On <i>k</i>-d Range Search with Patricia Tries

Nickerson, Bradford G.; Shi, Qingxiu

doi:10.1137/060653780

Cited by 4 publications

(1 citation statement)

References 10 publications

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“…If it is high and the other selectivity is low, the c-order curve performs badly. The zorder curve is a space-filling curve that is used, among others, by UB-trees [35] and k-d tries [30,33,36]. It is obtained by the bitwise interleaving of dimensions.…”

Section: Related Workmentioning

confidence: 99%

Dynamic interleaving of content and structure for robust indexing of semi-structured hierarchical data

2020

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We propose a robust index for semi-structured hierarchical data that supports content-and-structure (CAS) queries specified by path and value predicates. At the heart of our approach is a novel dynamic interleaving scheme that merges the path and value dimensions of composite keys in a balanced way. We store these keys in our trie-based Robust Content-And-Structure index, which efficiently supports a wide range of CAS queries, including queries with wildcards and descendant axes. Additionally, we show important properties of our scheme, such as robustness against varying selectivities, and demonstrate improvements of up to two orders of magnitude over existing approaches in our experimental evaluation.

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Section: Related Workmentioning

confidence: 99%

Dynamic interleaving of content and structure for robust indexing of semi-structured hierarchical data

2020

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Robust and scalable content-and-structure indexing

et al. 2022

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Frequent queries on semi-structured hierarchical data are Content-and-Structure (CAS) queries that filter data items based on their location in the hierarchical structure and their value for some attribute. We propose the Robust and Scalable Content-and-Structure (RSCAS) index to efficiently answer CAS queries on big semi-structured data. To get an index that is robust against queries with varying selectivities, we introduce a novel dynamic interleaving that merges the path and value dimensions of composite keys in a balanced manner. We store interleaved keys in our trie-based RSCAS index, which efficiently supports a wide range of CAS queries, including queries with wildcards and descendant axes. We implement RSCAS as a log-structured merge tree to scale it to data-intensive applications with a high insertion rate. We illustrate RSCAS’s robustness and scalability by indexing data from the Software Heritage (SWH) archive, which is the world’s largest, publicly available source code archive.

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