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Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce
Ablimit Aji1, Xiling Sun2, Hoang Vo1
1MathCS and BMI, Emory University.
Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
|September 13, 2016
Summary
Hadoop-GIS offers a scalable solution for high-performance spatial queries on large datasets using MapReduce. This system efficiently processes spatial data and supports complex queries for applications like pathology imaging and geo-spatial data warehousing.
Area of Science:
- Geographic Information Systems (GIS)
- Big Data Analytics
- Database Systems
Background:
- Massive spatial data growth from GPS devices and scientific instruments necessitates scalable solutions.
- Existing spatial data warehousing approaches face scalability limitations and efficiency bottlenecks.
Purpose of the Study:
- To present Hadoop-GIS, a scalable and high-performance spatial query system built on MapReduce.
- To demonstrate efficient processing of large-scale spatial data and queries.
Main Methods:
- Developed an efficient spatial query engine leveraging MapReduce.
- Implemented data and space-based partitioning for parallel query execution.
- Introduced an SQL-like spatial query language for workload specification.
Main Results:
- Hadoop-GIS demonstrates scalability and high performance for spatial queries over large datasets.
- Queries are translated to optimized MapReduce operators for efficient execution.
- The system effectively supports real-world use cases in pathology imaging and geo-spatial data warehousing.
Conclusions:
- Hadoop-GIS provides a robust solution for high-performance spatial data warehousing.
- The system addresses the need for efficient handling of massive spatial datasets.
- It enables advanced spatial analytics in fields like medical imaging and geo-informatics.
Keywords:
Analytical ImagingData WarehouseDatabaseHiveMapReduceScientific Data ManagementSpatial Query ProcessingMore Related Videos
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