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Author: Alexandr Savinov

Affiliation: Bosch Software Innovations GmbH, Germany

ISBN: 978-989-758-245-5

Keyword(s): Data Processing, Grouping and Aggregation, Data Accumulation, Concept-oriented Model.

Abstract: Most of the currently existing query languages and data processing frameworks rely on one or another form of the group-by operation for data aggregation. In this paper, we critically analyze properties of this operation and describe its major drawbacks. We also describe an alternative approach to data aggregation based on accumulate functions and demonstrate how it can solve these problems. Based on this analysis, we argue that accumulate functions should be preferred to group-by as the main operation for data aggregation.

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Paper citation in several formats:
Savinov A. (2017). From Group-by to Accumulation: Data Aggregation Revisited.In Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-245-5, pages 370-379. DOI: 10.5220/0006359803700379

@conference{iotbds17,
author={Alexandr Savinov},
title={From Group-by to Accumulation: Data Aggregation Revisited},
booktitle={Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2017},
pages={370-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006359803700379},
isbn={978-989-758-245-5},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - From Group-by to Accumulation: Data Aggregation Revisited
SN - 978-989-758-245-5
AU - Savinov A.
PY - 2017
SP - 370
EP - 379
DO - 10.5220/0006359803700379

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