Investigations on predicting patterns and anti patterns in sql query log using clustering and ensemble learning methods

Abstract

Data mining techniques present proficient structured query analysis newlinethrough clustering of similar patterns from query log dataset. During the newlinequery clustering process, identification of similar patterns is the most newlinesignificant task for minimizing the incorrect pattern detection. The effective newlineperformance of the query grouping helps to give enhanced results of antipattern newlinedetection with minimal complexity. With the help of ensemble newlineclustering technique, unnecessary patterns from the dataset are eliminated newlineeffectively. After eliminating the data from the dataset, similar patterns are newlinegrouped with enhanced performance of clustering. Thus, the determination of newlineanti-patterns from the dataset is a difficult one. The identification of antipatterns newlinefrom query log dataset is more significant in SQL query processing. newlineBefore the detection of anti-patterns, pattern clustering of queries are newlineperformed to minimize the complexity by means of the identifying similar newlinequery from the dataset. This aids to provide better results of pattern clustering newlinewith higher accuracy and minimum complexity. It is used for grouping newlinepatterns and anti-patterns effectively with minimum false-positive rate. newlineIn the recent research works, several ensemble-clustering techniques newlinehave been developed to correctly group query patterns into different clusters newlineat an earlier stage. Thus, techniques have been designed for solving the newlineproblem of pattern clustering for efficient detection of anti-patterns. In newlineaddition, many research works have been developed to provide enhanced antipattern newlinedetection in query log dataset. The major challenge is to attain higher newlinedetection accuracy with a minimized complexity. However, the detection of newlinepatterns from a large set of queries is difficult. It fails to detect the entire newlinepatterns in SQL query log. Due to the occurrence of anti-patterns, unwanted newlineSQL statements are provided with negative effects in query language newline