American-Eurasian Journal of Scientific Research 11 (2): 72-78, 2016 ISSN 1818-6785 © IDOSI Publications, 2016 DOI: 10.5829/idosi.aejsr.2016.11.2.22729 Corresponding Author: Tejy Johnson, Department of Computer Science, Ethiraj College for Women, Egmore, Chennai-8, India. 72 Multi Level Relational Mapping Algorithm Based Dependency Rule Generation for Query Optimization Tejy Johnson and S.K. Srivatsa 1 2 Department of Computer Applications, 1 Dr.MGR Educational Research and Institute University, Maduravoyal, Chennai-95 Department of CSC, Prathyusha Institute of Technology and Management (PITAM), 2 TIRUVALLUR – 602025, Chennai-602 025, India Abstract: The problem of query optimization has been approached in several methods but suffers with the problem of accuracy. To overcome this issue and to improve the performance of our previous solution, we propose a multi level relational mapping algorithm in this paper. The method first identifies the relational objects and generates relational maps. From the relational maps the method identifies the objects and entity of query. Based on the above the method generates different rules to perform the query and computes the dependency measure for each part of the query. The use of relational map helps to identify the query dependency according to the object and to compute the dependency measure for each of the rule being produced. Finally a subset of dependency rule is produced as a result and the method improve the performance of rule generation and improves the performance of query optimization by scheduling the execution of query parts efficiently. Key words: Relational Database Query Optimization Dependency Rules Relational Mapping INTRODUCTION data tables where the result of any part of the query can The modern data base maintains various schema and to execute the query part, some of the other part of the each has various relations. The information about any query has to be completed or if two different part of the product has no limit in size and can be presented in a query access the same relational data table then one has relational manner. For example, the information about a to be wait till the other part of the query has to be single human can be split into number of categories like finished. This introduces dependency in executing the personal, official, financial and so on. The personal query. Also, the input query can be split into number of information is about the personal detail about the person small query parts and the query optimization is performed which has name, parent name, age and sex and so on. according to the sequence of query execution. By Further the personal information can be split into the executing the query parts in different sequence the time address and personal information. The address itself can complexity will vary and to execute the query in more be stored in a relational data base and can be stored as a efficient manner the time complexity has to be minimized. new entity. Similarly the information about any object can In general the query optimization is performed by be presented and stored in number of data tables where splitting the query into number of small query parts and there is relation between the entities present in different execute them in different order in such a way to reduce the tables of any data base. Such relational entities stored in time complexity. However the query parts has different any data base can be named as relational data base. dependency between them and the earlier methods does The relational database helps organizing the data not handles this issue to reduce the time complexity and tuples in more efficient manner where the retrieval also to improve the performance of query optimization. By could be performed in more strategic manner. The query identifying the query parts and their dependency between produced by any user may access number of relational them, we can g enerate the dependency rules from which become an input to the other part of the query. So in order