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
Space-filling curves and their use in the design of geometric data structures
Theoretical Computer Science - Special issue: Latin American theoretical informatics
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Using Space-Filling Curves for Multi-dimensional Indexing
BNCOD 17 Proceedings of the 17th British National Conferenc on Databases: Advances in Databases
Master-Client R-Trees: A New Parallel R-Tree Architecture
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Parallel bulk-loading of spatial data
Parallel Computing - Special issue: High performance computing with geographical data
Map-reduce-merge: simplified relational data processing on large clusters
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Automatic alignment of large-scale aerial rasters to road-maps
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Materialized community ground models for large-scale earthquake simulation
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Parallel processing of data from very large-scale wireless sensor networks
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Towards personal high-performance geospatial computing (HPC-G): perspectives and a case study
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
A MapReduce approach to Gi*(d) spatial statistic
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
Spatial scene similarity assessment on Hadoop
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
Scalable and Distributed Processing of Scientific XML Data
GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
High performance spatial query processing for large scale scientific data
PhD '12 Proceedings of the on SIGMOD/PODS 2012 PhD Symposium
ComMapReduce: an improvement of mapreduce with lightweight communication mechanisms
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Multimedia Applications and Security in MapReduce: Opportunities and Challenges
Concurrency and Computation: Practice & Experience
Collaborative geospatial feature search
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Towards building a high performance spatial query system for large scale medical imaging data
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
MobiS: a distributed paradigm of mobile sensor data analytics for evaluating environmental exposures
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
Computational Engineering in the Cloud: Benefits and Challenges
Journal of Organizational and End User Computing
Sort-based parallel loading of R-trees
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
The family of mapreduce and large-scale data processing systems
ACM Computing Surveys (CSUR)
Efficient distributed multi-dimensional index for big data management
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
CG_Hadoop: computational geometry in MapReduce
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Hadoop GIS: a high performance spatial data warehousing system over mapreduce
Proceedings of the VLDB Endowment
Balancing reducer workload for skewed data using sampling-based partitioning
Computers and Electrical Engineering
| Hi-index | 0.03 |
The amount of information in spatial databases is growing as more data is made available. Spatial databases mainly store two types of data: raster data (satellite/aerial digital images), and vector data (points, lines, polygons). The complexity and nature of spatial databases makes them ideal for applying parallel processing. MapReduce is an emerging massively parallel computing model, proposed by Google. In this work, we present our experiences in applying the MapReduce model to solve two important spatial problems: (a) bulk-construction of R-Trees and (b) aerial image quality computation, which involve vector and raster data, respectively. We present our results on the scalability of MapReduce, and the effect of parallelism on the quality of the results. Our algorithms were executed on a Google&IBM cluster, which became available to us through an NSF-supported program. The cluster supports the Hadoop framework --- an open source implementation of MapReduce. Our results confirm the excellent scalability of the MapReduce framework in processing parallelizable problems.