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International Journal of Advanced Research Trends in Engineering and Technology (IJARTET) Vol. 1, Issue 2, October 2014

One-to-Many Linkage query using Two Way Adaptive Clustering algorithm P.Vijayameena1, R. Chithra Devi2 PG Scholar, Department of IT, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur1 Assistant Professor, Department of IT, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur2 Abstract: De-duplicating one data set or linking several data sets are increasingly important tasks in the data preparation steps of many data mining process. Record linkage is traditionally performed among tables to cluster the data. Old methods are taken long time for one-to-many linkage. Two Way Adaptive clustering algorithm (TWACA) is a new proposed technique, which has a small memory footprint, allowing many such operators to be active in parallel. TWACA is optimized to produce initial results quickly and can hide intermittent delays in data arrival by reactively scheduling background processing. We show that TWACA is an effective solution for providing fast query responses to users even in the presence of slow remote sources. Optimized One-to-Many queryclustering operation and execution is the main aim of this project. The first work of this project is projection. Required column only filtered from various data base. Then, three phases of TWACA named Arriving, Reactive, and Cleanup derived for result rate maximization.

Keywords: Data set, data linkage, clustering, two way adaptive clustering algorithm will then describe the problems with traditional query I. INTRODUCTION processing that adaptive query processing seeks to Record linkage is traditionally performed among overcome. And, lastly will outline various experimental the entities of same type [2]. It can be done based on entities solutions. that may or may not share a common identifier. A. Adaptive Query Processing Adaptive query processing refers to a set of Optimization is a critical component in the processing of each query submitted to a database management system techniques devised to combat the inherent of traditional (DBMS). The difference between a properly optimized query processing. It is aimed at producing optimal query query and an improperly optimized one is huge, as a plans at times that traditional plans fail. These techniques clustering following a suboptimal plan can take come in two factors: i) proactiveoperators, which are coded into an exponentially more time than the same query executed following an optimal plan. To determine the most efficient execution plan and autonomously adapt to run-time changes. ii) reactiveoptimizers, which reform the plan and manner in which to execute a given query, the DBMS must evaluate execution strategies and choose among the most reorder pre-existing operators due to run-time conditions. favorable calculated. II. RELATED WORK In recent years, database researchers have begun to A. Projection rethink the mechanisms for such clustering optimization. In Given that each input has a handling cost, there are part, this is due to the expansion of the internet and the twocases that we have to consider: distributed queries this has made possible, but the techniques 1. The cost of performing one projection is less uncovered can also be applied to non-distributed than or equal to the inter-arrival time for input objects (C 1ri environments. The research focuses on the consideration of π ≤ ). processing factors at the time that queries are executed, and 2. The cost of performing one projection is greater than the the adaptation of their execution in response to real-time inter-arrival time for input objects ( Cπ>1ri ). In this data sizes and transfer rates. [1] propose will outline the discussion, we incorporate the transmission cost T into the growing research field of adaptive Clustering processing. It handling cost. If we want to distinguish between them, we will start by first briefly explaining the mechanisms in can calculate the cost of handling an individual input as existing, traditional query processing common today and Cπ+T. Figure2 shows the consequences of each case. In the

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