• Mr.Pravin L Satore
• Mrs.Shital Y Gaikwad

The prime task of search computing is to join the results of complex query plans. In this survey we describe further views on topic by emphasizing the study on algorithms that operate with joining the ranked results produced by search services. This type of problem is categorized in the conventional rank aggregation, i.e., combining different ranked lists of objects to produce a single valid ranking. Rank-join algorithms provide best overall results without accessing total objects in ranked list. The rank-join problem has been dealt by extending rank aggregation algorithms to the case of join in the setting of relational databases. However, previous methods of top-k queries did not consider the distinctive features of search engines on the Web. However, in the context of search computing, joins differs from conventional relational concepts in many ways. Different access patterns are used to access the services i.e. some inputs needs to be provided; accessing services is costly, because usually they are remote. The output is returned in pages of answers and normally by some ranking criterion; multiple search services to answer the same query, in that user can interact to refine the search criteria. This survey reviews the challenges that are very important in the context of designing rank join algorithms for efficiency of search computing.

top-k, rank-join, query optimization, cost optimization, TA algorithm

"COST OPTIMIZED DATA ACCESS USING RANK JOIN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.24-28, April-2019, Available :http://www.jetir.org/papers/JETIRBD06006.pdf

"COST OPTIMIZED DATA ACCESS USING RANK JOIN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp24-28, April-2019, Available at : http://www.jetir.org/papers/JETIRBD06006.pdf