A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
MapReduce is an important method for large-scale data processing on parallel architecture. In Hadoop ecosystem, MapReduce runs on the application-level, thus it provides system with flexibility. MapReduce is good at offline batch processing and it could accelerate the whole execution time. The deficiency of the MapReduce architecture is a lack in balancing and scalability, thus leads to low efficiency when dealing with large-scale data. In this paper, we propose a new MapReduce framework thatdoi:10.2174/1874110x01509010253 fatcat:fvkdcz4dtbatpcbsr6wsgj2o5a