Efficient Processing of Skyline Queries Using MapReduce

Abstract

Efficient Processing of Skyline Queries Using MapReduce java project report Subspace skyline, as an important variant of skyline, has been widely applied for multiple-criteria decisions, business planning. With the development of mobile internet, subspace skyline query in mobile distributed environments has recently attracted considerable attention. However, efficiently obtaining the meaningful subset of skyline points in any subspace remains a challenging task in the current mobile internet. For more and more mobile applications, subspace skyline query on mobile units is usually limited by big data and wireless bandwidth. To address this issue, in this paper, we propose a system model that can support subspace skyline query in mobile distributed environment.

System Configuration:

H/W System Configuration:-

System          : Pentium I3 Processor.
Hard Disk       : 500 GB.
Monitor          : Standard LED Monitor
Input Devices : Keyboard
Ram               : 4 GB

S/W System Configuration:-

Operating system              : Windows 7/8/10.
Available Coding Language : Java and Phonegap
Database                          : MYSQL

Conclusion 

In Efficient Processing of Skyline Queries Using MapReduce java project report paper, we present a system model for supporting subspace skyline query in mobile distributed environments. The subspace skyline query algorithm can report the meaningful subset of skyline points from the full set of skyline 460 points. To reduce network communication and to shorten response time, we propose a pruning strategy for reducing the amount of data prior to computing the skyline points.

To support subspace skyline query, we construct a global index according to value of each dimension using MapReduce. During the processing of skyline query, we extract the attributes of interest from the entire index. 465 Finally, we eliminate some tuples that are worse in the important attributes using the SQM-filtering method or 𝜀-filtering method. Our scheme alleviates the problem of there being too many skyline points to perform a manual evaluation. The experimental results indicate that the subspace skyline algorithm is highly efficient.