research-article

HICAMP bitmap: space-efficient updatable bitmap index for in-memory databases

Authors:

David R. CheritonAuthors Info & Claims

DaMoN '14: Proceedings of the Tenth International Workshop on Data Management on New Hardware

Article No.: 7, Pages 1 - 7

https://doi.org/10.1145/2619228.2619235

Published: 23 June 2014 Publication History

Abstract

Bitmap represents an efficient indexing structure for querying large amounts of data and is widely deployed in data-warehouse applications. While the size of a bitmap scales linearly with the number of rows in a table, due to its sparseness, it can be greatly reduced via compression based on run-length encoding. However, updating a compressed bitmap is expensive due to the encoding and decoding overheads, in particular, as re-compression can change the compressed sequence length and data layout. Due to this problem, bitmap indices only perform well for read-only workloads.

In this paper, we propose a bitmap index structure which is both space-efficient and allows fast updates, by building on top of a smart memory model called HICAMP. As a consequence, our approach enables bitmap indices for workloads that exhibit high update ratios as in OLTP workloads. We also present a new multi-bit bitmap design which addresses the candidate checking problem. In our experiments, the HICAMP bitmap index demonstrates 3~12x reduction in size over B-tree and 8~30x over other commonly used indexing structures such as Red-Black tree, while supporting efficient updates simultaneously.

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Cited By

Klabe SSattler KBaumann S(2021)Updatable Materialization of Approximate Constraints2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00189(1991-1996)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00189
Lang HBeischl ALeis VBoncz PNeumann TKemper AMaier DPottinger RDoan ATan WAlawini ANgo H(2020)Tree-Encoded BitmapsProceedings of the 2020 ACM SIGMOD International Conference on Management of Data10.1145/3318464.3380588(937-967)Online publication date: 11-Jun-2020
https://dl.acm.org/doi/10.1145/3318464.3380588
Athanassoulis MYan ZIdreos SÖzcan FKoutrika GMadden S(2016)UpBitProceedings of the 2016 International Conference on Management of Data10.1145/2882903.2915964(1319-1332)Online publication date: 26-Jun-2016
https://dl.acm.org/doi/10.1145/2882903.2915964

Index Terms

HICAMP bitmap: space-efficient updatable bitmap index for in-memory databases

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cover image ACM Conferences

DaMoN '14: Proceedings of the Tenth International Workshop on Data Management on New Hardware

June 2014

71 pages

ISBN:9781450329712

DOI:10.1145/2619228

Editors:
Alfons Kemper
Technische Universitat Munchen
,
Ippokratis Pandis
Cloudera

Copyright © 2014 ACM.

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Published: 23 June 2014

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SIGMOD/PODS'14: International Conference on Management of Data

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Cited By

Klabe SSattler KBaumann S(2021)Updatable Materialization of Approximate Constraints2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00189(1991-1996)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00189
Lang HBeischl ALeis VBoncz PNeumann TKemper AMaier DPottinger RDoan ATan WAlawini ANgo H(2020)Tree-Encoded BitmapsProceedings of the 2020 ACM SIGMOD International Conference on Management of Data10.1145/3318464.3380588(937-967)Online publication date: 11-Jun-2020
https://dl.acm.org/doi/10.1145/3318464.3380588
Athanassoulis MYan ZIdreos SÖzcan FKoutrika GMadden S(2016)UpBitProceedings of the 2016 International Conference on Management of Data10.1145/2882903.2915964(1319-1332)Online publication date: 26-Jun-2016
https://dl.acm.org/doi/10.1145/2882903.2915964

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