SQL Knowledge

1998

The ever popular Structured Query Language (SQL) has continued to be the standard language to access relational databases for almost two decades. As SQL is widely used by all major relational database management systems (RDBMS), there is an ongoing effort to standardize syntax and semantics in the SQL (ISO/IEC) standards SQL-92 and SQL3. The first part of this presentation will present and discuss current language support concepts and features in the ANSI SQL standards including character sets and encodings in SQL data types, identifiers and literals, translations, collations, conversions, string functions, error handling and messaging, and call-level interfaces. It will be shown that those features, as specified in the standards, are still not mature and need to be refined before being used by actual implementations. The second part of the presentation proposes changes and additions to make language support features in the SQL standards workable. Topics covered will include a discu...

2011

Non-English-speaking users, such as Arabic speakers, are not always able to express terminology in their native languages, especially in scientific domains. Such difficulty forces many Arabic authors and scholars to use English terms in order to explain precise concepts, resulting in mixed/multilingual queries with both English and Arabic terms. Current CLIR techniques are optimized for monolingual queries, even if they are translated, but neither mixed-language queries nor searches for mixed-language documents have yet been adequately studied. This paper attempts to address the problem of multilingual querying in CLIR. It shows experimentally that current search engines and IR systems are not language-aware and are not adequate for multilingual querying. The paper then presents the main ingredients that every language-aware solution should take care of.

22nd International Conference on Data Engineering (ICDE'06), 2006

To effectively support today's global economy, database systems need to manage data in multiple languages simultaneously. While current database systems do support the storage and management of multilingual data, they are not capable of querying across different natural languages. To address this lacuna, we have recently proposed two cross-lingual functionalities, LexEQUAL[13] and SemEQUAL[14], for matching multilingual names and concepts, respectively. In this paper, we investigate the native implementation of these multilingual functionalities as first-class operators on relational engines. Specifically, we propose a new multilingual storage datatype, and an associated algebra of the multilingual operators on this datatype. These components have been successfully implemented in the Post-greSQL database system, including integration of the algebra with the query optimizer and inclusion of a metric index in the access layer. Our experiments demonstrate that the performance of the native implementation is up to two orders-of-magnitude faster than the corresponding outsidethe-server implementation. Further, these multilingual additions do not adversely impact the existing functionality and performance. To the best of our knowledge, our prototype represents the first practical implementation of a crosslingual database query engine.

Advances in Science, Technology and Engineering Systems Journal

English remains the language of choice for database courses and widely used for instruction in nearly all South African universities, and also in many other countries. Novice programmers of native origins are mostly taught Structured Query Language (SQL) through English as the medium of instruction. Consequently, this creates a myriad of problems in understanding the syntax of SQL as most native learners are not too proficient in English. This could affect a learner's ability in comprehending SQL syntaxes. To resolve this problem, this work proposes a tool called local language narrations to SQL (Local-Nar-SQL) that uses a type of Finite Machine, such as a Jumping Finite Automaton to translate local language narratives into SQL queries. Further, the generated query extracts information from a sample database and presents an output to the learner. This paper is an extension of work originally presented in a previous study in this field. A survey involving 145 participants concluded that the majority found Local-Nar-SQL to be helpful in understanding SQL queries from local languages. If the proposed tool is used as a learning aid, native learners will find it easier to work with SQL, which will eliminate many of the barriers faced with English proficiencies in programming pedagogies.

Global E-Commerce and E-Governance programs have brought into sharp focus for the need of database systems to store and manipulate data efficiently in a suite of multiple languages. While existing database systems provide some means of storing and querying multilingual data, they suffer from redundancy proportional to the number of language support. In this paper, we propose a system for multilingual data management in distributed environment that stores data in information theoretic way in encoded form with minimum redundancy. Query operation can be performed from the encoded data only and the result is obtained by decompressing it using the corresponding language dictionaries for text data or without dictionary for other data. The system has been evaluated by both syntactic data and real data obtained from a real life schema. We have compared the performance of our system with existing systems. Our system outperformed the existing systems in terms of both space and time.

Proceedings of the 2010 international conference on Management of data - SIGMOD '10, 2010

In this paper we describe a demo concerning the management of uncertain schemata. Many works have studied the problem of representing uncertainty on attribute values or tuples, like the fact that a value is 10 with probability .3 or 20 with probability .7, leading to the implementation of probabilistic database management systems. In our demo we deal with the representation of uncertainty about the meta-data, i.e., about the meaning of these values. Using our system it is possible to create alternative probabilistic schemata on a database, execute queries over uncertain schemata and verify how this additional information is stored in an underlying relational database and how queries are executed.

Journal of Systems and Software, 2006

We investigate classes of SQL queries which are syn- tactically correct, but certainly not intended, no mat- ter for which task the query was written. For instance, queries that are contradictory, i.e. always return the empty set, are obviously not intended. However, current database management systems execute such queries without any warning. In this paper, we give an exten- sive

2009

It is a long term desire of the computer users to minimize the communication gap between the computer and a human. Natural Language Interfaces to Databases (NLIDBs) is one of the mechanisms to pull off this goal. In NLIDBs the question is asked in simple daily life human language and the answer is given in the same language. This research paper is about NLIDBs for Urdu language. An algorithm is developed that efficiently maps a natural language query, entered in Urdu, to an SQL (Structured Query Language) statement. The algorithm has been implemented in Visual C#.NET and tested on a database containing Student Information System and Employee Information System. The program correctly maps 85% natural language queries.

2001

Most approaches to cross language information retrieval assume that resources providing a direct translation between the query and document languages exist. This paper presents research examining the situation where such an assumption is false. Here, an intermediate (or pivot) language provides a means of transitive translation of the query language to that of the document via the pivot, at the cost, however, of introducing much error. The paper reports the novel approach of translating in parallel across multiple intermediate languages and fusing the results. Such a technique removes the error, raising the effectiveness of the tested retrieval system, up to and possibly above the level expected, had a direct translation route existed. Across a number of retrieval situations and combinations of languages, the approach proves to be highly effective.

Developed in the information Tec., data management and multi-database, cloud computing that introduce problem in data integration. The one of data integration problem in database is heterogeneous database query. In the end how can join and representation data from multi-database although the differences in DBMS, Data Structure, and data type. In this research built set of algorithm to retrieval and integration data from databases such as (Oracle, SQL Server) by create virtual tables and join its to solution the heterogeneous in DBMS, Data Structure, and data type problem. system create new scheme for the tables (columns use in query) without all columns in database, after apply condition (on each table's database). This system rather than design a new database with new structure and new virtual programming for coordinated to solve integration data. the system can use also to re-fragmentation tables and rearrangement fields in tables.