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Big Data Frameworks for Efficient Range Queries to Extract Interested Rectangular Sub Regions

International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 119 - Number 22
Year of Publication: 2015
Süleyman Eken
Ahmet Sayar

Suleyman Eken and Ahmet Sayar. Article: Big Data Frameworks for Efficient Range Queries to Extract Interested Rectangular Sub Regions. International Journal of Computer Applications 119(22):36-39, June 2015. Full text available. BibTeX

	author = {Suleyman Eken and Ahmet Sayar},
	title = {Article: Big Data Frameworks for Efficient Range Queries to Extract Interested Rectangular Sub Regions},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {119},
	number = {22},
	pages = {36-39},
	month = {June},
	note = {Full text available}


A satellite object can consist of more than one mosaic image. To extract any object from remote sensing satellite images, mosaic images need to be stitched. It is critical problem that which mosaics will be selected for image stitching among big mosaic dataset. In this paper, we propose two approaches to overcome mosaic selection problem by means of finding rectangular sub regions intersecting with range query. Former one is based on hybrid of Apache Hadoop and HBase and latter one is based on Apache Lucene. Their effectiveness has been compared in terms of response time under varying number of mosaics.


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