Query optimization for massively parallel data processing

@inproceedings{Wu2011QueryOF,
  title={Query optimization for massively parallel data processing},
  author={Sai Wu and Feng Li and Sharad Mehrotra and Beng Chin Ooi},
  booktitle={SoCC},
  year={2011}
}
MapReduce has been widely recognized as an efficient tool for large-scale data analysis. It achieves high performance by exploiting parallelism among processing nodes while providing a simple interface for upper-layer applications. Some vendors have enhanced their data warehouse systems by integrating MapReduce into the systems. However, existing MapReduce-based query processing systems, such as Hive, fall short of the query optimization and competency of conventional database systems. Given an… CONTINUE READING
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