Distinction of Discrete Transformations Applied to Hadoop's MapReduce

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Hadoop MapReduce is an effective data processing platform for both commercial as well as academic applications. It intends the simplification of vast quantities of data as well as ease of processing in parallel on enormous clusters of hardware in a fault-tolerant and dependable approach. There are many modifications possible in the MapReduce to increase the performance along with increasing the simplicity of job tuning. Three of the adaptive run-time techniques namely, HIPI (Hadoop Image Processing Interface), distributed (HOG) Hadoop MapReduce On Grid and using SAMs (Situation Aware Mappers) are described and compared in the following paper.

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