@article{Zhao2014, 
author = {Yaxiong Zhao and Jie Wu and Cong Liu},
title = {Dache: A Data Aware Caching for Big-Data Applications Using the MapReduce Framework},
year = {2014},
journal = {Tsinghua Science and Technology},
volume = {19},
number = {1},
pages = {39-50},
keywords = {big-data, MapReduce, Hadoop, caching},
url = {https://www.sciopen.com/article/10.1109/TST.2014.6733207},
doi = {10.1109/TST.2014.6733207},
abstract = {The buzz-word big-data refers to the large-scale distributed data processing applications that operate on exceptionally large amounts of data. Google’s MapReduce and Apache’s Hadoop, its open-source implementation, are the defacto software systems for big-data applications. An observation of the MapReduce framework is that the framework generates a large amount of intermediate data. Such abundant information is thrown away after the tasks finish, because MapReduce is unable to utilize them. In this paper, we propose Dache, a data-aware cache framework for big-data applications. In Dache, tasks submit their intermediate results to the cache manager. A task queries the cache manager before executing the actual computing work. A novel cache description scheme and a cache request and reply protocol are designed. We implement Dache by extending Hadoop. Testbed experiment results demonstrate that Dache significantly improves the completion time of MapReduce jobs.}
}