Research on the Advanced Computing Method for Supporting Large Data Quality Assessment and Improvement
- https://doi.org/10.2991/icmmita-16.2016.29How to use a DOI?
- Cross-database Queries; Big Data Processing; Apache Hive; Data Quality Assessment and Improvement; Task Relevance.
To support the high efficient and fast data quality assessment of electrical operation, we need to make optimization of high performance computing technology on computing platform, this paper carry out in-depth research on the performance bottleneck that the data quality evaluation system faces, after the analysis of big data platform on data quality assessment and improvement, we make the design and implementation of easily cross-database queries, which can seamlessly integrate relational data into Hadoop ecosystem, and put forward a kind of optimization model for Hive by considering task relevance.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - He Yang AU - Jiangqi Chen AU - Xiaojia Xiang AU - Heng Liu AU - Yunpeng Li PY - 2017/01 DA - 2017/01 TI - Research on the Advanced Computing Method for Supporting Large Data Quality Assessment and Improvement BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 143 EP - 151 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.29 DO - https://doi.org/10.2991/icmmita-16.2016.29 ID - Yang2017/01 ER -