Clustering is the unsupervised classification of data items into homogeneous groups called clusters. Data linkage is the task of identifying different data items that refer to the same entity across different data sources. De-duplicating one data set or linking several data sets are important tasks in the data preparation steps of many data mining process. Data linkage is traditionally performed among tables to cluster the data. Traditional method has taken long time for clustering the data from data sets. In this new proposed technique, allowing many such operators are to be active in parallel. TWAC is optimized to produce initial results quickly and can hide irregular delays in data arrival by reactively scheduling background processing. The main aim of this paper is optimizing a query clustering operation and execution. Depending upon given query, entail column only linked and clustered from weather data sets. Finally, particular data's will be clustered and exhibited with clustering timing. Therefore, compared to traditional method, TWA clustering method is rapidly to cluster the data from data set. Eventually, comparisons of execution details are stored in a log file (i.e., txt file). This log file is used to viewing the data in SAP-Crystal report. So, TWACA is an effective solution for providing fast query responses to users, even in the presence of slow and bursty remote sources.
