Random sampling with a reservoir
ACM Transactions on Mathematical Software (TOMS)
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Maintaining Sliding Window Skylines on Data Streams
IEEE Transactions on Knowledge and Data Engineering
Skyline Queries Against Mobile Lightweight Devices in MANETs
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Probabilistic skylines on uncertain data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient computation of reverse skyline queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Distributed Skyline Retrieval with Low Bandwidth Consumption
IEEE Transactions on Knowledge and Data Engineering
Probabilistic Skyline Operator over Sliding Windows
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Reverse skyline search in uncertain databases
ACM Transactions on Database Systems (TODS)
Online aggregation and continuous query support in MapReduce
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Preference query evaluation over expensive attributes
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Efficient confident search in large review corpora
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Efficient parallel skyline processing using hyperplane projections
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Adapting skyline computation to the MapReduce framework: algorithms and experiments
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Dynamic skyline queries in large graphs
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Proceedings of the 15th International Conference on Database Theory
Energy-Efficient Reverse Skyline Query Processing over Wireless Sensor Networks
IEEE Transactions on Knowledge and Data Engineering
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The skyline operator and its variants such as dynamic skyline and reverse skyline operators have attracted considerable attention recently due to their broad applications. However, computations of such operators are challenging today since there is an increasing trend of applications to deal with big data. For such data-intensive applications, the MapReduce framework has been widely used recently. In this paper, we propose efficient parallel algorithms for processing the skyline and its variants using MapReduce. We first build histograms to effectively prune out nonskyline (non-reverse skyline) points in advance. We next partition data based on the regions divided by the histograms and compute candidate (reverse) skyline points for each region independently using MapReduce. Finally, we check whether each candidate point is actually a (reverse) skyline point in every region independently. Our performance study confirms the effectiveness and scalability of the proposed algorithms.