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The RUM-tree: supporting frequent updates in R-trees using memos

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Abstract

The problem of frequently updating multi-dimensional indexes arises in many location-dependent applications. While the R-tree and its variants are the dominant choices for indexing multi-dimensional objects, the R-tree exhibits inferior performance in the presence of frequent updates. In this paper, we present an R-tree variant, termed the RUM-tree (which stands for R-tree with update memo) that reduces the cost of object updates. The RUM-tree processes updates in a memo-based approach that avoids disk accesses for purging old entries during an update process. Therefore, the cost of an update operation in the RUM-tree is reduced to the cost of only an insert operation. The removal of old object entries is carried out by a garbage cleaner inside the RUM-tree. In this paper, we present the details of the RUM-tree and study its properties. We also address the issues of crash recovery and concurrency control for the RUM-tree. Theoretical analysis and comprehensive experimental evaluation demonstrate that the RUM-tree outperforms other R-tree variants by up to one order of magnitude in scenarios with frequent updates.

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Authors and Affiliations

  1. Department of Computer Sciences, Purdue University, West Lafayette, IN, 47907-2107, USA

    Yasin N. Silva, Xiaopeng Xiong & Walid G. Aref

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  1. Yasin N. Silva
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  2. Xiaopeng Xiong
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  3. Walid G. Aref
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Correspondence to Walid G. Aref.

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Silva, Y.N., Xiong, X. & Aref, W.G. The RUM-tree: supporting frequent updates in R-trees using memos. The VLDB Journal 18, 719–738 (2009). https://doi.org/10.1007/s00778-008-0120-3

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  • DOI: https://doi.org/10.1007/s00778-008-0120-3

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