IEICE TRANSACTIONS on Information
History-Pattern Encoding for Large-Scale Dynamic Multidimensional Datasets and Its Evaluations
Summary :
In this paper, we present a new encoding/decoding method for dynamic multidimensional datasets and its implementation scheme. Our method encodes an n-dimensional tuple into a pair of scalar values even if n is sufficiently large. The method also encodes and decodes tuples using only shift and and/or register instructions. One of the most serious problems in multidimensional array based tuple encoding is that the size of an encoded result may often exceed the machine word size for large-scale tuple sets. This problem is efficiently resolved in our scheme. We confirmed the advantages of our scheme by analytical and experimental evaluations. The experimental evaluations were conducted to compare our constructed prototype system with other systems; (1) a system based on a similar encoding scheme called history-offset encoding, and (2) PostgreSQL RDBMS. In most cases, both the storage and retrieval costs of our system significantly outperformed those of the other systems.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.4 pp.989-999
- Publication Date
- 2016/04/01
- Publicized
- 2016/01/14
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2015DAP0025
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering and Information Management)
- Category
Authors
Masafumi MAKINO
NTT Neo-meito, Corporation
Tatsuo TSUJI
University of Fukui
Ken HIGUCHI
University of Fukui
Keyword
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Masafumi MAKINO, Tatsuo TSUJI, Ken HIGUCHI, "History-Pattern Encoding for Large-Scale Dynamic Multidimensional Datasets and Its Evaluations" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 4, pp. 989-999, April 2016, doi: 10.1587/transinf.2015DAP0025.
Abstract: In this paper, we present a new encoding/decoding method for dynamic multidimensional datasets and its implementation scheme. Our method encodes an n-dimensional tuple into a pair of scalar values even if n is sufficiently large. The method also encodes and decodes tuples using only shift and and/or register instructions. One of the most serious problems in multidimensional array based tuple encoding is that the size of an encoded result may often exceed the machine word size for large-scale tuple sets. This problem is efficiently resolved in our scheme. We confirmed the advantages of our scheme by analytical and experimental evaluations. The experimental evaluations were conducted to compare our constructed prototype system with other systems; (1) a system based on a similar encoding scheme called history-offset encoding, and (2) PostgreSQL RDBMS. In most cases, both the storage and retrieval costs of our system significantly outperformed those of the other systems.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015DAP0025/_p
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@ARTICLE{e99-d_4_989,
author={Masafumi MAKINO, Tatsuo TSUJI, Ken HIGUCHI, },
journal={IEICE TRANSACTIONS on Information},
title={History-Pattern Encoding for Large-Scale Dynamic Multidimensional Datasets and Its Evaluations},
year={2016},
volume={E99-D},
number={4},
pages={989-999},
abstract={In this paper, we present a new encoding/decoding method for dynamic multidimensional datasets and its implementation scheme. Our method encodes an n-dimensional tuple into a pair of scalar values even if n is sufficiently large. The method also encodes and decodes tuples using only shift and and/or register instructions. One of the most serious problems in multidimensional array based tuple encoding is that the size of an encoded result may often exceed the machine word size for large-scale tuple sets. This problem is efficiently resolved in our scheme. We confirmed the advantages of our scheme by analytical and experimental evaluations. The experimental evaluations were conducted to compare our constructed prototype system with other systems; (1) a system based on a similar encoding scheme called history-offset encoding, and (2) PostgreSQL RDBMS. In most cases, both the storage and retrieval costs of our system significantly outperformed those of the other systems.},
keywords={},
doi={10.1587/transinf.2015DAP0025},
ISSN={1745-1361},
month={April},}
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TY - JOUR
TI - History-Pattern Encoding for Large-Scale Dynamic Multidimensional Datasets and Its Evaluations
T2 - IEICE TRANSACTIONS on Information
SP - 989
EP - 999
AU - Masafumi MAKINO
AU - Tatsuo TSUJI
AU - Ken HIGUCHI
PY - 2016
DO - 10.1587/transinf.2015DAP0025
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2016
AB - In this paper, we present a new encoding/decoding method for dynamic multidimensional datasets and its implementation scheme. Our method encodes an n-dimensional tuple into a pair of scalar values even if n is sufficiently large. The method also encodes and decodes tuples using only shift and and/or register instructions. One of the most serious problems in multidimensional array based tuple encoding is that the size of an encoded result may often exceed the machine word size for large-scale tuple sets. This problem is efficiently resolved in our scheme. We confirmed the advantages of our scheme by analytical and experimental evaluations. The experimental evaluations were conducted to compare our constructed prototype system with other systems; (1) a system based on a similar encoding scheme called history-offset encoding, and (2) PostgreSQL RDBMS. In most cases, both the storage and retrieval costs of our system significantly outperformed those of the other systems.
ER -
English
