efficient sort search on massive data
M.Ishwarya,S.Kalaiarasi,M.Revathy
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:4 Issue:3 Year: 29 March,2016 Pages:502-507
Abstract
Efficient top-N retrieval of records from a database has been an active research field for many years. We approach the problem from a real-world application point of view, in which the order of records according to some similarity function on an attribute is not unique. Many records have same values in several attributes and thus their ranking in those attributes is arbitrary (based on random choice). For instance, in large person databases many individuals have the same first name, the same date of birth, or live in the same city. Existing algorithms (Table-scan bassed T2S algorithm) are ill-equipped to handle such cases efficiently. We experimentally show that our method outperforms Dynamic Sorting Algorithm (DSA) for top-k retrieval in those very common cases where we used with dynamically scheduling the resources based on the data which are provided with, this efficient short search algorithm along with the massive data retrieval on a very fine tuple data’s can be of a different dataset.Here in this Project we are going to use these logics for the need of solution in the field of medical research. Where there are many manageable databases that are been used in a common path for the end of healthy need and the retrieval of solution for the cause of illness to a human being.
Kewords
Massive data, dynamic sort searcher, selection sort searcher, selective retrieval
Reference
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