HIPI: A REVIEW ON HADOOP MAP REDUCE FRAMEWORK USING IMAGE PROCESSING IN BIGDATA
DOI:
https://doi.org/10.26438/ijcse/v6si8.914Keywords:
Hadoop, Map reduce, Big data, Image Processing, HIPIAbstract
Nowadays, Big data is growing vey faster in the world. Big data is the large volume of data that consists of both structured and unstructured on a day-to-day basis. But it's not the amount of data. Big data is the data which includes sensor data, biometric data, Geo-spatial, Healthcare, power grid, transport, search engine and in Social networks. Hadoop process large amounts of data, in parallel, clusters of commodity hardware in a reliable and fault-tolerant manner. In this paper we review the Image processing using Map reduce technique with the help of HIPI (the image processing Tool).
References
[1] https://zephoria.com/top-15-valuable-facebook-statistics
[2]Hadoop map reduce framework.http://hadoop.apache.org/mapreduce/.
[3]Customizing input file formats for image processing in hadoop. Arizona State University. Online at: http://hpc. asu. edu/node/97.
[4]DEAN, J.,AND GHEMAWAT,S.2008. Mapreduce: Simplified data processing on large clusters. Communications of the ACM 51, 1,107–113.
[5] PDF: HIPI: A Hadoop Image Processing Interface for Image-based Map Reduce Tasks. Available from: https://www.researchgate.net/publication/266464321_HIPI_A_Hadoop_Image_Processing_Interface_for_Image-based_MapReduce_Tasks [accessed Jul 18 2018]
[6] http://hipi.cs.virginia.edu/
[7] https://github.com/uvagfx/hipi
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