Query-Log Aware Data Replicated Declustering
Anisaara Nadaph1, Vikas Maral2
1Anisaara Nadaph, Computer Engg, K.J College Of Engg. And Management Research, Pune, India.
2Prof. Vikas Maral, Computer Engg, K.J College Of Engg. And Management Research, Pune, India.
Manuscript received on March 12, 2013. | Revised Manuscript received on April 14, 2013. | Manuscript published on April 30, 2013. | PP: 172-177 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1339042413/2013©BEIESP

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Abstract: Query-Log is general record of what mysqld is doing, the server writes information to this log when client connect or disconnect. Declustering parallelizes the query retrieval process by distributing the data items requested by queries among several disks. Replication enables alternative disk choices for individual disk items and thus provides better query parallelism options. existing replicated declustering schemes do not consider query log information and try to optimize all possible queries for a specificquery type, such as range or spatial queries. In such schemes, it is assumed that two or more copies of all data items are to be generated and these data items are copied to disks by different algorithm. However, It is not feasible in some applications for generation of even two copies of all of the data items, since data items tend to have very large sizes. In this work we assume that there is a given limit on disk capacities and thus on replication amounts. We utilize existing query-log information to propose a selective replicated declustering scheme, in which we select the data items to be replicated and decide on their scheduling onto disks. We suggest an iterative algorithm to get a two-way replicated decluster and by making use of this algorithm recursively to generate a multiway replicated declustering. Later by makiing use of efficient heuristics we improve the multi-way replicated declustering. The survey show that the suggested work gives bettter performance result over the existing replicated declustering schemes.
Keywords: Declustering, replication, Parallel disk architectures, Iterative improvement heuristics.