Partial Adaptive Indexing for Approximate Query Answering
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916337287168000 |
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| author | Maroulis, Stavros Bikakis, Nikos Stamatopoulos, Vassilis Papastefanatos, George |
| author_facet | Maroulis, Stavros Bikakis, Nikos Stamatopoulos, Vassilis Papastefanatos, George |
| contents | In data exploration, users need to analyze large data files quickly, aiming to minimize data-to-analysis time. While recent adaptive indexing approaches address this need, they are cases where demonstrate poor performance. Particularly, during the initial queries, in regions with a high density of objects, and in very large files over commodity hardware. This work introduces an approach for adaptive indexing driven by both query workload and user-defined accuracy constraints to support approximate query answering. The approach is based on partial index adaptation which reduces the costs associated with reading data files and refining indexes. We leverage a hierarchical tile-based indexing scheme and its stored metadata to provide efficient query evaluation, ensuring accuracy within user-specified bounds. Our preliminary evaluation demonstrates improvement on query evaluation time, especially during initial user exploration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_18702 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Partial Adaptive Indexing for Approximate Query Answering Maroulis, Stavros Bikakis, Nikos Stamatopoulos, Vassilis Papastefanatos, George Databases H.3.1; H.2.4; E.1 In data exploration, users need to analyze large data files quickly, aiming to minimize data-to-analysis time. While recent adaptive indexing approaches address this need, they are cases where demonstrate poor performance. Particularly, during the initial queries, in regions with a high density of objects, and in very large files over commodity hardware. This work introduces an approach for adaptive indexing driven by both query workload and user-defined accuracy constraints to support approximate query answering. The approach is based on partial index adaptation which reduces the costs associated with reading data files and refining indexes. We leverage a hierarchical tile-based indexing scheme and its stored metadata to provide efficient query evaluation, ensuring accuracy within user-specified bounds. Our preliminary evaluation demonstrates improvement on query evaluation time, especially during initial user exploration. |
| title | Partial Adaptive Indexing for Approximate Query Answering |
| topic | Databases H.3.1; H.2.4; E.1 |
| url | https://arxiv.org/abs/2407.18702 |