Web logs are the best repository of data that can be extracted, managed for searching and understanding usage pattern of customers, websites visited in a session, its intensity etc. Log file is a huge source of such data stored in an unformatted manner that can be molded as needed and filtered how required. Needed data can be mined using data mining techniques and then classify it to various groups based on similarity (homogenous groups) or clusters. The classified data then can be used to find out the desired result or make study accordingly. The purpose of this study is to make efficient searching of web pages by clustering techniques and extracting and reformatting data derived from web log to enhance the data extracted using hash key and value structure between the web log data and database storage before applying any clustering techniques applied. Once clustering had been done the desired result will be used to form query string based on search criteria and result will be displayed to the user.