AROMA: automated resource allocation and configuration of mapreduce environment in the cloud

@inproceedings{Lama2012AROMAAR,
  title={AROMA: automated resource allocation and configuration of mapreduce environment in the cloud},
  author={Palden Lama and Xiaobo Zhou},
  booktitle={ICAC},
  year={2012}
}
Distributed data processing framework MapReduce is increasingly deployed in Clouds to leverage the pay-per-usage cloud computing model. Popular Hadoop MapReduce environment expects that end users determine the type and amount of Cloud resources for reservation as well as the configuration of Hadoop parameters. However, such resource reservation and job provisioning decisions require in-depth knowledge of system internals and laborious but often ineffective parameter tuning. We propose and… CONTINUE READING
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