ＳＱＬ查询能力,同时集成了对空间数据的管理。     

Ultrawrap: SPARQL execution on relational data

The Semantic Web’s promise of web-wide data integration requires the inclusion of legacy relational databases,¹ i.e. the execution of SPARQL queries on RDF representation of the legacy relational data. We explore a hypothesis: existing commercial relational databases already subsume the algorithms and optimizations needed to support effective SPARQL execution on existing relationally stored data. The experiment is embodied in a system, Ultrawrap, that encodes a logical representation of the database as an RDF graph using SQL views and a simple syntactic translation of SPARQL queries to SQL queries on those views. Thus, in the course of executing a SPARQL query, the SQL optimizer uses the SQL views that represent a mapping of relational data to RDF, and optimizes its execution. In contrast, related research is predicated on incorporating optimizing transforms as part of the SPARQL to SQL translation, and/or executing some of the queries outside the underlying SQL environment.Ultrawrap is evaluated using two existing benchmark suites that derive their RDF data from relational data through a Relational Database to RDF (RDB2RDF) Direct Mapping and repeated for each of the three major relational database management systems. Empirical analysis reveals two existing relational query optimizations that, if applied to the SQL produced from a simple syntactic translations of SPARQL queries (with bound predicate arguments) to SQL, consistently yield query execution time that is comparable to that of SQL queries written directly for the relational representation of the data. The analysis further reveals the two optimizations are not uniquely required to achieve a successful wrapper system. The evidence suggests effective wrappers will be those that are designed to complement the optimizer of the target database.     

基于树状模型的复杂自然语言查询转SQL技术研究

自然语言查询转SQL(NL2SQL)是指将自然语言表达的查询文本自动转化成数据库系统可以理解并执行的结构化查询语言SQL表达式的技术.NL2SQL可以为普通用户提供数据库查询访问的自然交互界面,从而实现基于数据库的自然问答.复杂查询的NL2SQL是当前数据库学术界的研究热点,主流方法采用序列到序列(Seq2seq)的编解码方式对问题进行建模.然而,已有的工作大多基于英文场景,面向中文领域实际应用时,中文特殊的口语化表达导致复杂查询转化困难;此外,现有工作难以正确输出包含复杂计算表达式的查询子句.针对上述问题,提出一种树状模型取代序列表示,将复杂查询自顶向下分解为多叉树,树结点代表SQL的各组成元素,采用深度优先搜索来预测生成SQL语句.在Du SQL中文NL2SQL竞赛的两个官方测试集中,该方法分别取得了第1名和第2名的成绩,验证了其有效性.     

基于B/S系统的SQL注入防御技术研究

随着互联网的发展,基于Web服务器语言和后台数据库模式的网站存在安全性问题,其中SQL注入数据库是最具威胁B/S系统漏洞的攻击。该文分析了SQL注入原理及特点,研究了预防SQL注入的攻击方法,针对B/S系统的特点,提出了字段检查、注入测试、服务器加固、绑定变量和禁止字符串拼接等SQL注入的防治手段,对预防SQL注入提供了有效的方法,增加了B/S系统的安全性。     

SQL Server数据库查询优化技术应用

在结构化查询语言中,SELECT是一个关键的查询操作语句。为了设计合理高效的查询脚本,应合理使用索引、嵌套子查询、WHERE条件子句。从SQL Server数据库查询优化方法的各个方面描述该技术的应用,最后能正确评价各种方法的优点及代价,从而选出最佳方案。     

基于MapX的空间查询应用

空间查询是GIS应用系统的基本功能之一，空间查询的功能和效率是GIS应用系统的重要指标。本文讨论了利用MapX实现空间查询的方法，包括基本的图形与属性数据互查和基于空间关系的复杂查询，并给出了详细的实现方法和流程。     

Density-based spatial keyword querying

With the rocket development of the Internet, WWW(World Wide Web), mobile computing and GPS (Global Positioning System) services, location-based services like Web GIS (Geographical Information System) portals are becoming more and more popular. Spatial keyword queries over GIS spatial data receive much more attention from both academic and industry communities than ever before. In general, a spatial keyword query containing spatial location information and keywords is to locate a set of spatial objects that satisfy the location condition and keyword query semantics. Researchers have proposed many solutions to various spatial keyword queries such as top-K keyword query, reversed kNN keyword query, moving object keyword query, collective keyword query, etc. In this paper, we propose a density-based spatial keyword query which is to locate a set of spatial objects that not only satisfies the query’s textual and distance condition, but also has a high density in their area. We use the collective keyword query semantics to find in a dense area, a group of spatial objects whose keywords collectively match the query keywords. To efficiently process the density based spatial keyword query, we use an IR-tree index as the base data structure to index spatial objects and their text contents and define a cost function over the IR-tree indexing nodes to approximately compute the density information of areas. We design a heuristic algorithm that can efficiently prune the region according to both the distance and region density in processing a query over the IR-tree index. Experimental results on datasets show that our method achieves desired results with high performance.     

Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBMS. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright © 2008 John Wiley & Sons, Ltd.     

空间查询语言GSQL的研究与实现

针对关系数据库操纵语言SQL不能处理复杂的空间数据类型的问题,在SQL基本原理的基础上,结合OGIS(开放式地理信息系统)协会提出的空间数据模型,提出了空间查询语言GSQL,并设计了查询解释器,实现了对空间数据的各种空间分析运算,并能够对空间和属性数据进行联合查询。     

GIS关系数据库SQL空间扩展算子的实现

针对传统关系数据库系统不能在地理信息系统(GIS)中有效实现复杂空间数据查询的问题,提出了一种扩展SQL空间算子的实现方法。定义了空间查询子句的语法和语义,编程实现了相关空间算子的功能。来自实际GIS领域的数据实验证明了该方法的有效性。     

正则表达式在数据库查询中的应用

SQL语句在数据库查询中具有非常重要的地位,但是标准的SQL语句在复杂的数据库查询中却存在着诸多不足。而正则表达式有着强大的查询功能,通过对正则表达式特殊字符以及数据库查询语言中谓词的分析,提出了将正则表达式运用于数据库查询当中的新查询方法,并对该方法在实际查询应用当中会遇到的几个普遍问题进行了探讨。从而证明该方法不仅可以降低查询语句的复杂程度而且还能简化对出错语句的修改工作。     

Semantics preserving SPARQL-to-SQL translation

Most existing RDF stores, which serve as metadata repositories on the Semantic Web, use an RDBMS as a backend to manage RDF data. This motivates us to study the problem of translating SPARQL queries into equivalent SQL queries, which further can be optimized and evaluated by the relational query engine and their results can be returned as SPARQL query solutions. The main contributions of our research are: (i) We formalize a relational algebra based semantics of SPARQL, which bridges the gap between SPARQL and SQL query languages, and prove that our semantics is equivalent to the mapping-based semantics of SPARQL; (ii) Based on this semantics, we propose the first provably semantics preserving SPARQL-to-SQL translation for SPARQL triple patterns, basic graph patterns, optional graph patterns, alternative graph patterns, and value constraints; (iii) Our translation algorithm is generic and can be directly applied to existing RDBMS-based RDF stores; and (iv) We outline a number of simplifications for the SPARQL-to-SQL translation to generate simpler and more efficient SQL queries and extend our defined semantics and translation to support the bag semantics of a SPARQL query solution. The experimental study showed that our proposed generic translation can serve as a good alternative to existing schema dependent translations in terms of efficient query evaluation and/or ensured query result correctness.     

Logical errors in database SQL retrieval queries

SQL is often used to express questions imposed by users. It is well known that this process is not error-free in that it may result in syntactically or semantically incorrect SQL queries. This article is meant to probe deeper into SQL queries that are incorrect, due to delusion errors. A classification of natural language questions will be introduced. The purpose of this classification is two-fold. Firstly, it gives insight into possible errors and enables us to distinguish between types of errors. Secondly, it is a means of determining the influence of measures (for instance, SQL training) that can be taken to reduce the number of aforementioned errors. For discussion, several of these measures will be presented and related to the classification.Abbreviations RA Relational algebra - SQL structured query language     

Extending a Natural Language Interface with Geospatial Queries

In this installation of architectural perspectives, we describe an extension of a menu-based natural language interface (MBNLI) to support geospatial queries. Our extension makes it easier for application analysts and even inexperienced users to phrase complex queries without knowing the relational database query language SQL, database schemas (table structures), spatial operators, or spatial indexes.     

Conversational querying

The traditional interaction mechanism with a database system is through the use of a query language, the most widely used one being SQL. However, when one is facing a situation where he or she has to make a minor modification to a previously issued SQL query, either the whole query has to be written from scratch, or one has to invoke an editor to edit the query. This, however, is not the way we converse with each other as humans. During the course of a conversation, the preceding interaction is used as a context within which many incomplete and/or incremental phrases are uniquely and unambiguously interpreted, sparing the need to repeat the same things again and again. In this paper, we present an effective mechanism that allows a user to interact with a database system in a way similar to the way humans converse. More specifically, incomplete SQL queries are accepted as input which are then matched to identified parts of previously issued queries. Disambiguation is achieved by using various types of semantic information. The overall method works independently of the domain under which it is used (i.e., independently of the database schema). Several algorithms that are variations of the same basic mechanism are proposed. They are mutually compared with respect to efficiency and accuracy through a limited set of experiments on human subjects. The results have been encouraging, especially when semantic knowledge from the schema is exploited, laying a potential foundation for conversational querying in databases.     

基于网络的选修课选课系统的设计与实现

基于网络选修课选课系统是基于Web技术,采用B／S结构,在Internet／Intrnet环境下使用的教学辅助系统;在系统中,使用ASP脚本语言和SQL Server2000数据库实现了选课的主体部分（B／S结构）;使用Delphi5．0编程语言和SQL Server2000数据库编写了选课系统辅助部分（C／S结构）,方便了教务处的教学管理,提高了工作效率。     

基于Ontology的数据库自然语言查询接口的研究

提出了一种基于Ontology的关系数据库自然语言查询接口的系统模型及设计框架.采用WordNet作为基本数据库并在WordNet之上定义领域词库,可以提高语法分析的识别率;同时利用Ontlogly知识表达能力存储关系数据库概念模型,并对概论模型的内容进行扩充;另外对Ontology和WordNet的同义词集进行关联,可以提高语义的识别率.用户的输入查询语句通过语法分析、语义分析生成中间表达式语言DRS,然后通过模板技术转换成SQL,通过DBMS执行SQL并返回结果.实验证明,这种方案不但实用可行,而且通过逐步完善Ontology知识库的定义,可以大大提高查询的命中率;另外通过WordNet和Ontology定义领域词库和领域知识,提高了系统的可移植性.最后,所提供的方法可以很容易地移植到其他领域.