{"title":"TIER: Table index evaluator and recommender — A proposed model to improve transaction performance in distributed heterogeneous database","authors":"Shefali Naik","doi":"10.1109/ICSOFTCOMP.2017.8280085","DOIUrl":null,"url":null,"abstract":"Use of appropriate indexing improves the performance of transactions in heterogeneous distributed database whereas inappropriate or no indexing deteriorates the same. Properly designed index leads to faster data access which ultimately improves the execution of transactions. Various relational database management systems and third party tools exist which provide suggestion for index management, but up to certain limits. These tools provide index suggestion with limited and simple queries. They do not analyze or suggest index for aggregate queries, sub queries and other complicated queries. The applications which access data from heterogeneous databases using such type queries need an index evaluator and recommender. To develop a good index evaluator and recommender a model is proposed in this paper on the basis of survey and literature review of existing methods. The survey has been conducted from the experienced people of IT industry to find out the feasibility of proposed model. The tool which is going to be developed from this model will be useful to improve the performance of heterogeneous distributed database transactions and will contribute in resolving index Selection Problem.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Use of appropriate indexing improves the performance of transactions in heterogeneous distributed database whereas inappropriate or no indexing deteriorates the same. Properly designed index leads to faster data access which ultimately improves the execution of transactions. Various relational database management systems and third party tools exist which provide suggestion for index management, but up to certain limits. These tools provide index suggestion with limited and simple queries. They do not analyze or suggest index for aggregate queries, sub queries and other complicated queries. The applications which access data from heterogeneous databases using such type queries need an index evaluator and recommender. To develop a good index evaluator and recommender a model is proposed in this paper on the basis of survey and literature review of existing methods. The survey has been conducted from the experienced people of IT industry to find out the feasibility of proposed model. The tool which is going to be developed from this model will be useful to improve the performance of heterogeneous distributed database transactions and will contribute in resolving index Selection Problem.