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- W4295682210 abstract "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 (LSM) 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." @default.
- W4295682210 created "2022-09-14" @default.
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- W4295682210 date "2022-09-12" @default.
- W4295682210 modified "2023-10-18" @default.
- W4295682210 title "Robust and Scalable Content-and-Structure Indexing (Extended Version)" @default.
- W4295682210 doi "https://doi.org/10.48550/arxiv.2209.05126" @default.
- W4295682210 hasPublicationYear "2022" @default.
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