{"title":"An Elementary Study of Query Optimization","authors":"Ravishankar Pandey, Maneesha Kaushik","doi":"10.47904/ijskit.12.1.2022.99-102","DOIUrl":null,"url":null,"abstract":"- Now a day's, query optimization has become a popular subject for research. The most interest in this area of research arises due to the new trends within the usage of databases. Initially, databases were meant for transaction-based processing of operative information. In present times, it helps to report as well as analysis integrated and historical data. Thus, the importance of database systems is increasing day by day. This role has resulted in complications in data queries due to the increased need of accuracy in query processing. Query processing is really a process of translating a question written in an application-oriented language into low-level data manipulation operations. Query processing is related to the implementation of the query. It involves the processes of extraction of data from a knowledge warehouse. In query processing, one of the foremost critical and important steps is query optimization. Query optimization is the way to manufacture an optimal feasible and practical framework for a given query. It aims at supplying minimal reaction time and more and more throughput. A number of the techniques are statistics, histograms, sampling and parametric techniques. Any error within the result size estimates increases the number of joins. Thus, most operation of query optimizer includes transforming queries, estimating and generating plans. The present article is an effort to debate the fundamentals of query optimization. It reveals the varied studies concerned with the topic and also presents the essential techniques and significance of query optimization .","PeriodicalId":424149,"journal":{"name":"SKIT Research Journal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SKIT Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47904/ijskit.12.1.2022.99-102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
- Now a day's, query optimization has become a popular subject for research. The most interest in this area of research arises due to the new trends within the usage of databases. Initially, databases were meant for transaction-based processing of operative information. In present times, it helps to report as well as analysis integrated and historical data. Thus, the importance of database systems is increasing day by day. This role has resulted in complications in data queries due to the increased need of accuracy in query processing. Query processing is really a process of translating a question written in an application-oriented language into low-level data manipulation operations. Query processing is related to the implementation of the query. It involves the processes of extraction of data from a knowledge warehouse. In query processing, one of the foremost critical and important steps is query optimization. Query optimization is the way to manufacture an optimal feasible and practical framework for a given query. It aims at supplying minimal reaction time and more and more throughput. A number of the techniques are statistics, histograms, sampling and parametric techniques. Any error within the result size estimates increases the number of joins. Thus, most operation of query optimizer includes transforming queries, estimating and generating plans. The present article is an effort to debate the fundamentals of query optimization. It reveals the varied studies concerned with the topic and also presents the essential techniques and significance of query optimization .