Title: An Elementary Study of Query Optimization


Authors:

Ravish Pandey

ravish.pandey@skit.ac.in
Department of Management Studies, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, India,

Maneesha Kaushik

maneesha.kaushik@skit.ac.in
Department of Management Studies, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, India

Pages: 99-102

DOI:

Abstract:

Now a day's, query optimization has become a popular subject for research. The most interest during 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 during an application-oriented language into low-level data manipulation operations. Query processing is related to the implementation of query. It involves the processes of extraction of data from a knowledge warehouse. In query processing, one among the foremost critical and important step is query optimization. Query optimization is the way to manufacture an optimal feasible and practical framework for a given query.It aims at suppling minimalreaction time and more and more throughput. Query optimization plays an important role in tuning overall performance of the database systems. Query optimizer includeselements of database system. Its motive is to convert the user given query in written form during a non-procedural languageinto an efficient query analysis plan which is implemented against the database. Thus, the performance of a question is critically dependent upon the power of the query optimizer in selecting the foremost efficient access plan. The choice of efficient access plan is completed supported the estimated cost of competing access plans. These costs are successively supported the estimates of intermediate result size. Several techniques are found in the literature to know about query result size. A number of the techniques are statistics, histograms, sampling and parametric techniques. Any error within the result size estimates increases the amount of joins. Thus, the most operation of query optimizer includes transforming queries, estimating and generating plans.The present article is an effort to debate about the fundamentals of query optimization.

Keywords:
Query, Optimization, Fundamental, Big Data