Measuring the Performance of Data Placement Structures for MapReduce-based Data Warehousing Systems

S. K. Makki; M. R. Hasan

DOI:10.17781/P002371

Corpus ID: 55639949

Measuring the Performance of Data Placement Structures for MapReduce-based Data Warehousing Systems

@article{Makki2018MeasuringTP,
  title={Measuring the Performance of Data Placement Structures for MapReduce-based Data Warehousing Systems},
  author={S. K. Makki and M. R. Hasan},
  journal={International journal of new computer architectures and their applications},
  year={2018},
  volume={8},
  pages={11-20}
}

S. K. Makki, M. R. Hasan

Published 2018

Computer Science

International journal of new computer architectures and their applications

The exponential growth of data requires systems that are able to provide a scalable and fault-tolerant infrastructure for storage and processing of vast amount of data efficiently. Hive is a MapReduce-based data warehouse for data aggregation and query analysis. This data warehousing system can arrange millions of rows of data into tables, and its data placement structures play a significant role for increasing the performance of this data warehouse. Hive also provides SQL-like language called… CONTINUE READING

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