Virtual denormalization via array index reference for main memory OLAP

Yansong Zhang; Xuan Zhou; Ying Zhang; Yu Zhang; Mingchuan Su; Shan Wang

doi:10.1109/ICDE.2016.7498387

Virtual denormalization via array index reference for main memory OLAP

Yansong Zhang
, Xuan Zhou
, Ying Zhang
, Yu Zhang
, Mingchuan Su
, Shan Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Denormalization is a common tactic for enhancing performance of data warehouses. However, it is rarely used in main memory databases, which regards storage space as scarce resource. In this paper, we demonstrate that MMDB can actually benefit from the strategy of denormalization. We have created A-Store, a prototypical main-memory database system customized for star and snowflake schemas, which applies the strategy of denormalization to achieve highly efficient OLAP. Instead of resorting to fully materialized denormalization, A-Store applies a method called virtual denomalization, which allows query processing to be performed in a denormalized way, while without incurring additional space consumption.

Original language	English
Title of host publication	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1486-1487
Number of pages	2
ISBN (Electronic)	9781509020195
DOIs	https://doi.org/10.1109/ICDE.2016.7498387
State	Published - 22 Jun 2016
Externally published	Yes
Event	32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: 16 May 2016 → 20 May 2016

Publication series

Name	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Conference

Conference	32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/Territory	Finland
City	Helsinki
Period	16/05/16 → 20/05/16

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10.1109/ICDE.2016.7498387

Cite this

Zhang, Y., Zhou, X., Zhang, Y., Zhang, Y., Su, M., & Wang, S. (2016). Virtual denormalization via array index reference for main memory OLAP. In 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016 (pp. 1486-1487). Article 7498387 (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDE.2016.7498387

@inproceedings{b091afaf4de749cea996a919093fe8ac,

title = "Virtual denormalization via array index reference for main memory OLAP",

abstract = "Denormalization is a common tactic for enhancing performance of data warehouses. However, it is rarely used in main memory databases, which regards storage space as scarce resource. In this paper, we demonstrate that MMDB can actually benefit from the strategy of denormalization. We have created A-Store, a prototypical main-memory database system customized for star and snowflake schemas, which applies the strategy of denormalization to achieve highly efficient OLAP. Instead of resorting to fully materialized denormalization, A-Store applies a method called virtual denomalization, which allows query processing to be performed in a denormalized way, while without incurring additional space consumption.",

author = "Yansong Zhang and Xuan Zhou and Ying Zhang and Yu Zhang and Mingchuan Su and Shan Wang",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 32nd IEEE International Conference on Data Engineering, ICDE 2016 ; Conference date: 16-05-2016 Through 20-05-2016",

year = "2016",

month = jun,

day = "22",

doi = "10.1109/ICDE.2016.7498387",

language = "英语",

series = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1486--1487",

booktitle = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",

address = "美国",

}

Zhang, Y, Zhou, X, Zhang, Y, Zhang, Y, Su, M & Wang, S 2016, Virtual denormalization via array index reference for main memory OLAP. in 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016., 7498387, 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1486-1487, 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, 16/05/16. https://doi.org/10.1109/ICDE.2016.7498387

Virtual denormalization via array index reference for main memory OLAP. / Zhang, Yansong; Zhou, Xuan; Zhang, Ying et al.
2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1486-1487 7498387 (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2016/6/22

Y1 - 2016/6/22

N2 - Denormalization is a common tactic for enhancing performance of data warehouses. However, it is rarely used in main memory databases, which regards storage space as scarce resource. In this paper, we demonstrate that MMDB can actually benefit from the strategy of denormalization. We have created A-Store, a prototypical main-memory database system customized for star and snowflake schemas, which applies the strategy of denormalization to achieve highly efficient OLAP. Instead of resorting to fully materialized denormalization, A-Store applies a method called virtual denomalization, which allows query processing to be performed in a denormalized way, while without incurring additional space consumption.

AB - Denormalization is a common tactic for enhancing performance of data warehouses. However, it is rarely used in main memory databases, which regards storage space as scarce resource. In this paper, we demonstrate that MMDB can actually benefit from the strategy of denormalization. We have created A-Store, a prototypical main-memory database system customized for star and snowflake schemas, which applies the strategy of denormalization to achieve highly efficient OLAP. Instead of resorting to fully materialized denormalization, A-Store applies a method called virtual denomalization, which allows query processing to be performed in a denormalized way, while without incurring additional space consumption.

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M3 - 会议稿件

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BT - 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhang Y, Zhou X, Zhang Y, Zhang Y, Su M, Wang S. Virtual denormalization via array index reference for main memory OLAP. In 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1486-1487. 7498387. (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016). doi: 10.1109/ICDE.2016.7498387

Virtual denormalization via array index reference for main memory OLAP

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